TRANSFORMATIVE

MARKETING
Combining New Age Technologies
and Human Insights

V. Kumar
Philip Kotler
Palgrave Executive Essentials
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 V. Kumar · Philip Kotler

Transformative
Marketing
Combining New Age Technologies
and Human Insights
V. Kumar Philip Kotler
Goodman School of Business Kellogg School of Management
Brock University Northwestern University
St. Catharines, ON, Canada Evanston, IL, USA

ISSN 2731-5614 ISSN 2731-5622 (electronic)

Palgrave Executive Essentials
ISBN 978-3-031-59636-0 ISBN 978-3-031-59637-7 (eBook)
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 Dedicated with Love
To my parents, Patta and Viswanathan, my uncle, Kannan
My wife, Aparna
my daughters’ family—Anita, Rohan, Ryan, Devin & Prita, Matt, Stephen and
Austin
my sister Shanti, brother-in-law Prasad, and their family,
my in-laws, Dr. Lalitha and Ramamurthy, and my spiritual guru, M.
Karthikeyan
—V. Kumar

Dedicated with Love

To my wife Nancy in celebration of our
69 wonderful years of marriage, love
and happiness.
—Philip Kotler
 Preface

The realm of new-age technologies is captivating and profound about

their influence on the constantly evolving marketing landscape and human
understanding. In continuing with the ongoing evolution of digital tech-
nologies, we stand at the intersection of innovation and interconnectedness,
where state-of-the-art technologies are revolutionizing the methods through
which businesses engage, comprehend, and establish connections with their
customer bases.
Progress in technology has a significant impact on the way consumers
establish connections with companies. With the rise of tech-savvy customers,
there is a growing demand for quick and effortless digital experiences, along
with an expectation for immediate solutions to their requirements. Conse-
quently, businesses are adapting their practices by embracing technology
at a faster pace, revamping their procedures, creating new organizational
frameworks, and introducing innovative business models. By allocating more
resources to technological advancements, companies can reap the advantages
of reduced expenses, improved efficiency, and a better ability to meet the
expectations of stakeholders.
Welcome to a new marketing era, one that is powered by technologies
of the modern age—the likes of artificial intelligence, machine learning,
drones, robotics, and many more. This book serves as a valuable guide to
navigating this new world, where the marketing function takes on various
roles in shaping, creating, executing, and influencing both human minds and
technological advancements in the rapidly evolving marketplace.

vii
viii Preface

The emergence of cutting-edge technologies like AI, metaverse, drones,

and IoT has paved the way for a fresh wave of marketing opportunities.
This signifies the commencement of a transformative journey that explores
the complexities of these technologies, their role in driving innovation, how
they reshape customer interaction, and how they enhance the effectiveness
of marketing endeavors. From the tailored experiences enabled by machine
learning algorithms to the captivating encounters made feasible by the meta-
verse, this book will guide readers through the technological terrain that is
propelling marketing through interesting times.
Significantly, this book delves into more than just the visible techno-
logical progress that surrounds us. By delving into these advancements,
this book uncovers the interconnectedness between technology and human
emotions and understanding. In the age of extensive data, comprehending
the intricacies of consumer behavior has become more complex and nuanced
than ever before. Modern technologies not only enable the gathering of
massive data sets but also empower marketers to extract valuable insights
that can guide strategic choices and foster business expansion. In essence,
this book commemorates the essence of the human spirit within the realm of
technology.
Moreover, this book delves into the challenges that marketing departments
face when dealing with new-age technologies. It emphasizes the need for
knowledge on which technology to use, how to use it, and when and why
it should be used. Additionally, it highlights the significance of the data
generated from successful technology deployment, which provides valuable
feedback to marketers. The book also addresses the handling of this abundant
data and the insights it offers for developing solutions and designing growth
strategies that align with both firm profitability and stakeholder well-being.
This book is aimed at the top-level and mid-level management, who have
the power and resources to change the design, development, and implemen-
tation of marketing strategies in their organization. This book also serves
as a guide for executives on the rise to understand how new-age tech-
nologies interface with conventional and emerging marketing practices in
the marketplace. Further, graduate /undergraduate/honors students in Busi-
ness and Marketing programs will also stand to gain from this book as it
covers emerging topics in technology and marketing. Therefore, this book
 Preface ix

can be adopted as a required/ supplemental/ recommended reading for

courses including Customer Relationship Management (CRM), Customer
Engagement, Technology Marketing, Technology Management, Social Media
Marketing, Digital Marketing, Marketing Analytics, and Marketing Strategy.

St. Catharines, Canada V. Kumar

Evanston, USA Philip Kotler
 Acknowledgments

We thank Bharath Rajan, Namrata Manchiraju, and Ben deHooge for their
assistance in the preparation of this book. Many thanks to our colleagues,
who stimulated us and brought new ideas and approaches to our attention in
writing this book.
We also thank our coauthors in each of the studies referenced in this book
for their contributions. Additional thanks are also to the practitioner commu-
nity who gave us many opportunities to put ideas into practice and thus
broaden our understanding of new-age technologies as it is currently evolving.
We are grateful to the students who, through constant interaction,
provided valuable input and feedback from the consumer’s perspective.
We are thankful to Renu for copyediting the book content.
Dr. V. Kumar, who is also the Distinguished Scholar of Research, We
School, India; Distinguished Fellow, MICA, India; and Chang Jiang Scholar,
Huazhong University of Science and Technology, Wuhan, China, thanks the
generous support from these institutions for his ongoing research.

xi
 Praise for Transformative Marketing

“This is an important book from two of the most influential thought

leaders the marketing profession has produced. They welcome you, the
reader, as follows: ‘Welcome to a new marketing era…. powered by technolo-
gies of the modern age…artificial intelligence, machine learning, drones, robotics,
and…more. This book [is a] guide to navigating this new world …’. A world
traveler who arrives in unfamiliar country needs a reliable guidebook. All
marketing executives are now on a journey to an unfamiliar, rapidly changing,
technological world. They need this guidebook. A must read.”
—Gary L. Lilien, Distinguished Research Professor of Management Science,
Penn State

“I consider Prof. Kotler as my Marketing Guru. Partnering with Prof. Kumar,

he has produced yet another groundbreaking book, which is a must-read
for anyone looking to understand the dynamic interplay between cutting-
edge technologies and modern marketing practices, deftly integrated with
human insights. Whether you’re a top-level executive, a rising leader, or a
student in the field of business and marketing, this book will equip you
with the knowledge and strategies needed to thrive in today’s rapidly evolving
marketplace.”
—Raja Rajamannar, Chief Marketing Officer of Mastercard

xiii
xiv Praise for Transformative Marketing

“Technology always transforms businesses by changing customer behavior,

which, in turn, influences marketing strategies to attract new customers.
V. Kumar and Philip Kotler’s outstanding book is an excellent guide for
businesses looking to embrace the right technologies in the Marketing 5.0
era.”
—Hermawan Kartajaya, Founder and Chairman of MCorp (MarkPlus),
Indonesia

“This book is a breakthrough because it identifies the enormous breakthrough

technologies for marketing. The book is a must read for every marketer who
wants to stay on the ball.”
—Hermann Simon, Founder and honorary chairman of Simon-Kucher

“Marketing leaders that mindfully apply the capabilities of New Age Tech-
nologies ahead of rivals give their firms a durable advantage. Kotler and
Kumar give these leaders a valuable guide to the transformative potential of
these technologies.”
—George Day, Professor of Marketing, Wharton School, University of
Pennsylvania

“In their groundbreaking book, Kumar and Kotler provide a comprehen-

sive and insightful guide to the future of technology-powered marketing.
By expertly weaving together the latest advancements in technology with
timeless marketing principles, they offer a roadmap for businesses to stay
ahead in an increasingly competitive landscape. This book is a must-read for
anyone looking to transform their marketing capabilities by leveraging the
full potential of new age technologies.”
—Mohan Sawhney, Associate Dean for Digital Innovation, Director, Center
for Research in Technology & Innovation, Northwestern Kellogg School of
Management

“Transformative Marketing brilliantly navigates the evolving landscape of

marketing, offering a comprehensive guide to harnessing new-age technolo-
gies for success. In this groundbreaking work, the authors navigate the
dynamic landscape of modern marketing, skillfully dissecting the impact
of new-age technologies like AI, GAI, metaverse, robots, ML, drones, IoT,
and blockchain. This book is a must-read for marketers seeking to not only
survive but thrive in the dynamic, technology-driven future of the industry.”
—Prof. Dr. Marc Oliver Opresnik, Distinguished Professor of Marketing,
Luebeck University of Applied Sciences, Germany
 Praise for Transformative Marketing xv

“It is a New Age. Advances in technology have forced us to change the way
we make marketing decisions. It brings exciting opportunity for what we
produce, how we market our products and services, how we understand our
customers, and how customers connect with us and others. Kumar and Kotler
are at the forefront of the marketing impact brought to us by cutting edge
technology. Transformative Marketing is a must read—the alternative is to be
left behind.”
—David J. Reibstein, William Stewart Woodside Professor of Marketing,
Wharton, University of Pennsylvania

“Professor Kotler’s legacy in marketing is unparalleled, and Transformative

Marketing cements his position as a thought leader for the digital age. Don’t
just adapt to change; embrace it with the transformative insights offered
within these pages. Highly recommended!”
—Waldemar A. Pfoertsch, Senior Marketing Professor, CIIM Business School,
University of Limassol, Cyprus

“If you want to know how far behind you are in marketing technologies –
read this book!”
—Professor Hooi Den Huan, Nanhang Technological University, Singapore

“Transformative Marketing offers marketing managers a much needed

roadmap of how to utilize eight new technologies to deliver superior customer
experience and value while simultaneously increasing marketing efficiency.”
—V. “Seenu” Srinivasan, Adams Distinguished Professor of Management,
Emeritus, Stanford University

“With technological advances profoundly changing the marketing world,

there is a critical need for top marketers to develop new skills and thinking.
Thankfully, Transformative Marketing delves into the eight most important
new-age technologies to offer clarity and invaluable insight and inspiration
to front-line marketers of all ranks.”
—Kevin Lane Keller, E.B. Osborn Professor of Marketing, Tuck School of
Business at Dartmouth College

“Professors Kotler and Kumar are ideally placed to describe the “marketing
of the future” and do so with remarkable clarity and prescience. A must read
for marketing practitioners and students alike!”
—Dominique M. Hanssens, Distinguished Research Professor of Marketing,
UCLA Anderson School of Management
 Contents

1 Transformative Marketing Has Begun 1

Introduction 1
A Brief Overview of NATs 4
Looking Beyond the Digital Frontier of NATs 11
Organization of the Book 13
Notes and References 15
2 Transformative Marketing: A Marketing 5.0 Perspective 19
Introduction 19
Meaningful Connections Using Human Insights 20
Convergence of NATs and Marketing 22
Understanding Resources, Capabilities, and Strategies of NATs 23
Notes and References 26
3 Transformative Marketing with Artificial Intelligence 29
Overview 29
Origin, Definition, and Components of AI 32
The Rise of the Transformative Home 34
Personalized Education 35
The World of Wearables 36
AI in the Marketing 5.0 World 38
Data-Driven Marketing Using AI 39
Predictive Marketing Using AI 39
Contextual Marketing Using AI 40

xvii
xviii Contents

Augmented Marketing Using AI 41

Agile Marketing Using AI 42
Current AI Applications in Marketing 43
Understanding Customer Needs to Deploy AI 44
Revisiting Firm’s Capabilities to Integrate AI 45
Designing Marketing Mix Strategies with AI 46
Driving Customer Engagement Through AI 47
Designing Digital Strategies with AI 48
Future of AI in Marketing 49
AI in Social Media 51
Marketing Tools for AI 52
Seamless Integration of AI with Marketing—The New
Marketing Culture 52
Notes and References 55
4 Transformative Marketing with Generative Artificial
Intelligence 65
Overview 65
Origin, Definition, and Classification of Generative AI 67
Origin 67
Definition 68
Classification 69
Some Commercial Applications of GAI 71
Generative AI in the Marketing 5.0 World 75
Data-Driven Marketing Using GAI 75
Predictive Marketing Using GAI 76
Contextual Marketing Using GAI 77
Augmented Marketing Using GAI 78
Agile Marketing Using GAI 79
Current Generative AI Applications in Marketing 79
Understanding Customer Needs to Deploy GAI 81
Revisiting Firm Capabilities to Integrate GAI 82
Designing Marketing Mix Strategies with GAI 83
Driving Customer Engagement Through GAI 87
Designing Digital Strategies with GAI 88
Future of Generative AI in Marketing 89
Ultra-Personalized Experiences 90
Personalized Marketing at Scale 90
New Forms of Creative Content 91
 Contents xix

Ethical Considerations for Developing Marketing

Campaigns 92
Notes and References 94
5 Transformative Marketing with Machine Learning (ML) 103
Overview 103
Origin, Definition, and Components of ML 104
Analytics-Oriented Technology 108
Link to Artificial Intelligence 110
Machine Learning Models 112
Machine Learning in the Marketing 5.0 World 114
Data-Driven Marketing Using ML 114
Predictive marketing using ML 115
Contextual Marketing Using ML 116
Augmented Marketing Using ML 117
Agile Marketing Using ML 117
Current ML Applications in Marketing 118
Understanding Customer Needs to Deploy ML 119
Revisiting Firm Capabilities to Integrate ML 120
Designing Marketing Mix Strategies with ML 121
Driving customer engagement through ML 124
Designing Digital Strategies with ML 125
Future of ML in Marketing 126
ML and Customer Churn Analytics 127
Improvement to demand forecasting 128
Strategy Development for Customers and Products 130
Notes and References 133
6 Transformative Marketing with Metaverse 141
Overview 141
Origin, Definition, and Classifications of the Metaverse 142
Origin 142
Definition 144
Classification 145
Metaverse in the Marketing 5.0 World 145
Data-Driven Marketing Using the Metaverse 148
Predictive Marketing Using the Metaverse 149
Contextual Marketing Using the Metaverse 150
Augmented Marketing Using the Metaverse 151
Agile Marketing Using the Metaverse 151
Current Metaverse Applications in Marketing 152
xx Contents

Understanding Customer Needs to Deploy in the Metaverse 153

Revisiting Firm Capabilities to Integrate in the Metaverse 154
Designing Marketing Mix Strategies in the Metaverse 155
Driving Customer Engagement Through the Metaverse 158
Designing Digital Strategies Within the Metaverse 159
Future of Metaverse in Marketing 160
Technical Considerations 161
Social/Ethical Considerations 162
Economic Considerations 163
Notes and References 164
7 Transformative Marketing with the Internet of Things (IoT) 171
Overview 171
Origin, Definition, and Classifications of IoT 172
Individuals 173
Organization 174
Industry 174
National 175
IoT in the Marketing 5.0 World 181
Data-Driven Marketing Using IoT 181
Predictive Marketing Using IoT 182
Contextual Marketing Using IoT 183
Augmented Marketing Using IoT 184
Agile Marketing Using IoT 185
Current IoT Applications in Marketing 186
Understanding Customer Needs to Deploy IoT 186
Revisiting Firm Capabilities to Integrate IoT 187
Designing Marketing Mix Strategies with IoT 188
Driving Customer Engagement Through IoT 190
Designing Digital Strategies with IoT 191
Future of IoT in Marketing 192
IoT and Transportation 193
Smart Cities 194
Real-Time Buying Process and Purchasing 196
Notes and References 199
8 Transformative Marketing with Robotics 211
Overview 211
Origin, Definition, and Classifications of Robotics 212
Origin 212
Definition 213
 Contents xxi

Classification of Robots 214

Industrial and Business Applications 216
Domestic-Oriented Technology 219
Humanoid Robots 221
Robotics in the Marketing 5.0 World 222
Data-Driven Marketing Using Robotics 223
Predictive Marketing Using Robotics 224
Contextual Marketing Using Robotics 224
Augmented Marketing Using Robotics 225
Agile Marketing Using Robotics 226
Current Robotics Applications in Marketing 227
Understanding Customer Needs to Deploy Robotics 227
Revisiting Firm Capabilities to Integrate Robotics 228
Designing Marketing Mix Strategies with Robotics 229
Driving Customer Engagement Through Robotics 232
Designing Digital Strategies with Robotics 233
Future of Robotics in Marketing 234
Robotics and the Interactive Service Industry 235
Interactive Marketing 236
Creative Content Curation 238
Notes and References 241
9 Transformative Marketing Using Drones 255
Overview 255
Origin, Definition, and Classification of Drones 256
Origin 256
Definition 257
Classification of Drones 257
Military-Oriented Technology 262
Consumer Applications 263
Business Applications 265
Disaster Response 268
Drones in the Marketing 5.0 World 269
Data-Driven Marketing Using Drones 269
Predictive Marketing Using Drones 270
Contextual Marketing Using Drones 271
Augmented Marketing Using Drones 272
Agile Marketing Using Drones 273
Current Drone Applications in Marketing 274
Understanding Customer Needs to Deploy Drones 275
Revisiting Firm Capabilities to Integrate Drones 276
xxii Contents

Designing Marketing Mix Strategies With Drones 277

Driving Customer Engagement Through Drones 278
Designing Digital Strategies With Drones 280
Future of Drones in Marketing 281
The “Good,” “Bad,” and “Ugly” of Drones 282
Enhanced Customer Experience 283
Customer Contact Solutions 284
Notes and References 287
10 Transformative Marketing Using Blockchain 299
Overview 299
Origin, Definition, and Classification of Blockchain 300
Origin 300
Definition 302
Classification of Blockchain 304
Security-Oriented Technology 306
Link to AI and ML 308
AI/ML Improving Blockchain’s Effectiveness 309
Blockchain in the Marketing 5.0 World 310
Data-Driven Marketing Using Blockchain 310
Predictive Marketing Using Blockchain 311
Contextual Marketing Using Blockchain 312
Augmented Marketing Using Blockchain 314
Agile Marketing Using Blockchain 314
Current Blockchain Applications in Marketing 316
Understanding Customer Needs to Deploy Blockchain 316
Revisiting Firm Capabilities to Integrate Blockchain 317
Designing Marketing Mix Strategies with Blockchain 318
Driving Customer Engagement Through Blockchain 321
Designing Digital Strategies with Blockchain 322
The Future of Blockchain in Marketing 324
Data and Transaction Security 325
Impact on Advertising Transparency 325
Online Marketing Campaign Management 327
Notes and References 331
11 Putting It All Together 345
New-Age Technologies for Better Marketing: A Strategic
Framework 346
New-Age Technologies 346
Generation of Firm Capabilities 351
 Contents xxiii

Strategic and Tactical Marketing Actions 353

Customer Experience 354
Stakeholder Engagement/Benefits 355
Value and Social Well-being in a New-Age Technology World 359
Notes and References 360

Index 365
 List of Figures

Fig. 2.1 The Marketing 5.0 concept 21

Fig. 3.1 Role of AI in personalized engagement marketing 50
Fig. 3.2 Popular and emerging applications of AI 51
Fig. 4.1 Amazon’s customer review highlights feature developed
by GAI 81
Fig. 5.1 Data mining process for marketing purposes 106
Fig. 11.1 NATs for transformative marketing: A strategic framework 347

Image 3.1 Smart locks for homes. A smart lock device used for home
protection 34
Image 3.2 Wearable devices. A smartwatch is a wearable device
that provides several features such as local weather,
to-do lists, appointments, personal communications,
personal health-related information, and much more 37
Image 5.1 Shopify. Shopify facilitates businesses through its
machine-learning capabilities 109
Image 5.2 Ride-sharing Applications. Ride-sharing apps such
as Uber and Lyft use a combination of AI and ML
to provide the most relevant route results 111
Image 5.3 Video and Music Editing Software. Video and music
editing software work in tandem with humans to create
content that can be personalized and highly engaging 129

xxv
xxvi List of Figures

Image 5.4 Machine Learning-powered Warehousing Solutions.

Machine learning solutions deployed at warehouses aid
in demand fulfillment, warehouse automation, and route
optimization for maximum efficiency 130
Image 5.5 Chatbots and intelligent agents. Chatbots and intelligent
agents use ML capabilities to assist customers in making
informed choices 131
Image 6.1 Fortnite. A person playing Fortnite on a mobile device 143
Image 6.2 Pokémon Go. A person playing Pokémon Go on a mobile
device 143
Image 6.3 Product design using Metaverse. Product design
and ergonomic features can be configured on the metaverse 155
Image 6.4 Metaverse in public spaces. Metaverse can be used
in public spaces such as museums to blend physical
and virtual worlds 158
Image 7.1 Wearable. Personal wearables such as the Apple Watch
can perform and monitor a wide range of actions 177
Image 7.2 Smart Homes. Consumers can connect and control their
devices via Google Home 178
Image 7.3 Smart Thermostats. Smart home energy management
systems such as Nest can automatically regulate room
temperature based on learning energy usage patterns
over time 191
Image 7.4 IoT Warning Applications. IoT applications for smart
cities such as this one, LOCUS, provide a direct
connection between the citizens and the information
system of the city in a visualized form 195
Image 7.5 Amazon Go store. An Amazon Go store that uses
a combination of machine vision, IoT sensors,
and a mobile app to facilitate contactless retail customer
transactions 197
Image 8.1 Robots in manufacturing. Robots in an automobile
manufacturing plant 217
Image 8.2 Service robots. Robots serving drinks at a bar 220
Image 8.3 Interactive robots. Robots can be used in interactive
settings in social spaces 237
Image 8.4 Robots in airports. A robot assisting passengers at Incheon
airport, South Korea 238
Image 8.5 Collaborative robots in manufacturing. Collaborative
robots are used alongside humans in an industrial setting 239
Image 9.1 Fixed-wing drone 259
Image 9.2 Multirotor drone 259
Image 9.3 Drones used in Aerial Photography 264
Image 9.4 Drone Racing. First-person view drone racing 265
 List of Figures xxvii

Image 9.5 Drones used in spraying farms 267

Image 9.6 Drones used in construction 268
Image 9.7 Drones used in apple-picking 274
Image 10.1 Bitcoin. Bitcoins are used widely as a reliable means
of digital currency 301
Image 10.2 Tracking food origin using blockchain. Nestlé allows users
to trace the coffee origins of their Zoégas coffee brand
through blockchain-recorded data 315
Image 10.3 Blockchain for advertising effectiveness. Blockchain
is used to improve efficiencies in ad buying and ad
development 327
Image 10.4 Blockchain for managing influencer marketing.
Blockchain can be used to manage influencer marketing
programs efficiently 329
 List of Tables

Table 1.1 Understanding new-age technologies for transformative

marketing 5
Table 3.1 AI adoption worldwide 2022, by industry and function 30
Table 3.2 Selected companies in the AI ecosystem 31
Table 4.1 Representation of how GAI is used by industry worldwide 66
Table 4.2 Definition of Generative AI offered by various organizations 69
Table 4.3 Classification of GAI 70
Table 4.4 Types of GAI models 71
Table 4.5 A comparison of the popular GAI models—ChatGPT,
DALL-E, & Bard 73
Table 4.6 Top 10 professions that show the most automation
potential for GAI 80
Table 6.1 Types of metaverses 146
Table 8.1 Select definition of robotics 214
Table 8.2 Select conceptualization of robots 214
Table 8.3 Classification of robots 215
Table 8.4 Select conceptualization of social robots 221
Table 9.1 Similar terms relating to drones 258
Table 9.2 Changing nature of user demographics in the United States 281
Table 10.1 Select conceptualizations of Blockchain 302
Table 10.2 Classification of Blockchain 305

xxix
 1
Transformative Marketing Has Begun

Introduction
Avant-garde. This is a term that can be used to describe the current state of
business and marketing. In the vast canvas of human history, there have been
pivotal moments that have redefined the way we live, work, and connect.
Today, we find ourselves at the cusp of such a transformative era, where
the convergence of new-age technologies is reshaping the world as we know
it. The rapid and relentless march of innovation, fueled by advances in
technology has ushered in a new chapter in the human story.
Essentially, everything we know, have, and see today is different from what
it was a decade ago. There may have been signs of technology penetrating our
daily lives in popular culture, but the rate at which it is taking place is both
scary and exciting. As with many things, marketing has also adapted to these
technological advancements. Originally, marketing was product-driven (1.0),
which then evolved to be customer-oriented (2.0), and then human-centric
(3.0). These phases have taken seven decades to come into place.
In this era of unprecedented change, traditional boundaries are dissolving,
and established norms are being upended. The impact of these technologies
reaches into every corner of our lives, from the way we communicate and
access information to the way we address global challenges, including climate
change and healthcare. Just as we currently reflect on past transformative
periods, such as the Industrial Revolution or the rise of the Internet, future
marketing experts will undoubtedly look back on this era as a pivotal moment
in history. The impact of these technological advancements on marketing

© The Author(s), under exclusive license to Springer Nature 1

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_1
2 V. Kumar and P. Kotler

strategies, consumer behavior, and the overall business landscape will be

analyzed and studied for years to come.
In this regard, while many thought that Marketing 3.0 (human-centric
marketing) would be the last of the evolution; a new set of values and
principles of Generation Y and Z have ushered in marketing with new
frameworks to serve customers in the hybrid customer journeys. Thus,
emerged Marketing 4.0, which discusses the use of technologies, digital
media, and channels. Undoubtedly, technology’s role in marketing extends
beyond that—thus paving the carpet for Marketing 5.0.1 Companies are
unleashing technologies into their strategies, tactics, and operations, while
also leveraging them for the good of humanity. In this phase, the human-
centricity of marketing and technological empowerment are integrated, with
the core intention of using new-age technologies to emulate the capabilities
of human marketers.
At the heart of this transformation lies the exponential growth of data,
which has become the lifeblood of innovation and progress. Our digital
footprints, from the websites we visit to the products we purchase, are
now meticulously analyzed by algorithms to understand our behaviors and
preferences. These insights are then leveraged to create personalized experi-
ences, from curated content recommendations to tailored personal solutions.
Further, the rise of social media platforms, search engines, and e-commerce
has fundamentally changed the way businesses reach and interact with their
target audience. Traditional marketing channels, such as print advertise-
ments or television commercials, are being supplemented, and in some
cases replaced, by digital advertising methods that offer greater precision,
personalization, and measurability.
Furthermore, the way we interact with our environment is evolving. Smart
cities are emerging, harnessing the power of the IoT to enhance urban
living, from intelligent transportation systems that reduce traffic congestion
to energy-efficient buildings that reduce our carbon footprint. Recognizing
the impact of new-age technologies on human lives and the environment,
many organizations now track the performance of cities in their efforts to use
technology to improve human lives.2
Moreover, the proliferation of smartphones and other mobile devices has
further accelerated this shift towards digital marketing. Consumers now have
constant access to the internet and are increasingly relying on their mobile
devices to research products, compare prices, and make purchases. As a result,
businesses must adapt their marketing strategies to effectively engage with
consumers on these platforms, ensuring their brand message is accessible and
compelling across various devices and channels.
 1 Transformative Marketing Has Begun 3

In addition to digital marketing, emerging technologies such as artificial

intelligence (AI), virtual reality (VR), and augmented reality (AR) are poised
to have a profound impact on the marketing landscape. AI-powered chat-
bots and virtual assistants are already being used to enhance customer service
and provide personalized recommendations. VR and AR technologies enable
immersive brand experiences, allowing consumers to visualize products in
their environment before purchasing.
Furthermore, the increasing emphasis on data-driven marketing is trans-
forming the way businesses understand and target their audience. The
vast amount of data generated by consumers’ online activities, combined
with advanced analytics tools, allows marketers to gain valuable insights
into consumer preferences, behaviors, and purchasing patterns. This data-
driven approach enables businesses to deliver highly targeted and personal-
ized marketing campaigns, resulting in improved customer engagement and
higher conversion rates.
Yet, as we stand on the edge of this brave new world, we must also grapple
with profound questions about the ethical and societal implications of these
advancements. Issues of data privacy, algorithmic bias, and the potential for
job displacement loom large, calling for careful consideration and responsible
regulation.
Here, new-age technologies (NATs) are expanding known marketing
boundaries. It is the leveraging of these innovative, new-age technologies
as we understand them when viewed through the lens of marketing that
will both inform and redefine our approach to customers for many years
to come.3 Particularly, NATs such as artificial intelligence (AI), generative
AI, metaverse, robots, machine learning (ML), drones, Internet of Things
(IoT), and blockchain are just the beginnings of an infrastructure whereby
marketing is both experiential and instantaneous, a constant loop that
marketers will be able to tap into to shift perceptions, provide goods and
services and satisfy consumers.
Academic research has defined transformative marketing as, “…the conflu-
ence of a firm’s marketing activities, concepts, metrics, strategies, and
programs that are in response to marketplace changes and future trends
to leapfrog customers with superior value offerings over competition in
exchange for profits for the firm and benefits to all stakeholders.”4 Consid-
ering the confluence of new-age technologies in the marketing function,
we define transformative marketing in this context as, the usage of new-age
technologies and human insights to revolutionize how businesses and customers
interact to create more personalized and immersive experiences to engage
customers with superior value offerings over competition in exchange for profits
for the firm and benefits to all stakeholders.
4 V. Kumar and P. Kotler

How did we get here? What is the potential for new-age technologies
in marketing? What strategies, capabilities, and resources can we explore to
prepare? By examining the attributes of these eight key technologies, their
larger impact on marketing management, and taking a closer look into coun-
tries currently making advancements, we can better understand how new
marketing advancements in a digital world emerge.

A Brief Overview of NATs

As mentioned earlier, this book deals with eight rapidly emerging NATs. To
better understand these technologies and what they offer to firms and users,
a brief overview of these technologies is warranted. Table 1.1 presents a brief
overview of these technologies.
As listed in Table 1.1, each of the eight NATs denotes specific contexts,
serving tangible needs for firms and users through various marketing applica-
tions. A brief discussion of the NATs that can serve as a good starting point
to illustrate their potential for marketing applications is presented here.
Artificial intelligence. AI operates in the domain of continuous learning
and automation, acting as the intelligence that drives data-based analytics and
enables automated decision-making. AI uses technologies like deep learning
and natural language processing, to train machines to accomplish specific
tasks by processing large amounts of data and recognizing patterns in the
data. AI can analyze complex data to identify behavioral patterns and insights.
This ability prepares a firm to implement AI solutions to learn from expe-
rience. As a result, AI can aid firms in making transformative decisions,
with minimum error, and automatically trigger responses based on prior
experiences.
Generative AI . Generative AI refers to a category of artificial intelli-
gence (AI) algorithms that generate new outputs based on the data they
have been trained on.13 This data can take many forms, including text,
images, music, and even entire virtual worlds. The goal of generative AI is
to create machines that can not only replicate human creativity but, in some
instances, also surpass it, producing content that is both novel and high-
quality. One of the key techniques used in generative AI is deep learning,
a type of machine learning that involves training neural networks on large
datasets. These networks can then be used to generate new content by
sampling from the learned distribution. Other techniques used in genera-
tive AI include reinforcement learning, evolutionary algorithms, and Bayesian
networks. Generative AI has the potential to transform the way businesses
Table 1.1 Understanding new-age technologies for transformative marketing
AI Generative AI Machine Learning Metaverse

Definition • A system’s ability to • A category of artificial • Computational methods using • A fully immersive, hyper
interpret external data intelligence (AI) algorithms experience to improve spatiotemporal, and
correctly, to learn from such that generate new outputs performance or to make self-sustaining virtual
data, and to use those based on the data they have accurate predictions.7 shared space blending the
learnings to achieve specific been trained on.6 ternary physical, human,
goals and tasks through and digital worlds.8
flexible adaptation.5
Fields of origin • Philosophy • Philosophy • Mathematics • Computer Science
• Cognitive Science • Cognitive Science • Computational Statistics • Virtual Reality
• Computer Science • Computer Science • Computer Science • Augmented Reality
• Sensors
Popular marketing uses • Digital Marketing • Email Marketing • Digital Marketing • E-commerce
• Content Marketing • Digital Marketing • Content Marketing • Test marketing
• Interactive Marketing • Social Media Marketing • Content Marketing
• Predictive Analytics • Digital Marketing
Types of data used • Text • Text • Numerical data • Structured, semi-structured,
• Audio • Audio • Categorical data or wholly unstructured
• Video • Video • Time series data
• Images • Text
• Code
Types of human/technology • Direct/Visual • Direct/Visual • Mobile • Mobile
interaction • Mobile • Mobile • Web-based • Web-based
• Web-based • Web-based • AR/VR headsets
Key end user benefits • Continuous learning • Personalized results • Automation of learning • Entertainment
• Automation of non-routine • Solution to complex inquiries • Decision-making support • Interactivity
tasks • Humanlike conversations • Easier to try out new
• Decision support aid offerings
• Personalization
Key user challenges • Requires a specialist level of • Inaccurate results • Understanding potential • Privacy/ Data concerns
understanding • Potential intellectual property benefits • Early stages of
• Importance of trust in results violations • Managing user expectations technological know-how
of the results • Relatively higher cost of
usage
1 Transformative Marketing Has Begun

(continued)
5
 6

Table 1.1 (continued)

AI Generative AI Machine Learning Metaverse

Key firm benefits • Customer strategy • Saving time and resources • Pattern recognition • Virtual work environment
development • Delivering superior customer • Data management and collaboration
• Omnichannel marketing experience • Integration with traditional • Expanded learning spaces
• Marketing intelligence • Enhancing user engagement job roles • E-commerce opportunities
capabilities • Create personalized offerings • Social media proficiency
Key firm challenges • Employee training • Bias and accuracy issues • Security concerns, especially • Higher level of initial
• Compliance with government • Ethical and legal uncertainties with sensitive data investment to set up the
regulations • Integration with existing • Infrastructure for testing, infrastructure
• Identifying and using infrastructure implementing, and managing • Limited clarity on the
relevant knowledge to drive of large data regulatory and compliance
V. Kumar and P. Kotler

the development of AI • Financial and operational framework

solutions planning regarding talent • Potential misuse of data
management, data
management, and solutions
development
• Managing firm expectations
• User education efforts
Key reasons for the breadth/ • Growing acceptance among • Quick response time to • Rapidly evolving • Easy integration with other
depth of firm adoption users and marketers customers • Early focus remains on NATs
• Faster turnaround of • Real-time insights improving customer service, • Ability to create digital
data-driven decision-making • Scalable personalized with more promising areas of twins
• Elimination of human errors marketing use in the future • Enhance operational
• Access to high-quality data • Emphasis on efficient performance
problem-solving
 AI Generative AI Machine Learning Metaverse
Nature of privacy concerns/ • Collection and retention of • Exposing private or • Data-driven spear-phishing • Potential misuse of data,
origin of concerns personal data proprietary information to • Data poisoning especially that of minors
• Understanding the the public • High degree of intrusion
implications of using users’ • Ambiguities over the into private lives
digital footprint to develop ownership of the generated • Misapplication and
solutions content applicability of current
• Balancing inference • Potential employee misuse privacy regulations (e.g.,
generation and maintaining GDPR)
anonymity • Issues concerning data
• Dealing with personally rights and ownership
identifiable information and
quasi-identifiers

(continued)
1 Transformative Marketing Has Begun
7
 8

Table 1.1 (continued)

IoT Robots Drones Blockchain

Definition • A system of uniquely • Mechanical machines or • Any aerial vehicle that does • A distributed database
identifiable objects (things) intangible computer not rely on an onboard human solution that maintains a
and virtual addressability programs that perform operator for flight, either continuously growing list
that would create an rule-based work and tend to autonomously or remotely of data records that are
Internet-like structure for be configurable with basic operated.11 confirmed by the nodes
remote locating, sensing, features like authentication, participating in it.12
operating, and/or actuating security, auditing, logging,
of entities.9 and exception handling.10
Fields of origin • Computer Science • Philosophy • Mathematics • Computer Science
• Industrial Engineering • Physics
V. Kumar and P. Kotler

• Mechanics • Engineering
• Computer Science • Military defense
• Computer Science
Popular marketing uses • Digital Marketing • Interactive Marketing • Direct Marketing • Digital Marketing
• Content Marketing • Content Marketing • Digital Marketing • Interactive marketing
• Interactive Marketing • Digital (when combined with • Visual Marketing • Content marketing
AI) • Creative Marketing
• Content Marketing
Types of data used • Combination of apps, • Programming languages • Sensor data (Speed/Distance, • Inter-node communications
wearables, sensors, devices, • Mechanics Infrared/ Thermal) • Text
web, media, and location • Images • Audio/video
• Chemical • Numerical
Types of human/technology • Mobile • Direct/Visual: person-robot • Direct/Visual: person-drone • Mobile
interaction • Web-based • Web-based
Key end user benefits • Enhanced functionality • Task execution • Last mile solutions • Expedited processing of
• Device integration • Efficiency • Connectivity actions
• Real-time connectivity • Quicker and consistent • Monitoring • Secure transfer of data and
responses • Security value
Key user challenges • Establishing trust • Human-robot interaction/ • Privacy • Unstandardized
• Privacy/ Data concerns communication can be tricky • Legalities implementation
• Security of multiple devices at times • Navigating no-fly zones • Potential liability and legal
• Adjusting to an • Less accountability for • Accounting for physical issues, and their recourse
environment of integrated problems that arise damages to assets
devices • Ethical issues
 IoT Robots Drones Blockchain
Key firm benefits • Better sensing, tracking, • Superior efficiency • Content creation • Transparency in business
and monitoring capabilities • Precision • Data collection and integration operations
• Security of assets • Enhanced work capacity • Delivery solutions • Faster processing of
• Single point of data • Faster adaptability to • Use in media uses for business operations
collection from integrating procedural changes marketing campaigns • Better tracking of business
multiple assets • Tolerance of severe and processes
• Enables easier hazardous environments
communication between
multiple assets
Key firm challenges • Integration of multiple • Understanding mobility and • Operational concerns • Estimating and managing
business functions dexterity needs • Privacy management the volume and speed of
responsible for developing, • Integration with the • Compliance with regulatory transaction traffic to
implementing, and development agenda of framework develop and implement
maintaining IoT solutions solutions • Managing damages while in Blockchain solutions
• Data protection • Clarity on when and where operation • Understanding liability and
• Efforts towards determining to use robots legal issues
security vulnerabilities • Compliance with government
within devices or networks regulations
• Compliance with IoT
regulations
Key reasons for the breadth/ • Rapidly gaining traction • Still in the exploratory stages • A new and promising way to • Formative stages of
depth of firm adoption among users and firms, of development reach consumers development
owing to a wide range of • Wide range of business and • Provides ample scope for • Early adopting firms are
applications customer-facing applications marketing and promotion exploring uses and
• Increased collaborations • Future potential remains activities boundaries regarding
between technology varied • Useful in data collection and potential uses and
companies enable the targeting activities, especially implementation
development of many IoT when paired with IoT, virtual
applications reality, augmented reality, and
cloud services
Nature of privacy concerns/ • Data or Network based • Privacy concerns center • Safety & surveillance concerns • Data (private vs. public)
origin of concerns hacking concerns around movement and • Detecting and recording • Jurisdiction concerns, HIPPA
surveillance without explicit permission. concerns, Federal and State
• Staying informed of the Law concerns, GDPR
1 Transformative Marketing Has Begun

distinction and classification of • Threats from new-age

public and private spaces hackers and hacking
techniques

Source Adapted and extended from Kumar, V. (2021). Intelligent marketing: Employing new age technologies. Sage Publications
9
10 V. Kumar and P. Kotler

approach marketing and customer service. From product design to personal-

ization, and nurturing customer relationships to delivering superior customer
experiences, this technology has the potential to transform the way businesses
operate and interact with their customers.
Machine Learning . Machine learning refers to computational methods
that use experience to improve performance or to make accurate predic-
tions.14 By considering past information (i.e., referred to as experience),
machines gain the ability to learn while they perform, thereby showing
performance improvement. Therefore, the quality of learning is dependent on
the volume and quality of data; and the key outcome is predictions about key
variables of interest. Simply put, ML is a subset of AI that trains a machine
to learn. Thus, through ML, firms can develop algorithms that enable them
to predict future behaviors and trends based on prior data and patterns in
behaviors.
Metaverse. Metaverse refers to a fully immersive, hyper spatiotemporal,
and self-sustaining virtual shared space blending the ternary physical, human,
and digital worlds.15 It can also be visualized as a virtual reality space where
users can interact with a computer-generated environment and other users in
real-time. It is a collective virtual shared space that encompasses the physical
world and various virtual worlds, allowing users to engage in a wide range of
activities, such as socializing, gaming, and conducting business. Metaverse is
characterized by its immersive nature and interconnectedness. In this regard,
the metaverse has the potential to revolutionize the way we work, learn, and
entertain ourselves. In the business world, the metaverse holds important
implications for productivity, content creation, and delivering experiences.
Overall, the metaverse has the potential to reshape various aspects of our lives
and open new possibilities for human interaction and creativity.
Internet of Things. The International Telecommunication Union (ITU)
defines IoT as “a global infrastructure for the information society, enabling
advanced services by interconnecting (physical and virtual) things based
on existing and evolving interoperable information and communication
technologies.”16 IoT is designed on a network of sensors that capture infor-
mation about each device and are individually identifiable. IoT devices can
sense, compute, and communicate wirelessly over short distances, and can
interconnect to form a wireless sensor network. By interconnecting things,
harvesting information from the environment, and interacting with the
physical world through the Internet, IoT can provide services for informa-
tion transfer, analytics, applications, and communications.17 IoT devices can
sense, compute, and communicate wirelessly over short distances, and can
interconnect to form a wireless sensor network.
 1 Transformative Marketing Has Begun 11

Robots. Robots are mechanical machines, systems, or programs that “per-

form rule-based work, and tend to be configurable with basic features
like authentication, security, auditing, logging, and exception handling”.18
Robots made their first appearance in the industrial space in the 1970s by
assisting in production activities. Recently, service robots (i.e., robots that
are used for service applications) aid firms in performing a wide array of
customer-oriented tasks. Intelligent robots, a specialized class of service robots
(e.g., robotic waiters, robotic home cleaners), refer to “technology that can
perform physical tasks, operate autonomously without needing instruction,
and are directed by computers without help from people.”19 With intelli-
gent robots, efficiency can be achieved using some human participation, or
achieved totally by machines.
Drones. A drone refers to any aerial vehicle that does not rely on an
onboard human operator for flight, either autonomously or remotely oper-
ated.20 Drones and drone technology have significantly benefitted from the
open-source developer market. The drone manufacturers have harnessed the
passion and expertise of the open-source community by bringing together
geographically distributed user communities. Such an initiative continues to
pay rich dividends by developing solutions that serve specific use cases. In this
regard, drones are used in a wide range of commercial applications such as
surveillance, inspection, logistics, film production, and rescue efforts, among
others.
Blockchain. Blockchain is a distributed database that allows for the perma-
nent, immutable, and transparent recording of data and transactions.21
The decentralized storage of records ensures that no single point of weak-
ness exists, thereby lowering the likelihood of hacking and data breaches.22
By specifying the conditions under which a transaction may be executed,
a blockchain allows two or more parties to complete their transactions
efficiently and more quickly, with greater security of data and assets.

Looking Beyond the Digital Frontier of NATs

Digitalization in marketing has revolutionized the way businesses interact
with their customers. Social media marketing has enabled businesses to reach
a wider audience and engage with them in real time. E-commerce has made
it easier for customers to purchase products and services from the comfort
of their homes. These advancements have made marketing more efficient,
cost-effective, and personalized. One of the key benefits of digitalization in
marketing is the ability to track customer behavior and preferences. With
12 V. Kumar and P. Kotler

the help of analytics tools, businesses can gather data on customer interac-
tions with their brand, including website visits, social media engagement,
and purchase history. This data can be used to create targeted marketing
campaigns that are tailored to the specific needs and interests of each
customer.
Another benefit of digitalization in marketing is the ability to automate
certain tasks. For example, businesses can use chatbots to provide customer
support and answer frequently asked questions. This not only saves time and
resources but also improves the customer experience by providing instant
responses. Digitalization in marketing also allows businesses to create more
engaging and interactive content. For example, augmented reality and virtual
reality technologies can be used to create immersive experiences that allow
customers to interact with products in a virtual environment. This can help
businesses to showcase their products more engagingly and memorably.
The NATs individually and collectively are ushering in a business
scenario that is markedly different from conventional practices.23 Specifi-
cally, marketing activities and business tasks have seen the incorporation of
NATs as individual implementations. More recently, firms are beginning to
see the merits of an integrated implementation of NATs wherein multiple
technologies are used in a specific area of operation. Further, an added focus
on data-driven business and marketing strategies has allowed firms to harness
the power of NATs in their firm-wide operations, particularly in marketing.
The potential of NATs in integrating multiple sources of data and mining this
data using sophisticated techniques geared towards the generation of insights
has encouraged firms to view NATs in a new way.
Today, new-age technology is making its presence known in the marketing
environment, right up to our doorsteps. Amazon, for instance, uses a conflu-
ence of AI, robots, ML, drones, IoT, and blockchain to offer, deliver,
and develop solutions that are already changing the business landscape. A
far cry from the humble homepage set up in 1995, Amazon has truly
embraced an ever-evolving digital ecosystem. AI engages the moment you
interact with the Amazon app, website, or Alexa-enabled device, robots zing
through warehouses to identify and retrieve products, ML fuels a flurry of
recommendations based on individuals’ shopping and browsing behaviors,
and drones stand ready to deliver PrimeAir packages (pending regulatory
support). Amazon Web Services (AWS) offers AWS IoT, which presents a
wide range of solutions to integrate devices and data collection for indus-
trial, consumer, and commercial applications. Advances are being made into
blockchain with Amazon Managed Blockchain providing a means to create
and manage a scalable blockchain network using open-source frameworks,
 1 Transformative Marketing Has Begun 13

and the added ability to perform necessary analyses. This is but one example
to note, how each technology in its own right—AI, robots, ML, drones,
IoT, and blockchain—will continue to foster firm capabilities to address the
ever-growing information pool.
The NATs form the foundation on which companies design their digital-
ization journey. For instance, AI enables marketers to forecast the outcomes
of marketing campaigns, analyze past data to identify patterns and suggest
optimized designs for future campaigns. This empowers marketers to be
aware of potential market failures and navigate through them. Similarly,
IoT empowers businesses to incorporate contextual touchpoints into phys-
ical locations, creating a seamless omnichannel experience. It also allows
marketers to offer personalized experiences to their customers. Augmented
and virtual realities assist companies in delivering captivating products with
minimal human intervention.
Therefore, it is no wonder that marketers throw around these new
technology buzzwords as they flock to capitalize on each of the above-
mentioned NATs, adapting to the observable impacts taking place currently
in the marketing arena and which will continue, no doubt, for decades to
come. Overall, technology will drive marketing to be data-driven, predic-
tive, contextual, augmented, and agile. The Marketing 5.0 concept revolves
around three interconnected applications—predictive marketing, contextual
marketing, and augmented marketing. These applications are built upon
two organizational disciplines—data-driven marketing and agile marketing.
Chapter 2 will discuss how these marketing applications contribute to
enhancing human lives.

Organization of the Book

This book will adopt a humanistic applications perspective, based on the
Marketing 5.0 concept, with specific reference to the marketing discipline
regarding NATs. Particularly, the following eight NATs are covered in this
book—AI, Generative AI, ML, Metaverse, IoT, Robotics, Drones, and
Blockchain—with eight chapters devoted to each of the eight NATs. The
eight NAT chapters are bookended by introductory and concluding chapters.
All eight chapters on the NATs follow a similar four-part narrative struc-
ture that focuses on key areas of these technologies. The choice of keeping a
similar narrative structure is in recognition of the interconnectivity and relat-
edness of these technologies, and how they often work in tandem in many
organizations for the betterment of human lives.
14 V. Kumar and P. Kotler

The introduction chapter (this chapter) opens with a discussion about the
Marketing 5.0 concept and how it can be viewed from the NATs perspec-
tive. Here, the eight NATs covered in this book are introduced. Further, this
chapter sets up the case to look beyond the NATs as just technologies and
view them as being critical in the digitization process of companies and in
enriching human lives.
In Chapter 2, the case is made for how NATs can be used by companies
in not only enhancing customer journeys but also improving human lives
by making meaningful connections. This is done through the Marketing 5.0
concept that integrates several key marketing concepts relating to technology
and humans. Subsequently, Chapters 3–10 are dedicated to each of the NATs.
Each NAT chapter (Chapters 3–10) begins with a discussion on the
foundations of these technologies—i.e., origin(s), definition, and compo-
nents. While the discussion of the foundations can be technical, it is kept
to a minimum so that readers can follow the marketing discipline-specific
discussion that subsequently follows.
In the second part of the NAT chapters, the components of Marketing
5.0 (i.e., data-driven marketing, predictive marketing, contextual marketing,
augmented marketing, and agile marketing) are discussed concerning the
NAT covered in that chapter. This approach would allow readers to see how
each of the NATs works towards enhancing value across the customer journey
while devoting attention to creating a better living for humanity.
In the third part of the chapters, the five components of Marketing 5.0
are dwelled upon in detail. Here, the five components are envisaged from
a customer experience and customer engagement perspective as follows: (a)
understanding customer needs to deploy the NAT, (b) revisiting firm capabil-
ities to integrate the NAT, (c) designing the marketing mix strategies with the
NAT, (d) driving customer engagement through the NAT, and (e) designing
digital strategies with the NAT. In doing so, the discussion is firmly centered
around how the resources, capabilities, and strategies that the NATs present
and sustain can be used to improve human living. By drawing upon market-
place examples, trends, and business practices, this section of the chapters
presents the marketing applications of NATs as it currently stands.
In the final part of the chapters, the future of these technologies is
discussed, along with early indications of how these technologies are likely
to progress. It presents a range of upcoming developments that can signify
future business practices and marketing uses of the NATs.
Subsequently, the concluding chapter (Chapter 11) presents largely organi-
zational issues driving and challenging the implementation and development
 1 Transformative Marketing Has Begun 15

of NATs, and the Marketing 5.0 concept. Further, a discussion on the next
developments in the world of NATs is presented and discussed.

Key Terms and Related Conceptualizations

Artificial intelligence A new-age technology that uses deep learning and
natural language processing to train machines to
accomplish specific tasks by processing large amounts
of data and recognizing patterns in the data.
Blockchain A distributed database that allows for the permanent,
immutable, and transparent recording of data and
transactions.
Drones Aerial vehicles that do not rely on an onboard human
operator for flight, either autonomously or remotely
operated.
Generative artificial intelligence A category of artificial intelligence (AI) algorithms that
generate new outputs based on the data they have
been trained on.
Internet of Things A global infrastructure for the information society,
enabling advanced services by interconnecting (physical
and virtual) things based on existing and evolving
interoperable information and communication
technologies.
Machine learning A subset of AI that trains a machine to learn.
Metaverse A collective virtual shared space that encompasses the
physical world and various virtual worlds and allows
users to engage in a wide range of activities.
Robots Mechanical machines, systems, or programs that perform
rule-based work, and tend to be configurable with
basic features like authentication, security, auditing,
logging, and exception handling.
Transformative marketing The usage of new-age technologies and human insights
to revolutionize how businesses and customers interact
to create more personalized and immersive experiences
to engage customers with superior value offerings over
competition in exchange for profits for the firm and
benefits to all stakeholders

Notes and References

1. Kotler, P., H. Kartajaya, & . Setiawan (2021). Marketing 5.0: Tech-
nology for humanity. John Wiley & Sons.
2. The Smart City Index created by IMD in 2019 adopts a balanced
focus on the economic and technological aspects of global smart
cities on the one hand, and the “humane dimensions” of the
global smart cities (quality of life, environment, inclusiveness) on the
other. According to the 2023 Smart City Index, the top five global
smart cities are Zurich, Oslo, Canberra, Copenhagen, and Lausanne,
respectively. [Source: “IMD Smart City Index 2023,” IMD, April,
accessed from https://www.imd.org/wp-content/uploads/2023/04/sma
rtcityindex-2023-v7.pdf.]
16 V. Kumar and P. Kotler

3. Kumar, V. (2021). Intelligent marketing: Employing new age technologies.

Sage Publications.
4. Kumar, V. (2018). “Transformative marketing: The next 20 years,”
Journal of Marketing, 82(4), 1–12.
5. Kaplan, A., & M. Haenlein (2019), “Siri, Siri, in my hand: Who’s
the fairest in the land? On the interpretations, illustrations, and
implications of artificial intelligence,” Business Horizons, 62(1), 15–25.
6. Routley, N. (2023), “What is generative AI? An AI explains,” World
Economic Forum, February 6, accessed from https://www.weforum.org/
agenda/2023/02/generative-ai-explain-algorithms-work/.
7. Mohri, M., A. Rostamizadeh, & A. Talwalkar (2018). Foundations of
machine learning. Cambridge, MA: MIT Press.
8. Wang, H., H. Ning, Y. Lin, W. Wang, S. Dhelim, F. Farha, J. Ding, &
M. Daneshmand (2023), “A survey on the metaverse: The state-of-
the-art, technologies, applications, and challenges,” IEEE Internet of
Things Journal , 10 (16), 14671–14688. https://doi.org/10.1109/JIOT.
2023.3278329.
9. Ng, I. C. L., & Y. L. W. Susan (2017), “The Internet-of-Things:
Review and research directions,” International Journal of Research in
Marketing, 34 (1), 3–21.
10. Wilson, H. J. (2015), “What is a robot, anyway?” Harvard Business
Review, April 15, available at https://hbr.org/2015/04/what-is-a-robot-
anyway.
11. Newcome, L. R. (2004), Unmanned aviation: A brief history of
unmanned aerial vehicles. American Institute of Aeronautics and Astro-
nautics.
12. Yli-Huumo, J., D. Ko, S. Choi, S. Park, & K. Smolander (2016),
“Where is current research on blockchain technology?—A systematic
review,” PloS One, 11(10), e0163477.
13. Routley, N. (2023), “What is generative AI? An AI explains,” World
Economic Forum, February 6, accessed from https://www.weforum.
org/agenda/2023/02/generative-ai-explain-algorithms-work/.
14. Mohri, M., A. Rostamizadeh, & A. Talwalkar (2018). Foundations of
machine learning. Cambridge, MA: MIT Press.
15. Wang, H., H. Ning, Y. Lin, W. Wang, S. Dhelim, F. Farha, J. Ding, &
M. Daneshmand (2023), “A survey on the metaverse: The state-of-
the-art, technologies, applications, and challenges,” IEEE Internet of
Things Journal , 10 (16), 14671–14688. https://doi.org/10.1109/JIOT.
2023.3278329.
 1 Transformative Marketing Has Begun 17

16. ITU (2012), “Overview of the Internet of things,” International

Telecommunication Union, June, accessed from http://handle.itu.int/
11.1002/1000/11559.
17. Gubbi, J., R. Buyya, S. Marusic, & M. Palaniswami (2013), “Internet
of Things (IoT): A vision, architectural elements, and future direc-
tions,” Future Generation Computer Systems, 29 (7), 1645–1660.
18. Wilson, H. J. (2015), “What Is a Robot, Anyway?” Harvard Business
Review, April 15, available at https://hbr.org/2015/04/what-is-a-robot-
anyway.
19. Colby, C. L., S. Mithas, & A. Parasuraman (2016) “Service robots:
How ready are consumers to adopt and what drives acceptance,” The
2016 Frontiers in Service Conference. Norway: Bergen.
20. Newcome, L. R. (2004), Unmanned aviation: A brief history of
unmanned aerial vehicles. American Institute of Aeronautics and Astro-
nautics.
21. McKinsey (2022). What is blockchain? McKinsey, December 5,
accessed from https://www.mckinsey.com/featured-insights/mckinsey-
explainers/what-is-blockchain#.
22. While new blocks of information can be appended to the existing
blockchain ledger, previous data cannot be overwritten or erased,
thereby creating a permanent, verifiable, and traceable trail of trans-
actions (Giordani 2018).
23. Kumar, V. (2021). Intelligent marketing: Employing new age technologies.
Sage Publications.
 2
Transformative Marketing: A Marketing 5.0
Perspective

Introduction
Transformative marketing aims to leverage the potential of cutting-edge NATs
to revolutionize the way businesses connect with their target audience. By
harnessing the capabilities of new-age technologies, companies can create
innovative and impactful marketing campaigns that drive significant results.
These technologies encompass a wide range of tools and platforms, including
AI, drones, metaverse, robotics, and other NATs introduced in Chapter 1.
The term “transformative” suggests that these technologies have the potential
to significantly change the way marketing is conducted. These technologies
can revolutionize how businesses interact with their customers, allowing for
more personalized and immersive experiences.
One of the key aspects of transformative marketing is its ability to adapt
and evolve with the ever-changing digital landscape as it combines new-age
technologies and human insights. With the rapid advancements in tech-
nology, businesses need to stay ahead of the curve to remain competitive.
By embracing NATs, companies can stay relevant and effectively engage with
their customers in a dynamic and personalized manner. For instance, AI can
be used to analyze vast amounts of customer data, enabling businesses to gain
valuable insights into consumer behavior and preferences. This information
can then be utilized to create targeted marketing campaigns that resonate with
the target audience on a deeper level.
Moreover, transformative marketing using NATs enables businesses to
enhance customer experiences and build stronger brand loyalty. Virtual
reality and augmented reality, for example, can be utilized to create immersive

© The Author(s), under exclusive license to Springer Nature 19

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_2
20 V. Kumar and P. Kotler

and interactive experiences for customers. This can range from virtual show-
rooms that allow customers to explore products in a lifelike environment to
augmented reality apps that enable users to visualize how a product would
look in their own space. By providing such engaging experiences, businesses
can leave a lasting impression on customers and foster a sense of loyalty and
trust. Going by industry developments, transformative marketing appears to
be a game-changer for businesses looking to stay ahead in the digital era.

Meaningful Connections Using Human Insights

In their quest for market expansion, companies are focusing on develop-
ment (of themselves, and society), not just on growth. When a society moves
toward greater literacy and better incomes, the untapped segments become
new sources of growth. Further, brands are recognizing the need to develop
and nurture the markets they are competing in. With the advancements
due to the internet and technology, companies are under constant scrutiny
and their ethical aspects are being monitored. Adopting an inclusive and
sustainable marketing approach would help mitigate the problem. Utilizing
technologies to invest back into society accelerates progress and opens oppor-
tunities for everyone. This has opened a whole new realm of possibilities
for building relationships and fostering connections with people who share
similar interests or goals. Now, new-age technologies offer unique opportuni-
ties to foster meaningful human connections.1 While it may seem paradoxical
that technology, often accused of isolating people, can bring them closer
together, the potential lies in how these tools are harnessed.
In this regard, Marketing 5.0 has been presented as a concept that can
foster togetherness and connections for humanity. Here, Marketing 5.0 is
defined as “…the application of human-mimicking technologies to create,
communicate, deliver, and enhance value across the customer journey”
(p. 6).2 It has the potential to assist marketers in effectively tackling contem-
porary obstacles, including the generation gap, prosperity polarization, and
the digital divide. Through its implementation, marketers can successfully
generate, convey, distribute, and augment value throughout the customer
journey, all while maintaining a harmonious equilibrium between human
intellect and computer intelligence. The deployment of Marketing 5.0 calls
for the use of NATs (such as AI, generative AI, metaverse, robots, ML,
drones, IoT, and blockchain) that aim to emulate the capabilities of human
marketers. The Marketing 5.0 concept revolves around three intercon-
nected applications, namely predictive marketing, contextual marketing, and
 2 Transformative Marketing: A Marketing 5.0 Perspective 21

augmented marketing. These applications are further grounded in two funda-

mental organizational disciplines, namely data-driven marketing, and agile
marketing (p. 12).3 Figure 2.1 illustrates the Marketing 5.0 concept.
Accordingly, the two disciplines in the Marketing 5.0 concept can be
understood as follows. First, data-driven marketing involves the systematic
gathering and examination of extensive data obtained from both internal and
external sources. Additionally, it entails the establishment of a comprehensive
data ecosystem aimed at facilitating and enhancing marketing decision-
making processes. Second, agile marketing entails the utilization of decen-
tralized, cross-functional teams to swiftly conceptualize, design, develop, and
validate products and marketing campaigns. These two disciplines form the
foundation for the implementation of the Marketing 5.0 concept.
The three disciplines in the Marketing 5.0 concept are explained as follows.
First, predictive marketing refers to the systematic approach of constructing

Data-driven
Marketing

Predictive
Marketing

Contextual Augmented
Marketing Marketing

Agile
Marketing

Fig. 2.1 The Marketing 5.0 concept

(Source Kotler, P., Kartajaya, H., & Setiawan, I. (2021). Marketing 5.0: Technology for
humanity. John Wiley & Sons)
22 V. Kumar and P. Kotler

and employing predictive analytics, occasionally incorporating ML tech-

niques, to anticipate the outcomes of marketing endeavors before their
commencement. Second, contextual marketing refers to the process of recog-
nizing and characterizing customers and delivering tailored experiences using
sensors and digital interfaces in the physical environment. Finally, augmented
marketing refers to the utilization of digital technology to enhance the effi-
ciency of customer-facing marketers through the integration of humanlike
technologies, including chatbots and virtual assistants.
The adoption of Marketing 5.0 necessitates a data-driven approach,
which can be achieved through the establishment of a comprehensive
data ecosystem. This ecosystem enables marketers to engage in predictive
marketing, deliver personalized marketing messages, and create seamless
interfaces with customers using augmented marketing. However, to fully
leverage these execution elements, companies must also possess corporate
agility, allowing them to respond promptly to market changes. By embracing
these principles, companies can effectively implement Marketing 5.0 and
maximize their marketing efforts.
The NATs offer tremendous opportunities for society and bring value
through Marketing 5.0. It allows businesses to build platforms and ecosys-
tems that are capable of processing large-scale transactions without geograph-
ical and industry boundaries. This helps companies meet customers’ growing
expectations, increase their willingness to pay, and drive better value creation.
For instance, AI is being used in healthcare, thanks to its potential in
accelerating drug discovery and precision medicine. Health tracking devices
(wearables), connected with IoT are being used in preventive healthcare.
Additionally, digitalization is contributing to the sustainability initiatives of
global companies. Electric vehicles are picking up momentum, solar energy
trading is being practiced for energy conservation. To tackle the digital divide
and the issues with polarization, companies need to apply NATs in all aspects
of our lives—extending it to serve the larger good of society.

Convergence of NATs and Marketing

The age of technological transformation has begun. However, this was not
always the case. Despite technology’s vital role in driving marketing objectives
and firm outcomes, it was not considered a key component of the marketing
practice.4 Recent developments in marketing practices have embraced tech-
nology and firmly placed it at the center of business operations. Using
technology, firms are now able to interact with users through various touch
 2 Transformative Marketing: A Marketing 5.0 Perspective 23

points and often at several points in a day. Further, technology also enables
firms to facilitate and monitor interactions among users. Such technology-
focused actions allow firms to collect real-time data about users and their
needs. Subsequently, this knowledge can be used in developing personalized
offerings and implementing customer-centric marketing strategies that can
result in the creation of customer engagement with firms.
The origins of the NATs are entwined with long-established disciplines
(e.g., philosophy, mathematics, engineering, etc.) and of course with more
recent disciplines such as computer science. Understanding the origins and
evolution of NATs is therefore important given their ever-increasing presence
in our lives and, in turn, the rules of marketing. IoT and blockchain, by far
the youngest of the eight technologies, are considered to have grown because
of knowledge gleaned from computer science. Considering each technolog-
ical advancement respective to its historical context with society is important
to modern marketers as they represent platforms for customer engagement.
Knowledge of what technology to employ, how to employ it, and when and
why it should be employed across countries and cultures is critical. Also, it
stands to reason that once these platforms are effectively harnessed, the resul-
tant data generated will provide a continuous stream of feedback to marketers
with potential implications for developing solutions and firm growth strate-
gies. In other words, a clear understanding of how the eight NATs will help
firms develop strategies, build capabilities, and deploy resources is of utmost
need.

Understanding Resources, Capabilities,

and Strategies of NATs
The convergence of NATs and the marketing discipline can best be under-
stood via resources, capabilities, and strategies.5 Resources6 refer to some-
thing an organization can draw on to accomplish its goals and are conceptual-
ized as a firm’s physical, human, and organizational capital that enable a firm
to conceive and implement strategies that improve its efficiency and effec-
tiveness.7 Originally conceptualized as part of the resource-based view (RBV)
of the firm, resources are viewed as integral to the sustained competitive
advantage (SCA) of the firm.8 Research has provided the VRIO framework
(Value, Rarity, Imitability, and Organization) to understand the relationship
between a resource and sustainable competitive advantage. It has been iden-
tified that SCA only results when the resources are simultaneously valuable,
rare, imperfectly imitable, and exploitable by the firm’s organization.9
24 V. Kumar and P. Kotler

Capabilities are subsets of the firm’s resources and refer to “an organiza-
tionally embedded non-transferable firm-specific resource whose purpose is
to improve the productivity of the other resources possessed by the firm”
(p. 389).10,11 Capabilities can be static or dynamic. While static capabilities
denote “…well-honed and difficult-to-copy routines for carrying out estab-
lished processes” (p. 185)12 ; dynamic capabilities refer to “the capacity of
an organization to purposefully create, extend, or modify the resource base”
(p. 4).13 In essence, unlike static capabilities, dynamic capabilities enable the
firm to stay informed of marketplace developments and prepare the firm to
constantly update its approach of using resources to deliver value to all its
stakeholders.
Research has also identified advancements to the capabilities theory in
terms of the firm perspective. Specifically, the dynamic capabilities approach
adopts an inside-out view wherein the firm looks at the outside market
(i.e., external to the firm) and undertakes all necessary steps to prepare and
perform its stated objectives. Adaptive capabilities, in contrast, recognize
the need for an outside-in orientation (i.e., a perspective that begins with
the market and flows inward to the firm), and prepare the management
team to step outside the firm to understand customer needs (for strategy
development).14
Strategy refers to “…a firm’s theory of how it can gain superior perfor-
mance in the markets within which it operates” (p. 140).15 Further, strategy
is also seen as a plan, ploy, pattern, position, and perspective adopted by firms
in managing their business relationships16 that ultimately deliver value to
customers.17 Overall, strategy binds firms through collective perception and
action, rather than discrete steps aimed at solving specific issues. While from
a definition standpoint strategies, capabilities, and resources refer to discrete
firm-related concepts, the current NAT-driven environment has ushered in a
medium to integrate various technologies and how firms utilize them.
Any successful implementation of a NAT will need firms to unify
resources, capabilities, and strategies. Netflix is a faithful illustration of
this process in action in a firm using NATs. Netflix’s corporate strategy is
centered around people (i.e., employees, customers, etc.). Despite not having
a stated mission statement, we can find information on their firm strategy
from how they speak of their current corporate culture. Specifically, their
core philosophy is “people over process” and focuses on a list of values
such as judgment, communication, curiosity, passion, selflessness, innovation,
inclusion, integrity, and impact.18 Netflix’s capabilities include a well-built
technology infrastructure with strong data management and the ability to
source talent and content effectively.
 2 Transformative Marketing: A Marketing 5.0 Perspective 25

We can observe Netflix’s capabilities in action from a consumer standpoint

when users log into the Netflix app via internet-enabled devices (computers,
TVs, tablets), or using cellular data via mobile phones. Once logged in they
make selections based on their interests. The proprietary machine learning
algorithms get to work and soon curate the shows and previews specifically
for the user. A wealth of information is generated over time capturing not
only preferences but behaviors also. What they watch, when they watch, how
often they watch, and where and how they watch, are only some of the infor-
mation that is captured, in addition to a host of other user-specific details.
The information generated ties into Netflix’s firm resources and to those
tangible and intangible benefits. As a result, Netflix can procure more titles
their consumers are genuinely interested in saving both time and money, and
create targeted marketing campaigns to gain new users given what they learn
from current consumers. Understanding the implications of firm strategies,
resources, and capabilities is an integral part of utilizing new technologies for
marketing management potential. It certainly is a win-win for Netflix and its
subscribers.

Key Terms and Related Conceptualizations

Agile The utilization of decentralized, cross-functional teams to swiftly

marketing conceptualize, design, develop, and validate products and
marketing campaigns
Augmented The utilization of digital technology to enhance the efficiency of
marketing customer-facing marketers through the integration of humanlike
technologies, including chatbots and virtual assistants
Capabilities Subsets of the firm’s resources that belong to an organizationally
embedded non-transferable firm-specific resource whose purpose
is to improve the productivity of the other resources possessed
by the firm.
Contextual The process of recognizing and characterizing customers and
marketing delivering tailored experiences using sensors and digital
interfaces in the physical environment
Data-driven The systematic gathering and examination of extensive data
marketing obtained from both internal and external sources
Dynamic The capacity of an organization to purposefully create, extend, or
capabilities modify the resource base
Marketing The application of human-mimicking technologies to create,
5.0 communicate, deliver, and enhance value across the customer
journey
Predictive The systematic approach of constructing and employing predictive
marketing analytics, occasionally incorporating ML techniques, to anticipate
the outcomes of marketing endeavors before their
commencement.
(continued)
26 V. Kumar and P. Kotler

(continued)
Resources Something an organization can draw on to accomplish its goals
and is conceptualized as a firm’s physical, human, and
organizational capital that enables a firm to conceive and
implement strategies that improve its efficiency and effectiveness
Static Well-honed and difficult-to-copy routines for carrying out
capabilities established processes
Strategy A firm’s theory of how it can gain superior performance in the
markets within which it operates

Notes and References

1. Barney, J. (1991), “Firm resources and sustained competitive advan-
tage,” Journal of Management, 17 (1), 99–120.
2. Kotler, P., H. Kartajaya, & I. Setiawan (2021). Marketing 5.0: Tech-
nology for humanity. John Wiley & Sons (p. 6).
3. Kotler, P., H. Kartajaya, & I. Setiawan (2021). Marketing 5.0: Tech-
nology for humanity. John Wiley & Sons (p. 12).
4. Brady, M., M. Saren, & N. Tzokas (2002), “Integrating information
technology into marketing practice–the IT reality of contemporary
marketing practice,” Journal of Marketing Management, 18(5–6), 555–
577.
5. Kumar, V. (2021). Intelligent marketing: Employing new age technologies.
Sage Publications.
6. Barney and Arikan (2001). Define resources as the tangible and intan-
gible assets firms use to conceive of and implement their strategies
(p. 138).
7. Barney, J. (1991), “Firm resources and sustained competitive advan-
tage,” Journal of Management, 17 (1), 99–120; Wernerfelt, B. (1984),
“A resource-based view of the firm,” Strategic Management Journal ,
5 (2), 171–180.
8. The RBV proposes that if a firm possesses valuable resources that are
not normally possessed by other firms, and if other firms find it too
expensive or challenging to imitate the resources, the firm owning the
resources can create a sustainable competitive advantage (Barney and
Hesterly 2012).
9. Barney, J. & W. Hesterly (2012). Strategic management and competitive
advantage: Concepts and cases (4th ed.). New Jersey: Pearson.
10. Makadok, R. (2001), “Toward a synthesis of the resource-based
and dynamic-capability views of rent creation,” Strategic Management
Journal , 22(5), 387–401 (p. 389).
 2 Transformative Marketing: A Marketing 5.0 Perspective 27

11. From a knowledge standpoint, capabilities are conceptualized by

Day, G. S. (1994), “The capabilities of market-driven organizations,”
Journal of Marketing, 58(4), 37–52, as complex bundles of skills and
accumulated knowledge, exercised through organizational processes
that enable firms to coordinate activities and make use of their assets
(p. 38).
12. Day, G. S. (2011), “Closing the marketing capabilities gap,” Journal of
Marketing, 75 (4), 183–195.
13. Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M., Singh, H.,
Teece, D., & Winter, S. G. (2007). Dynamic capabilities: Under-
standing strategic change in organizations. Blackwell (p. 4).
14. Day, G. S. (2011), “Closing the marketing capabilities gap,” Journal of
Marketing, 75 (4), 183–195 (p. 185).
15. Barney, J. & A. M. Arikan (2001). The resource-based view: Origins
and implications. The Blackwell handbook of strategic management,
124–188 (p. 140).
16. Mintzberg, H. (1987), “The strategy concept I: Five Ps for strategy,”
California Management Review, 30 (1), 11–24.
17. Varadarajan, R. (2010), “Strategic marketing and marketing strategy:
Domain, definition, fundamental issues and foundational premises,”
Journal of the Academy of Marketing Science, 38(2), 119–140.
18. Netflix (2020), “Netflix Culture,” Netflix.com, accessed from https://
jobs.netflix.com/culture.
 3
Transformative Marketing with Artificial
Intelligence

Overview
Artificial intelligence (AI) is ubiquitous in our everyday lives. By utilizing data
analysis, machine learning, algorithms, and natural language processing, AI
influences the marketing industry by giving companies a competitive advan-
tage for the present and the future.1 Currently, nearly all industries and
business functions use AI to varying degrees. Table 3.1 provides the adoption
of AI by industry and function in 2022.
As provided in Table 3.1, the business function deploying AI the most
was risk management in the high-tech/telecom industry (38%), followed
by service operations for consumer goods/retail (31%), and product and/or
service development for financial services (31%). Notably, the use of AI in
marketing is low. This is perhaps due to the relatively higher levels of indi-
vidual human instincts and interventions required in the marketing function,
compared to the other functions. Looking ahead, this also represents areas of
potential growth and opportunities for companies to develop AI applications
in marketing. Companies have already started to use AI for initiating person-
alized customer actions. In this regard, the importance of AI for businesses
can be seen in the varied uses of AI such as automating customer interactions,
personalizing customer journeys across channels, and predicting customer/
prospect behavior, among others.2 Other growing applications of AI in
marketing include conducting survey research, writing and publishing, inter-
pretation and translation services, and public relations management, among
others. As the number of AI applications increases, the AI ecosystem is also

© The Author(s), under exclusive license to Springer Nature 29

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_3
 30

Table 3.1 AI adoption worldwide 2022, by industry and function

Human Product/service Strategy and Supply chain
resources Manufacturing Marketing and development Risk Service corporate management
(%) (%) sales (%) (%) (%) operations (%) finance (%) (%)
All industries 11 8 5 10 19 19 21 9
V. Kumar and P. Kotler

Business, legal, 11 10 9 8 16 20 19 12
and
professional
services
Consumer 14 4 3 4 15 31 29 11
goods/retail
Financial 1 8 7 31 17 24 23 2
services
Healthcare/ 15 7 2 4 22 12 8 8
Pharma
High-tech/ 6 6 4 7 38 21 25 8
telecom
Source Stanford University. (March 15, 2023). AI adoption by industry and function, 2022 [Graph]. In Artificial Intelligence Index Report
2023. Retrieved September 4, 2023, from https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_AI-Index-Report_2023.pdf
 3 Transformative Marketing with Artificial Intelligence 31

Table 3.2 Selected companies in the AI ecosystem

Selected AI applications Key players
Data Science Platforms SAS, IBM Watson, Rapidminer, Anaconda
Data Generation & Labelling Hive, Upwork, Amazon MTurk, Unity
Machine Learning Operations (MLOPS) Fiddler, Arize, Neural Magic, Evidently AI
Computer Vision Amazon SageMaker, Matroid, clarifai
Speech Siri, Alexa, Cortana, PolyAI
Natural Language Processing (NLP) Google Cloud Natural Language AI, Hugging
Face, Amazon Translate
Edge AI Hailo, Deeplite, Edge Impulse
Horizontal AI/AGI Google Research, Microsoft Research, Meta
Research, OpenAI, stability.ai, Midjourney
AI Hardware Google Cloud, Nvidia, Intel, Graphcore,
Cerebras
Closed Source Models OpenAI (ChatGPT), OpenAI (DALLE2), OpenAI
(GPT-4), DeepMind, Midjourney, Google Bard,
Google LaMDA
Source Insights Compass 2023—Unleashing Artificial Intelligence’s true potential.
In Statista. Retrieved September 4, 2023, from https://www.statista.com/download/
MTY5Mzc0Njk0MiMjMjIwMjY0OCMjMTM4OTcxIyMxIyNudWxsIyNTdHVkeQ==

expanding with more companies developing AI offerings and applications.

Table 3.2 presents a list of selected companies in the AI ecosystem.
As listed in Table 3.2, AI solutions are dominant in many user-facing inter-
actions. For instance, AI-powered chatbots influence the online shopping
experience by personalizing the experience based on the customer’s previous
shopping data. Everyday uses of AI include automated customer support for
customer queries and requests, and travel assistance wherein chatbots provide
users with travel recommendations, ticket booking, and landmarks recom-
mendations. The growth of AI and its prospects for the marketing industry
are immense.
This chapter is organized in the following manner. First, a brief history of
the origin of AI is presented, followed by a definition of AI (from a marketing
standpoint), and a discussion on related processes that are linked to AI such as
neural networks, and deep learning, among others. In this regard, some prac-
tical applications of such AI processes are presented. Next, some marketing
applications of AI focusing on understanding customer needs, revisiting firm
capabilities to integrate AI, designing AI-focused marketing mix strategies,
driving customer engagement through AI, and designing digital strategies
with AI are discussed. Finally, the future of AI for the marketing industry
is envisioned through specific customer-facing tasks such as the inclusion
of robotics, user experience, and seamless integration of various customer
interaction points with the company.
32 V. Kumar and P. Kotler

Origin, Definition, and Components of AI

The quest for AI over the years has not been smooth sailing. In this regard,
Alan Turing was a pioneer in identifying the possibility of AI as a field of
study. Turing believed that computers can assess and solve problems like
humans. He published how to build and test machines with intelligence in his
1950s paper titled “Computing Machinery and Intelligence”.3 This seminal
research laid the foundation for the field of AI and spurred research in this
area. In 1956, John McCarthy and Marvin Minsky hosted the Dartmouth
Summer Research Project on Artificial Intelligence. This event marked the
first AI program, and it was where the term “artificial intelligence” originated.
In the following years, computers were able to become more accessible and
less costly, leading to more advances in AI. Computers’ memory and speed
improved, as well as more knowledge was gained on the usage of algorithms.
Today, our lives encompass several elements of AI through technology. The
entertainment, banking, and marketing industries all use AI. From voice assis-
tants such as Siri, Cortana, and Alexa to generative AI tools like ChatGPT,
Bard (Google’s chatbot and content generative tool), DALL-E (Open AI’s
tool for image and art generation), AI continues to affect our everyday lives.
In establishing the concept of AI, John McCarthy described AI as “the
science and engineering of making intelligent machines, especially intelligent
computer programs”.4 The idea of intelligence comes from the framework
of the human brain, such as the ability to solve problems, reason, and learn.
In marketing, AI is defined as “a system’s ability to interpret external data
correctly, to learn from such data, and to use those learnings to achieve
specific goals and tasks through flexible adaptation”.5 Now, with the integra-
tion of AI, marketers can automate tasks (lead generation, scoring, customer
retention). By leveraging AI, they can identify potential customers and
engage with them at times they are most likely to respond to marketing
messages. Additionally, AI technologies can create customer profiles based
on the purchase history and interactions customers have had with the
brand. Through these profiles, marketers can generate targeted marketing
campaigns, and enhance customer engagement and conversion rates. And
lastly, AI is an essential component of predictive analytics and forecasting.
Harnessing its ease in navigating through large and complex datasets, AI can
forecast customer responses, as well as business metrics like revenues, returns
on investments, etc. to guide strategic decision-making.6
The power of AI stems from various subfields like natural language
processing, neural networks, and deep learning. Specifically, AI operates in
the field of automation and continuous learning, acting as the intelligence
 3 Transformative Marketing with Artificial Intelligence 33

that drives data-focused analytics and decision-making using data science.7

That is, AI can assist in programming many of the processes in handling
information that pertains to storing, retrieving, and using relevant informa-
tion for the marketing activities of firms. Further, AI can be used to teach
machines and generate insights to accomplish specific tasks by processing
large amounts of data and recognizing patterns in the data.
The language used by AI scientists is like that used by humans. While
computer programs are developed using specific codes, the codes are not
easily understood by all people. Therefore, when machines go through natural
language processing (i.e., the natural way humans communicate), it results in
the development of value-rich human-focused solutions. Natural language
processing (NLP) consists of natural language understanding and natural
language generation. Ambiguity is a phenomenon in natural language and
pertains to understanding a linguistic structure in multiple ways. This is
because many words, phrases, and sentences can have multiple meanings
or even similar meanings, addressing ambiguities in NLP is essential for
understanding and comprehending that the understanding of the natural
language aims for analyzation and comprehension of the text in the intended
manner. Ambiguities can be classified into four types, depending on where
the source of ambiguity lies in the text. The ambiguity may arise at the level
of words (lexical ambiguity), syntax (syntactic ambiguity), semantic interpre-
tation (semantic ambiguity), and the interaction between interpretation and
context (pragmatic ambiguity).8 By adequately addressing ambiguities, NLP
can help to understand and make sense of the spoken word in a manner
that is valuable. However, as mentioned earlier, owing to the complexities of
the human language and how computers interpret it, NLP continues to be a
challenge for machines to implement.9
In machine learning (ML), machines realize specific patterns and improve
their performance for the future. Specifically, by considering past informa-
tion (i.e., referred to as experience), machines gain the ability to learn while
they perform, thereby showing performance improvement. The past infor-
mation can be in the form of collected data or information actively sourced
through interaction with the environment. The quality of learning is depen-
dent on the volume and quality of data, and the key outcome is predictions
about key variables of interest.10 To facilitate deep learning, AI uses neural
networks, like the way a human brain functions. Artificial neural networks
(ANNs) consist of a regular neural network and a deep neural network. Their
differences relate to the number of neurons. A deep neural network contains
several hidden layers of neurons, which is where information is processed.
The more the layer of neurons, the more connections occur. In general, ML
34 V. Kumar and P. Kotler

focuses on learning that is inherently based on data analysis and statistics,

with an added emphasis on predictions (and higher-order interactions that
are not pre-specified).11 As a result, ML can produce predictions that can
also be used to (in)validate theories and calibrate data.12
Following deep learning, inference is possible. Inference takes place when
abilities gained from training are used to understand new data. An example
of deep learning and inference in use today is the facial recognition tool that
allows Facebook to tag known family and friends in photos. In conclusion,
the overview of AI, the following three vignettes present the possibilities of
AI and how companies and users are deriving value from such offerings.

The Rise of the Transformative Home

The use of transformative devices is constantly increasing as consumers seek

devices that can perform small tasks within the home.13 Alexa, developed by
Amazon to accompany an Echo device, comes with the ability to answer ques-
tions and requests, such as forecasting the weather, playing music, dimming
the lights, or locking doors (see Image 3.1). Activation of the device follows
the term “Alexa,” and a cloud-based service will do the job of answering the
requests.14 Other popular tools in the transformative home include solutions
for travel planning (e.g., Mezi), music (e.g., Pandora), financial planning
(e.g., Olivia), language translation (e.g., Liv), and smart-home solutions (e.g.,
Nest), among others. Due to the popularity of mobile devices, consumers use
Siri and Google Assistant more frequently than Amazon’s Alexa.

Image 3.1 Smart locks for homes. A smart lock device used for home protection
(Source Photo by Sebastian Scholz (Nuki) on Unsplash)
 3 Transformative Marketing with Artificial Intelligence 35

In 2019, there were an estimated 3.25 billion voice assistants in use

worldwide, which is expected to reach 8.4 billion active devices in 2024.15
Virtual assistants have become an important part of the smart device business,
playing an important role in how users engage with their devices. Companies
are increasingly looking for bigger and better uses of “smart” technology as
the business grows and its technology advances. Tech-savvy consumers may
now communicate with their connected homes and automobiles in the same
manner that they can with their smartphones. The popularity of voice assis-
tants continues to grow, which contributes to the market of AI, among others.
Similarly, Amazon, Google, and Apple continue to work on advancing their
AI devices. Amazon aims to allow conversations with Alexa to last longer
without having to repeat the wake word “Alexa” before every request. Google’s
Duplex on the Web allows Google Assistant to book appointments, make
reservations, and even book car rentals using autofill. Apple plans to update
Siri with voice-recognition ability to provide the user with customized recom-
mendations. Overall, the future of voice assistant devices is expected to have
a more natural dialog and human-sounding voice.

Personalized Education

AI is also making strides in the field of education. Particularly, AI is used

in educational applications such as intelligent tutoring, simulation activ-
ities in science, personalized learning, educational resources and courses,
and educational games. The standard model of education has largely stayed
unchanged, with one instructor giving the same content to an entire class of
students but paying limited attention to their individual growth. The need to
design personalized learning programs for each student is currently the most
powerful motivating factor for AI in education and learning. When instruc-
tors think of testing students’ knowledge, exams and tests are the main factors
for them to analyze. This aspect can change as AI tools can be used to analyze
students’ educational data to assist teachers in creating personalized learning
plans. For example, Brightspace Insights by D2L can analyze data from
online sources, publishers, and learning apps to come up with a student’s
learning behavior. Brightspace Insights provides teachers with information
for them to decide how to teach, and it predicts the learner’s current issues
allowing teachers to address the problem right away.16 Similarly, Georgia
State University introduced an AI chatbot, Pounce, that reduced “summer
melt” (i.e., students enrolled in spring dropping out of college in fall) by 22%.
Using conversational AI technology, the chatbot was able to guide students
in getting their queries answered in a timely and relevant manner, thereby
36 V. Kumar and P. Kotler

helping them stay in college.17 At the K-12 level in the United States, Cogni-
tive Tutor® , an AI-based application developed by Carnegie Learning, is a
secondary mathematics program with an emphasis on how learners under-
stand and absorb mathematics. Teachers help students learn by letting them
acquire and apply new material while discussing their work. A textbook,
adaptive software, or a combination of textbook and software activities can
be used to implement the curriculum.
Similar tools are also developed for younger kids, as part of developmental
learning aids. Pillar Learning created an AI interactive toy, Codi, for chil-
dren with customized content based on the child’s age, ability, and interest.
Codi contains songs, lessons, and stories that can be regulated by parents
through a coordinating mobile app. According to the CEO of Pillar Learning,
Dayu Yang, “Unlike other children’s toys, Codi is development-focused, over
purely comfort or entertainment-focused”.18 Other examples of such appli-
cations include Querium Corporation using an AI platform called Stepwise
to help students with personalized lessons on STEM, and Hubert.ai creating
an assessment system that can analyze a child’s skills, such as imagination,
background reasoning, and creativity.19 These programs are all made possible
by AI’s ability to augment personalized learning.

The World of Wearables

Wearable devices (popularly referred to as wearables) are electric tech-

nology or devices incorporated into items that can be worn on a body.
These devices are used for tracking information (sleep schedules, heart rates,
activity) on a real-time basis (see Image 3.2). While wearable technology
entered the consumer market in recent years, they have been widely used
for military, medical, and healthcare purposes. Smartwatches, fitness trackers,
head-mounted displays, sports watches, and smart jewelry are a few of the
wearables that are trending in today’s consumer markets.20
Wearables consist of MEM (Micro-Electric-Mechanic) sensors that are
designed to sense and measure a diverse range of environmental and phys-
ical parameters such as motion, temperature, humidity, etc. The different
types of MEM sensors in wearables include accelerometers (track movements,
distance traveled, sleep patterns), gyroscopes (detecting gestures, measuring
orientation), and barometric pressure sensors (for weather prediction, and
altitude tracking). The sensors make wearables accurate and also strengthen
their capabilities in offering valuable insights into users’ health and daily
activities. The popular applications of wearables are discussed below.
 3 Transformative Marketing with Artificial Intelligence 37

Image 3.2 Wearable devices. A smartwatch is a wearable device that provides

several features such as local weather, to-do lists, appointments, personal commu-
nications, personal health-related information, and much more
(Source Photo by Fabian Albert on Unsplash)

Smartwatches and Fitness Trackers. As the industry competition intensi-

fies with new entrants, brands such as Apple, Fitbit, Garmin, Samsung, and
others are increasing efforts to gain market share. For instance, the Apple
Watch Series 8 can now detect skin temperatures, track menstrual cycles,
detect falls, and call for help using its fall detection feature. Smartwatches
and fitness trackers are seeing a surge in new users (including people from
older populations), to cater better to this new segment by adding abilities
such as glucose monitoring for people with diabetes. Similarly, Fitbit added
a feature to detect sleep apnea, while also offering features that track activity,
steps taken, sleep patterns, etc.
Head-Mounted Displays: Ten years ago, Google ventured into the Head-
mounted Displays space with their invention—the Google Glass. Their
wearable smart glasses were pulled from the market in 2015 due to reasons
that included high price and safety and privacy concerns. While Google
still may explore the area further, other industry leaders like Microsoft and
Apple are taking the space by storm. Microsoft’s HoloLens, Microsoft’s
38 V. Kumar and P. Kotler

mixed-reality headset, combines the best of augmented reality (AR) and

virtual reality (VR) and can boost an organization’s productivity (specifically
across manufacturing, healthcare, and education). Through multiple sensors,
advanced optics, and holographic processing that melds seamlessly with the
environment—holograms can be used to display information, blend with
the world, and simulate a virtual world. The main features of this device
include Holograms (create photographic images of objects without using a
lens), Cortana (Microsoft’s Virtual Assistant), and Cloud (the device works
seamlessly with Microsoft Azure).
Smart Jewelry: Searches for health-tracking jewelry were up 200% year over
year, with millions of these devices being sold globally. In 2023, customers are
seeing a new era of smart jewelry—sleek, stylish, technologically advanced,
and discreet. Smart jewelry has expanded its focus on sleep data, fertility,
and mental health—thus providing a holistic picture of well-being. For
instance, Oura, the Finnish health technology company known for launching
the Oura Ring in 2015, collects data on heart rate, body temperature,
respiratory rate, sleep data, etc. from the user’s finger. They launched the
third-generation Oura Ring in 2021, with new features such as heart rate
monitoring, blood oxygen monitoring, period predictions, etc. As of 2022,
the company sold more than one million rings, with celebrities like Jennifer
Aniston, Prince Harry, and Gwyneth Paltrow using it. Other examples of
smart jewelry include Bellabeat’s Leaf Urban, which is a bracelet, necklace,
or brooch, Ringly’s Aries smart ring, Fossil’s Q Tailor analog watch, and
Ringly’s Aries bracelet, among others. While these products are receiving crit-
ical acclaim, companies continue to develop designs and accuracy to offer the
best customer experiences.

AI in the Marketing 5.0 World

The utilization of AI in marketing has become increasingly significant in
recent years. AI has revolutionized the way businesses approach marketing
by providing valuable insights into consumer behavior and preferences. With
the help of AI, marketers can analyze vast amounts of data and gain a deeper
understanding of their target audience, allowing them to create more person-
alized and effective marketing campaigns. Companies that are adopting AI
into their business processes are gaining a competitive advantage that will
augur well in the future. Expanding on the Marketing 5.0 concept discussed
in Chapter 2, this section presents how AI operates in the Marketing 5.0
world. Particularly, this section discusses five examples of where AI is applied
through the lens of Marketing 5.0 and establishes how such actions can also
bode well for humanity.
 3 Transformative Marketing with Artificial Intelligence 39

Data-Driven Marketing Using AI

The significance of technology in delivering customized experiences for

customers is being extensively documented. In this context, it is intriguing to
examine how Spotify, a digital native company, utilizes artificial intelligence
(AI) and implements data-driven marketing. Spotify’s AI models suggest
audio content to users by harnessing user data, such as playlist creation,
listening history, and interactions with the platform, to predict their pref-
erences for future listening. Spotify heavily relies on reinforcement learning,
which optimizes long-term user satisfaction, to provide highly personalized
recommendations that enhance user happiness and encourage continued
engagement. While each player in the music streaming platforms industry
has its unique characteristics, Spotify’s ability to offer hyper-personalized
recommendations positions it at the forefront. By leveraging AI, they have
revolutionized their service, generating unparalleled value in the market.
According to the company, they process an astounding half a trillion events
daily to train their models, enabling them to provide recommendations of
superior quality as they accumulate more data.21
Recently, Spotify introduced a new AI DJ that acts as a personalized guide
for users based on their music data.22 This feature was initially launched as a
beta version and offers a curated selection of music and commentary on tracks
and artists in a realistic voice. The AI guide can sift through the latest music,
revisit users’ old favorites, and bring back albums they have not listened to
in years. The DJ is a combination of Spotify’s personalization technology,
Generative AI, and a dynamic AI voice that brings text to life with realistic
voices.

Predictive Marketing Using AI

As technology continues to evolve and our interactions with it become more

extensive, it becomes crucial to establish a series of procedures that allow us to
effectively analyze data and stay focused on the objectives that organizations
initially set. To assist organizations in making informed decisions, tech-
nology companies are developing various AI-based tools that enable them to
extract valuable insights from data. A notable example is Salesforce’s Einstein
Analytics.
Salesforce Einstein Analytics is a cloud-based analytical solution designed
to help Salesforce users gain insights from data collected from various sources
such as ERPs, data warehouses, and log files.23 The main objective of this
platform is to address the challenge of consolidating data from different loca-
tions and generating valuable insights. By leveraging AI, the tool is capable of
40 V. Kumar and P. Kotler

generating reports, building predictive models, and even providing chatbot

functionalities. With its data exploration and predictive analytics capabilities,
businesses can find answers to critical business questions and make smarter
decisions to meet customer needs. Additionally, the tool offers AI forecasting,
empowering the sales team to assess risks, provide interactive deal guidance,
identify potential missed opportunities, and offer recommendations to
improve performance. Lastly, the platform provides complete visibility into
the sales pipeline, enabling a transparent evaluation of each sales metric
throughout the process.
The predictive capabilities of Einstein Analytics have made it a popular
tool across various industries. For instance, in the healthcare sector, Einstein
Analytics for Healthcare leverages AI to provide care coordinators, utilization
managers, and referral managers with valuable insights and metrics related
to their patient populations. By using this tool, healthcare coordinators can
quickly identify patients who are not following their care plans and take
proactive measures to prevent unnecessary hospital admissions. Utilization
managers can also benefit from insights into the care request process, which
can help them reduce cycle times and increase approval rates. Additionally,
referral coordinators can use patient referral management insights to better
understand referral sources, identify areas for improvement, and increase
patient conversions.

Contextual Marketing Using AI

Contextual marketing using artificial intelligence involves the use of sophisti-

cated algorithms and machine learning techniques to understand the context
in which consumers interact with brands. This includes analyzing factors such
as location, time of day, device used, and even the weather to deliver tailored
marketing messages. AI-powered systems can also analyze social media posts,
online reviews, and customer feedback to gain deeper insights into consumer
sentiment and preferences. The integration of artificial intelligence in contex-
tual marketing has not only improved the efficiency and effectiveness of
marketing campaigns but has also enhanced the overall customer experi-
ence. AI-powered chatbots and virtual assistants further enhance the customer
experience by providing instant and accurate responses to queries, offering
personalized recommendations, and even assisting with purchases.
Starbucks is a prime example of how AI can revolutionize contextual
marketing. The company firmly believes in the power of innovation, empha-
sizing the need for swift action rather than lengthy timelines. This allows for
constant improvement in the customer experience and the lives of employees.
 3 Transformative Marketing with Artificial Intelligence 41

By utilizing AI and data science, Starbucks can inform its processes and
product development. They take both quantitative and qualitative feedback
from customers, empowering their partners and exploring ways to add more
value to the organization.
In 2019, Starbucks launched Deep Brew, which uses AI and IoT technolo-
gies to optimize store labor allocations, drive inventory management, and
personalize the customer experience.24 This technology streamlines opera-
tions and humanizes the customer experience, making it easier for customers
to get what they want and for employees to provide it. By embracing AI,
Starbucks can stay ahead of the curve and provide a unique and person-
alized experience for its customers. Furthermore, by analyzing customer
purchase history, preferences, and behaviors, Deep Brew generates personal-
ized recommendations for customers through the mobile app. This enhances
user experiences and drives engagement. In addition to this, Deep Brew also
helps Starbucks create targeted promotions and offers by identifying trends
and patterns. This allows Starbucks to launch campaigns that resonate with
specific customer segments, driving sales and engagement.
Starbucks is not only using Deep Brew to create contextually relevant
experiences for its customers.25 The company is also exploring other initia-
tives such as location-based targeting. The Starbucks app uses geolocation to
provide location-specific promotions and features to users. When a customer
is near a store, the app can send notifications about ongoing offers or person-
alized discounts to encourage visits. By leveraging AI and other technologies,
Starbucks can create a more personalized and engaging experience for its
customers, ultimately driving sales and loyalty.

Augmented Marketing Using AI

Augmented marketing is a powerful tool that can help businesses improve

their marketing efforts in two critical ways. First, it allows marketers to create
more targeted and personalized marketing campaigns. By analyzing customer
data, AI algorithms can identify patterns and preferences that can be used to
create more effective marketing messages. Second, augmented marketing can
help businesses save time and money. By automating certain marketing tasks,
businesses can reduce the time and resources required to create and execute
impactful campaigns.
AI plays a crucial role in enhancing human efforts, particularly in the
field of cancer research and treatment. The shortage of pathologists, espe-
cially in cancer treatment, has become a significant concern in recent years,
mirroring the challenges faced by various sectors of healthcare. Additionally,
42 V. Kumar and P. Kotler

the aging population has led to an increase in the workload of pathologists.

Pathologists must allocate an appropriate amount of time to each case, as
the consequences for patients can be severe if too much or too little time
is spent. Although digitization is being explored as a means to enhance the
efficiency of pathologists’ workflow, it presents significant challenges. For
example, the process of digitizing a single slide can consume a substantial
amount of storage, exceeding a gigabyte. Consequently, this places immense
pressure on the technology infrastructure and incurs substantial costs for data
collection and storage.
Google and the US Department of Defense have collaborated to tackle
this challenge by creating the Augmented Reality Microscope (ARM).26 This
microscope, resembling the ones commonly used in high school labs, is
connected to a computer equipped with AI models. By placing a prepared
glass slide under the microscope, the AI can accurately outline the location of
the cancer. Pathologists can observe this outline as a bright green line through
their eyepieces and on a separate monitor. Additionally, the AI provides infor-
mation on the severity of the cancer and generates a black-and-white heat
map on the monitor, displaying the cancer’s boundaries in a pixelated format.
Moreover, the ARM software’s ability to capture screen grabs of slides is
expected to bring significant cost savings to healthcare organizations.
Although the ARM is not intended to substitute digital pathology systems,
its uncomplicated design can aid healthcare institutions in obtaining speedy
diagnoses. At present, there are only 13 ARMs in existence, and they are
not yet utilized to assist in diagnosing patients. Nevertheless, experts suggest
that it could be a valuable resource for pathologists who do not have conve-
nient access to a second opinion. All things considered, due to the cost
savings and enhanced workflow efficiencies, this technology has the potential
to revolutionize cancer research and treatment globally.

Agile Marketing Using AI

As mentioned in Chapter 2, agile marketing involves the utilization of decen-

tralized, cross-functional teams to swiftly conceptualize, design, develop, and
validate products and marketing campaigns. When coupled with AI, agile
marketing offers a dynamic and flexible approach to marketing that is unpar-
alleled. With AI algorithms analyzing vast amounts of data, marketers can
gain valuable insights into consumer behavior, preferences, and trends. This
enables them to make data-driven decisions and tailor their marketing efforts
to target specific audiences with precision. By leveraging AI, businesses can
automate repetitive tasks, streamline processes, and optimize their marketing
efforts for better results.
 3 Transformative Marketing with Artificial Intelligence 43

For instance, consider the case of Kraft Foods. The company recently
announced plans to implement its Agile-based strategy—Agile@Scale—
throughout all areas of its business operations, incorporating specialized pods
of teams dedicated to addressing specific challenges and opportunities.27 This
expansion aims to enhance the company’s ability to effectively compete with
private label brands by efficiently managing increased promotional activities
this year.
As part of its Agile@Scale approach, the organization has implemented
multifunctional pods that consist of twelve individuals who concentrate on
crucial opportunities, including revenue management and innovation. This
strategy combines technology investments, such as artificial intelligence, with
Agile methodologies to enhance the company’s in-house capabilities while
collaborating with vendors like Microsoft. As per the strategy, the pods are
distributed across various departments such as innovation, logistics, manufac-
turing, sales, and finance. These pods are defined by ROI and consist of teams
comprising both Kraft Heinz employees and external partners like Microsoft.
Each team is dedicated to addressing a specific challenge or opportunity.
Through the partnership with Microsoft, a “Supply Chain Control Tower”
was established to serve as an air traffic control for the company’s entire
product portfolio. This innovation provided the company with real-time visi-
bility into plant operations and automated the supply chain distribution
across Kraft Heinz’s 85 product categories. By utilizing Azure’s AI, IoT, and
data analytics capabilities, the company was able to get its products efficiently
and cost-effectively to its 2,500 US retailer and food service customers, as well
as millions of consumers.28 By implementing this program, Kraft successfully
integrated AI into its supply chain visibility operations, resulting in a signif-
icant increase of $30 million in sales. Moreover, this initiative enabled the
company to streamline its operational priorities and automate the identifica-
tion of service risks and operator alerts. As a result, Kraft Heinz has effectively
reduced its operator alerts by an impressive 42% through the utilization of
this advanced technology.29

Current AI Applications in Marketing

Companies are increasingly using AI technology to develop customer-focused
solutions.30 Additionally, governments across the world are also keenly
looking into AI investments to spur economic and technological growth.31
When used correctly, AI can become a critical tool for boosting companies’
productivity and increasing the speed of the decision-making process. It is
critical to understand that AI-powered tools can enable managers to have a
44 V. Kumar and P. Kotler

more in-depth insight into subjects such as segmentation and positioning

without spending too much time.
Further, AI has achieved enhanced capabilities with the help of big data.32
By analyzing vast sets of data of demographics and personal information,
AI can suggest personalized products and services, which generally include
advertisements and strategic discounts to influence consumers directly. AI
allows product curation on a scale impossible for any human or group of
humans to achieve. Machines are better at it, and the insights created as a
result of their ability to slice and dice data are much better than the ones
performed by humans. Additionally, companies can use AI to offer enhanced
search engines, which are based on machine learning-based algorithms. For
instance, Google, the leader in online search, also incorporates AI to provide
elaborate and comprehensive results regarding search queries. Using a tech-
nology called Search Generative Experience, Google leverages large language
models and generative AI to not only identify the most relevant informa-
tion but also present it in neatly written text (along with the relevant search
results) that the user can readily use.33 Initially popularized by Google, many
companies are trying to offer smarter search results. For instance, Carmax’s AI
tool sifts through choices regarding brands, mileage, and price ranges to fully
customize options, acting as the customer’s personalized dealer. This ensures
that the consumer sees only the content and options that are relevant to
their needs.34 The section presents five specific application areas where AI
continues to help companies in developing marketing initiatives.

Understanding Customer Needs to Deploy AI

A deep understanding of customers’ needs and wants is critical to the success

of any company. Following this, firms are collecting more data on various
aspects of their business than ever before, which offers both significant oppor-
tunities and challenges as firms try to convert all this data into actionable
insights. However, firms are facing a paradox of increasing information, yet
decreasing knowledge and insight. This has been identified as quantity over-
powering quality, thereby resulting in poor-quality information.35 In other
words, it is not a case of how much data firms possess, but a case of what
data they have for decision-making. Further, analyzing and using that data in
the decision-making process raises different types of challenges. In this regard,
AI serves companies well in analyzing the volumes of data collected.
To speed up the process for simple procedures and daily responsibilities,
chatbots, and virtual assistants can be beneficial tools. Companies can take
advantage of these tools to increase customer satisfaction by optimizing the
 3 Transformative Marketing with Artificial Intelligence 45

time spent on these routine tasks. By examining large data sets, AI can
predict consumer needs and wants with a high degree of accuracy that can
help firms develop timely and valuable offerings. An industry where AI is
used for understanding customer needs is the fashion industry. Here, the
popular use cases include Zara using AI algorithms to generate textures and
patterns, Adidas and Nike allowing customers to design their shoes using AI
algorithms, and Stitch Fix using AI to deliver a superlative online shopping
experience, among others. Particularly, Stitch Fix utilizes AI extensively to
drive several of its core functions. While they are known for the styling algo-
rithm that picks out the best clothes for their clients based on their stated
preferences and needs, the company also employs AI in other areas.36 Exam-
ples of such uses include using algorithms to pair the right stylists with their
clients, helping buyers predict future styles to better manage inventory, and
identifying a buyer’s ‘latent style’ and ‘latent size’, regardless of their explicitly
stated preferences. Overall, these algorithms work together to deliver clothes
that best-fit clients’ distinctive needs.

Revisiting Firm’s Capabilities to Integrate AI

As noted earlier, ML is one of the main driving forces of AI. Specifically, ML

examines similar statistical patterns that computer systems use to perform a
specific task based on models instead of precise instructions. For businesses
that thrive in the fiercely competitive environment, it is vital to implement
AI effectively in the solutions that have been offered to the customers. This
implies that it is essential that the AI tool be in sync with firm objectives
for the AI implementation to triumph. Further, it is important to set clear
expectations for AI tools. In this regard, a key reason for companies to not
adopt AI is the insufficient or unclear returns from an AI implementation.37
Furthermore, AI can help businesses to allocate their resources more
efficiently. Many job functions currently contain several repetitive and time-
consuming tasks, such as document processing, proofreading, and data
collection, among others. The AI infrastructure enables businesses to tackle
these time-consuming tasks with ease. Therefore, there is more time to spend
on essential tasks, that are more important for the companies’ future, such
as creative thinking and decision-making. For instance, it has been estimated
that 60% of occupations will have at least 30% of their work automated, in
addition to the actual decline in certain occupations. Further, AI is also fore-
cast to create new job roles previously nonexistent.38 In this regard, AI is set
to alter the workplace in terms of type of work and workforce management.
46 V. Kumar and P. Kotler

Designing Marketing Mix Strategies with AI

In a dynamic business environment where consumer preferences and

demands change continuously, it can be challenging to determine a marketing
strategy to execute. Today, AI allows businesses to examine these instant
changes and adapt to the fast-paced environment. Breaking down AI’s role
in the marketing mix provides interesting insights into the extent to which it
has permeated through the organization. This can be observed in how AI is
included in the marketing mix strategies of companies, as discussed below.
AI in product decisions: AI in product decisions refers to the use of arti-
ficial intelligence tools to help designers and manufacturers create better
products. With AI, designers can collect and analyze large amounts of
data, understand customer needs, and create efficient, cost-effective prod-
ucts. It offers capabilities to customize offerings to suit the customer needs.39
Another feature of AI in product design is its ability to generate designs
based on a set of parameters (materials, costs, size, etc.). In this regard, gener-
ative design algorithms are becoming increasingly popular in the industry
today; with it being used in aerospace, architecture, and manufacturing of
consumer products. For instance, companies are increasingly using digital
twins to design, manage, and update their products in real time. A digital
twin is a virtual representation of a physical product available in real-time
through new-age technologies such as AI and connected devices. Such a
format allows companies to define, manage, and update product features and
product design, in addition to monitoring the performance of the product
and predicting potential performance issues. Examples of companies using
digital twins include Microsoft, Boeing, and Mercedes-Benz, among others.
In the future, as AI becomes more accessible and affordable, more companies
are expected to adopt digital twins to manage their product development and
management that can not only drive better product performance but also
deliver immersive and engaging experiences to customers.
AI in pricing decisions: In today’s competitive business environment,
companies are constantly looking for ways to increase revenue, and maintain
and gain a competitive advantage. In recent years, one approach that has
gained attention is price optimization using AI algorithms. AI’s capability
to analyze large amounts of real-time data offers the potential to identify
optimal pricing for products and services at any given time. For example, the
ride-sharing app, Uber, uses dynamic pricing. Here, AI algorithms analyze
real-time data to forecast demand, identify pricing trends, and adjust prices
in real time. For Uber, this translates to adjusting prices based on real-time
market demand and traffic conditions. Additionally, AI-based analytics
help companies analyze customer data (purchase history, demographics,
 3 Transformative Marketing with Artificial Intelligence 47

online behavior) to create a personalized pricing strategy for each customer.

Through this approach, companies can increase customer loyalty, and boost
sales by offering prices that match customer needs and their willingness to
pay. Brands can also build stronger relationships with customers and improve
customer satisfaction.
AI in place and promotion decisions: Product access and product avail-
ability are essential for maximizing customer satisfaction levels. Product
distribution, as a process, relies on various other processes like logistics, inven-
tory management, transportation, etc.—all of which are repetitive processes.
AI offers solutions that automate these processes, through the integration
of other new-age technologies like robots for packaging, drones for deliv-
eries, and IoT (the Internet of Things) for order tracking and refilling.40
Concerning promotions, AI plays a role in the personalization and customiza-
tion of the message as per the customer profile. Emotive AI algorithms and
content analysis could be deployed to track and understand customer senti-
ments. For instance, AI-based online writing tools such as CopyAI, Jasper,
and QuillBot help users generate various types of content (blog headlines,
emails, social media content). It provides tools and writing frameworks to
aid marketers in generating content and is great for beginners to get familiar
with generative AI.

Driving Customer Engagement Through AI

Having the advantage of AI allows companies to connect with their customers

efficiently. Within AI, ML algorithms (e.g., collaborative filtering, deep
learning, etc.) are increasingly being used to create tools that not only under-
stand customer needs and expectations but also identify firm offerings that
users are more likely to favor.41 Such firm actions would likely result in
solidifying the relationship between customers and marketers.42,43
Further, satisfied customer relationships that also have an emotional
bonding have been identified to progress to a state of engagement,44 and
positive relationships play a role in influencing customer engagement behav-
iors.45 Accordingly, engagement (with two stakeholders) has been defined as
the attitude, behavior, the level of connectedness (1) among customers, (2)
between customers and employees, and (3) between customers and employees
within a firm.46 Further, the more positive the attitude and behavior and the
higher the level of connectedness, the higher the level of engagement.
Data allows AI to analyze, predict, and recommend personalized consumer
needs and wants smartly and efficiently.47 Consumers are always searching for
products and services that make their lives better and easier. In this regard,
48 V. Kumar and P. Kotler

offering personalized solutions via an AI tool in a curated manner can be

considered by firms to improve customer engagement.48 Curated offerings
play a critical role for firms, especially in an environment where users have
access to a high volume of information.49 For instance, a recent survey found
that 48% of consumers moved their purchase to a different provider (online
or in-store) simply because the offerings were poorly curated.50 Further,
research has identified that customer engagement improved with curation.51
Overall, the use of AI to curate and recommend products across industries
continues to yield impressive results for companies.

Designing Digital Strategies with AI

Executing an online marketing campaign is an integral part of every

marketing strategy. The possibility of reaching large masses of people with
online campaigns is increasing every day. Pay-per-click advertisements, search
engine optimization, content marketing, email, and social media marketing
are the most practiced strategies of a digital marketing campaign. There is a
possibility that AI will be integrated with digital marketing strategies.
AI can enable companies to expand into new platforms, that have not
been discovered by competitors. Displaying relevant advertisements to the
right people in the right place can become a valuable aspect of a successful
digital marketing strategy. Specifically, using AI tools, companies can accu-
rately ascertain and develop innovative offerings that otherwise may have
been difficult to determine. For instance, in the United Kingdom, L’Oréal
has incorporated AI tools to closely monitor social media regarding what
users say about them. The brand’s CMO Stéphane Bérubé says “By person-
alizing our interactions with consumers we get to understand them and react
accordingly. More than ever before, we will be able to predict and fore-
cast market-wide trends to serve the consumer”.52 Similarly, IBM Watson
is implemented at McCormick Foods to develop new spice variations that
are driven by monitoring customer feedback and social media.53
Natural language processing, linking similar products based on consumer
research, semantic understanding, and relevance instead of optimization
continues to drive the features of an AI-powered offering. Furthermore,
it is possible to apply these aspects to content creation. For instance, AI
enables the development of content-focused advertising as seen in the case of
McCann’s AI tool, wherein the tool aids the creative team to script and film
commercials that resonate closely with the intended audiences.54 Tools such
as Grammarly can predict what the user wants to say and give recommenda-
tions to make the content concise and relevant. There are some areas where
AI is better than humans in content marketing tasks such as writing e-mail
 3 Transformative Marketing with Artificial Intelligence 49

subject lines and suggesting keywords. As a result, companies can design

their digital marketing strategies more efficiently by using AI.
In short, the overarching theme of AI in marketing appears to center
around personalization. Recent research has recognized that AI impacts a
firm’s marketing practices in a way that is significantly different from conven-
tional and contemporary marketing practices. In this new technological
age, it is proposed that personalization can deliver better marketing results
when done using the AI tool through the strategy of curation. Subsequently,
when firms use AI in the context of curation for personalization, signifi-
cant enhancements to branding and customer management practices can be
observed.55 In this regard, Fig. 3.1 presents a framework to understand the
role of AI in delivering personalized offerings via curation.
As illustrated in Fig. 3.1, two factors—(a) how consumers process their
decision choices to arrive at credible decisions, and (b) how consumers store
and use knowledge to make decisions—continue to influence the develop-
ment of firm offerings. Specifically, the richness of information and the need
for consumers to process publicly available information has been captured
in academic research as the paradox of choice and digital cognitive load.56
Collectively, the above-mentioned two factors prepare firms and users for
a new era wherein AI neatly distills and curates wide-selection options for
customers and an abundance of information in a format that is personal-
ized to individual users. Additionally, it is expected that personalization will
continue to drive firm offerings in the future, with the help of AI solutions.

Future of AI in Marketing
AI has made significant developments in the relatively short time that it has
been used in businesses and marketing. More importantly, it has demon-
strated its relevance and practicality to businesses and users in a wide range
of settings. The future of AI is set to build on its current progress and gather
momentum in doing so. Currently, the most important implication of AI in
marketing appears to be building customer engagement by offering person-
alized experiences.57 The automated decision-making of AI reduces manual
guesswork from marketers who try to personalize a customer’s experience.
This presents various marketing opportunities in the areas of content strategy,
campaign strategy, product delivery, sales strategy, sales intent, retargeting,
and more. Specifically, AI aids users in making critical purchase decisions
and accurately pairs the right firm offering(s) with the user’s needs by looking
into the data. This makes AI an influential force in ensuring consumers make
 50

Choice criteria in
decision making
Branding and customer management
• Presence of AI-driven capabilities implications in an AI-driven environment
alternatives • Marketing
• Technological - Brands will become - Regional brands will
• Formation of a
• Operational more important become more
consideration set
- Incorporation of important
• Routinized vs. human-machine - Incremental and Long
abnormal decisions interface is critical adaptive usage of
Wave 3: run
• Formation of a - More customers are human-machine
decision plan Curation of better irrespective of interface is important
information through their loyalty - Creation of profitable
V. Kumar and P. Kotler

personalization loyalty is critical

Digital vs. traditional

Knowledge - Creating brand - Creating brand trust is
brands
organization & experiences will win important
management over customers - Affordable prices
• Revenue generation, • Reliance on data
and not just cost maturity - Dynamic prices would work well
• Organizing is a savings • Alignment to firm would work well - Standardizing service
• Scalable to handle goals - Automating service delivery Short
fundamental human
complex scenarios • Control protocol in an delivery - Solutions-focused run
belief
• Contributes to AI environment - Content-focused advertising to entice
• Development of a

Gains from AI
efficiency • Potential workforce advertising to acquire customers
set of governing • Frees up human time uncertainties new customers
rules for creative pursuits • Largely unexplored
• Are the governing • Application across ethical and privacy
rules relevant (for multiple industries and issues Developed Developing
business contexts economy economy
me/my purpose)? • Integration of inter-
Readiness to AI

disciplinary knowledge

Fig. 3.1 Role of AI in personalized engagement marketing

(Source V. Kumar, Bharath Rajan, Rajkumar Venkatesan, & Jim Lecinski [2019], “Understanding the Role of Artificial Intelligence in
Personalized Engagement Marketing,” California Management Review, 61(4), 135–155)
 3 Transformative Marketing with Artificial Intelligence 51

Fig. 3.2 Popular and emerging applications of AI

(Source Authors’ own)

the right choices within a short time. Figure 3.2 presents an illustration of
popular and emerging applications of AI.
A 2023 McKinsey report identifies that AI and related analytics can unlock
$17.7 trillion of economic value.58 Furthermore, AI-enabled marketing can
unlock significant value for the firm by—aiding in offering better products
and services, delivering higher satisfaction, and transforming the overall busi-
ness operation.59 Particularly, the future of AI in marketing can be viewed in
two ways—(a) through the lens of data-driven marketing, and (b) through
the lens of customer engagement and experience management. Data-driven
marketing with AI begins with collecting data from a multitude of sources
(social media, customer relationship management systems, website analytics).
Upon collecting the data, AI-powered tools can be employed to analyze the
data, identify the patterns and trends to aid decision-making, and uncover
opportunities for optimization. Within data-driven marketing, we discuss
three key areas where AI is expected to play a bigger role—AI in social media,
marketing tools for AI, and content generation using AI.

AI in Social Media

The use of AI in social media is growing.60 Within industries, it is observed

that social media platforms are becoming popular as retail businesses are using
them to strengthen customer relationships. AI in social media helps retail
brands make their promotions more effective. In today’s age of influencers,
52 V. Kumar and P. Kotler

identifying the right influencers that align with a brand’s values and offer-
ings is crucial for successful promotions. AI can offer in-depth insights about
influencers, make predictions about how well they align with the brand, eval-
uate their potential based on their engagement statistics, etc. It can also offer
healthy returns on investments and aid in selecting the most effective content
for each influencer campaign.

Marketing Tools for AI

AI-powered marketing tools are facilitating analysis for marketers, and are
providing insights based on real-time data, at a faster and more accurate level.
Firstly, AI-powered tools can help analyze large amounts of ad targeting and
budget variations, find and segment the audiences, make the ads creative,
test ads, and improve ad performance in the target audiences, etc. AI could
also be used to make predictions—on which language would drive the best
results in the customer segments, on the type of content to create based
on the keywords customers use for searching the products and services, etc.
Additionally, many companies are incorporating AI-powered logo detection
systems to check how often their logos appear on social media networks,
understand the customer sentiments about their brand, and identify areas
they can improve their advertising, among others.

Seamless Integration of AI with Marketing—The New

Marketing Culture

The possibility for AI to benefit the marketing industry remains immense,

and businesses should consider how AI advancements can aid in their
brand’s goals. Companies are integrating AI in personalization, search engine
optimization, content development, consumer decision-making, customer
service, customer relationship management, and more. To ensure the success
of AI implementations, it is vital to align with firm goals. That is, a successful
AI implementation covers the entire organization and leaves no departments
or interested parties behind. Since AI is interactive, a successful implementa-
tion is often one that is interdisciplinary, interactive, and integrative and ties
in all firm operations, rather than in a siloed or even sequential manner. This
would place firms in a better position to overcome the various challenges
that arise in an AI implementation. Further, the identification of defined AI
implementation is vital.61
In summary, the future looks to be firmly trending towards personaliza-
tion, and curated offerings. Firms have taken notice of this trend and are
 3 Transformative Marketing with Artificial Intelligence 53

progressing well along this path. As with many innovations on the rise, the
future of AI is expected to undergo rapid changes. However, a certain facet
of AI is the fundamental shift in the operation of business enterprises. This is
true for companies operating in both developed and developing markets. As
immediate changes, the developed market firms are already incorporating AI-
driven changes, i.e., with specific reference to personalization in (a) delivering
memorable usage encounters for users (e.g., Spotify’s ‘Discover Weekly,’ a
curated personalized playlist based on their listening history),62 (b) real-time
pricing information (e.g., online retailer Jet using AI to dynamically update
pricing in real-time),63 and (c) preprogrammed service delivery instances
(e.g., Uber Eats’ use of AI to optimize delivery times).64
The developing market firms, on the other hand, are focusing on actions
such as (a) establishing a trusted image among users for the brand (e.g.,
mobile financial conversation platform, Juntos tailors personalized text
messages in multiple local Latin American languages to help consumers
achieve their financial goals),65 (b) identifying firm offerings at reasonable
price points (e.g., Amazon India’s AI tool can study holiday purchase data
and advise on the right pricing),66 (c) regimenting service delivery options
that ensure uniformity (e.g., Keeko robot that teaches kindergarten kids has
been in 600 schools in China can bring in a uniform level of instruction),67
and (d) developing commercials that focus on the solution (e.g., Ogilvy
created a nutrition assistant for Nestle in China to help in the development
of personalized meal preparation options).68
In terms of long-term impact, firms are likely to equip themselves better
in delivering AI solutions that encompass all aspects of customer interac-
tion with the firm, instead of being deployed at only specific usage instances
often deployed in the short run. In this regard, research has identified that
developed market firms’ personalization approach is likely to focus on (a)
strengthening their brand value, (b) incorporating human-machine interac-
tion as a core feature, and (c) serving customers across varying profitability
levels (rather than focus only on high-profit customers) to serve as the
cornerstones of their marketing strategy.69
As expected, in the long term the developing market firms are likely to
focus on different aspects from their developed market counterparts. Specif-
ically, it is expected that developing market firms are likely to focus on (a)
building brand value at the regional level (rather than at the national level),
(b) incorporating the human-machine interaction on incremental and adap-
tive levels to supplement existing business practices, and (c) promoting and
ensuring profitable customer loyalty among users.
54 V. Kumar and P. Kotler

Of course, both short and long-term firm initiatives (in developing and
developed markets) would not be possible without building firm capabil-
ities in AI. The AI-driven capabilities are comprised of capabilities about
marketing, technology, and operational elements. The marketing capabilities
(e.g., gathering and using customer-level data to drive firm marketing actions)
impact how AI benefits a firm. The new-age technologies like AI enable firms
to collect, integrate, and analyze large amounts of data at the individual level,
giving firms access to granular insights but the volume, variety, and velocity
of data available to firms could lead to information overload.70 This enables
corporations to identify and extract insights that can aid in ensuring superior
marketing performance.
In terms of technological capabilities, organizations would have to reeval-
uate their technological infrastructure and ascertain how they would align
with the new-age technologies. Further, the effort and time required to learn
how to use and apply new-age technologies can be impacted by the extent to
which new-age technologies are related to the existing knowledge base and
skills of the firm and its employees.71
Finally, operational capabilities enable a firm to perform an activity on
an ongoing basis using more or less the same techniques on the same scale
to support existing products and services for the same customer popula-
tion.72 Further, they are conceptualized as geared towards the operational
functioning of the firm, including both staff and line activities.73
The developments in AI indicate its strong potential in personalizing and
curating offerings while providing valuable information to guide users in their
decision-making process. With the power of robust algorithms, an AI tool
can accommodate user requirements and specifications in developing targeted
suggestions and offerings. Additionally, an AI tool can learn and improve
over time, which further augments the accuracy of suggestions and offerings.
Finally, the output of an AI tool is often designed to be user-friendly and easy
to use. This serves as a strong point for users to adopt such offerings, and in
turn, enjoy memorable usage experiences.

Key Terms and Related Conceptualizations

Ambiguity A phenomenon in natural language that
pertains to understanding a linguistic
structure in multiple ways
Artificial intelligence The science and engineering of making
intelligent machines, especially
intelligent computer programs
(continued)
 3 Transformative Marketing with Artificial Intelligence 55

(continued)
Artificial intelligence (in a marketing context) A system’s ability to interpret external
data correctly, to learn from such data,
and to use those learnings to achieve
specific goals and tasks through
flexible adaptation
Deep neural network A component of artificial neural
networks that contains several hidden
layers of neurons where information is
processed. The more the layer of
neurons, the more connections occur
MEM (Micro-Electric-Mechanic) sensors Sensors that are designed to sense and
measure a diverse range of
environmental and physical parameters
such as motion, temperature, humidity,
and so on

Notes and References

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2. Salesforce Research found that (a) 87% of marketing professionals used
AI for bridging online and offline experiences in 2022, compared to
71% in 2021, (b) 87% of marketing professionals used AI for resolving
customer identity in 2022, compared to 82% in 2021, and (c) 88%
of marketing professionals used AI for automating processes (such as
reporting) in 2022, compared to 83% in 2021 (Salesforce 2023).
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ital/our-insights/the-economic-potential-of-generative-ai-the-next-pro
ductivity-frontier#work-and-productivity.
59. Das, A. C., M. Gomes, I. L. Patidar, G. Phalin, R. Sawhney, &
R. Thomas (2023), “The next frontier of customer engagement:
AI-enabled customer service,” McKinsey, March 27, accessed from
https://www.mckinsey.com/capabilities/operations/our-insights/the-
next-frontier-of-customer-engagement-ai-enabled-customer-service.
60. The global market for AI in social media in 2022 is estimated at
USD 2.2 billion and is projected to reach USD 13.3 billion by 2030,
growing at a CAGR of 25.1% (Research and Markets 2023). The
fastest-growing geographic regions are the USA, China, Japan, and
Canada.
61. A Deloitte global survey found that 35% of global companies in the
developed markets already have a comprehensive, companywide AI
strategy, with others planning to have such a strategy soon (Loucks,
J., S. Hupfer, D. Jarvis, & T. Murphy [2019], “Future in the balance?
How countries are pursuing an AI advantage,” Deloitte Insights,
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May, accessed from https://www2.deloitte.com/content/dam/Deloitte/

lu/Documents/public-sector/lu-global-ai-survey.pdf). This shows that
it is important to investigate and have ready the implementation
specifics for a successful AI implementation.
62. Pasick, A. (2015), “The magic that makes Spotify’s Discover
Weekly playlists so damn good,” Quartz, December 21, accessed
from https://qz.com/571007/the-magic-that-makes-spotifys-discover-
weekly-playlists-so-damn-good/.
63. Intelligence Node (2018), “3 retail leaders using big data &
AI to drive efficiency,” Intelligence Node, September 27, 2018,
accessed from http://www.intelligencenode.com/blog/3-retail-leaders-
using-big-data-ai-to-drive-efficiency/.
64. Williams, R. (2018), “Uber Eats harnesses AI for $6B in annual
bookings,” Mobile Marketer, October 3, accessed from https://www.
mobilemarketer.com/news/uber-eats-harnesses-ai-for-6b-in-annual-
bookings/538724/.
65. Estopace, E. (2018), “Beyond FIGS: How Juntos Localizes into
Bemba, Swahili, Tagalog, Arabic and more,” Slator, April 2, accessed
from https://slator.com/features/localization-a-force-multiplier-in-jun
tos-financial-conversation-platform/.
66. Baruah, A. (2018), “Artificial intelligence at India’s top eCommerce
firms—Use CASes from Flipkart, Myntra, and Amazon India,”
techemergence, February 1, accessed from https://www.techemergence.
com/artificial-intelligence-at-indias-top-ecommerce-firms-use-caes-
from-flipkart-myntra-and-amazon-india/.
67. Low, A. (2018), “China is using adorable robot teachers in kinder-
gartens,” cnet, August 29, accessed from https://www.cnet.com/news/
china-is-using-adorable-robot-teachers-in-kindergartens/.
68. Lyall, N. (2018), “Where does AI fit into the future of advertising and
marketing?” Ogilvy, September 14, accessed from https://www.ogilvy.
com/feed/where-does-ai-fit-into-the-future-of-advertising-and-market
ing/.
69. Kumar, V., B. Rajan, R. Venkatesan, & J. Lecinski (2019), “Under-
standing the role of artificial intelligence in personalized engagement
marketing,” California Management Review, 61(4), 135–155.
70. Day, G. S. (2011), “Closing the marketing capabilities gap,” Journal of
Marketing, 75 (4), 183–195; Martin, J. E. & M. Jeanne (2004), “The
concept of information overload: A review of literature from organiza-
tion science, accounting, marketing, MIS, and related disciplines,” The
Information Society, 20 (5), 325–344.
 3 Transformative Marketing with Artificial Intelligence 63

71. Cohen, W. M. & D. A. Levinthal (2000), “Absorptive capacity: A

new perspective on learning and innovation,” Administrative Science
Quarterly, 35 (1), 128–152.
72. Helfat, C. E. & S. G. Winter (2011), “Untangling dynamic and opera-
tional capabilities: Strategy for the (N) ever-changing world,” Strategic
Management Journal , 32(11), 1243–1250.
73. Cepeda, G. & D. Vera (2007), “Dynamic capabilities and operational
capabilities: A knowledge management perspective,” Journal of Business
Research, 60 (5), 426–437.
 4
Transformative Marketing with Generative
Artificial Intelligence

Overview
Generative Artificial Intelligence, Generative AI (or GAI), is a form of AI that
creates new content in text, imagery, audio, video, or synthetic data based
on what it learned from the existing content. The process of learning from
the existing content is training, which results in creating a statistical model.
Generative AI uses the statistical model to predict an expected response, thus
generating new content. The world today has come a long way since tradi-
tional programming, where one had to write hard code the rules for the
model. Since then, there has been the advent of neural networks, which
consist of many layers of neurons that help them process more complex
patterns and provide outputs. Generative AI is a subset of deep learning,
that uses supervised, unsupervised, and semi-supervised machine learning
methods to generate new data instances based on the learned probability
distribution of existing data. The output is natural language like speech, text,
image, audio, and video. Interestingly, previous models were not flexible with
the input type, whereas GAI takes prompts in the form of text, speech, etc.
Relatively new to the marketing landscape, GAI’s market is expected to
rise significantly, from 14 billion US dollars in 2020 to nearly 900 billion US
dollars in 2023 and more than 1.3 trillion US dollars in 2032.1 This is due
to an explosion of generative AI tools in recent years such as Bard by Google,
ChatGPT by OpenAI, and Midjourney by Midjourney, Inc., among others.
GAI is receiving increasing attention from all business industries and func-
tions, with nearly all industries around the world having tried a generative AI

© The Author(s), under exclusive license to Springer Nature 65

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_4
66 V. Kumar and P. Kotler

tool at least once in 2023.2 Table 4.1 presents how GAI is used by industry
worldwide.
The employment of GAI tools has become increasingly pervasive in various
business functions. As is the case with AI, the business functions that
exhibit the most common use of GAI are marketing and sales, product,
and service development, and service operations, which include customer
care and back-office support. For instance, within the marketing function,
the common uses of GAI include developing copies for emails and social
media messages, images for social media and websites, scripts for chatbots and
marketing materials, creating early drafts of marketing documents, messaging
for personalized marketing campaigns, and summarizing text documents,
among others.3 As the adoption of newer GAI tools gains momentum,
reports indicate that these same business functions exhibit the highest usage
of these tools.

Table 4.1 Representation of how GAI is used by industry worldwide

Have
Regularly tried
used for Regularly at
Regularly work and used least No Don’t
used for outside of outside of once exposure know
Characteristic work (%) work (%) work (%) (%) (%) (%)
Advanced 5 11 16 47 15 5
industries
Business, 7 16 13 41 21 2
legal, and
professional
Consumer 7 11 12 40 26 4
goods/retail
Energy and 6 8 15 50 19 3
materials
Financial 8 16 18 41 14 4
services
Healthcare, 6 10 17 44 15 7
pharma, and
medical
products
Technology, 14 19 19 37 9 3
media, and
telecom
Source McKinsey & Company. (August 1, 2023). Share of respondents using generative
AI at work or outside of work in 2023, by industry [Graph]. In Statista. Retrieved
October 10, 2023, from https://www.statista.com/statistics/1407402/generative-ai-use-
by-industry/.
 4 Transformative Marketing with Generative Artificial … 67

The above trends indicate that the rise of GAI has undoubtedly imprinted
its transformative footprint in the evolving landscape of organizational
functions. Among the numerous domains witnessing this transformation,
marketing emerges as a standout beneficiary of this cutting-edge innovation.
This chapter will investigate the multifaceted effects of GAI on marketing
paradigms.
This chapter is organized in the following manner. First, a brief history
of the origin of GAI is presented, followed by a definition of GAI (from a
marketing standpoint), and a discussion of related processes that are linked
to GAI. In this regard, some practical applications of such AI processes
are presented. Next, some marketing applications of GAI focusing on
understanding customer needs, revisiting firm capabilities to integrate GAI,
designing GAI-focused marketing mix strategies, driving customer engage-
ment through GAI, and designing digital strategies with GAI are discussed.
Finally, the future of GAI for the marketing industry is envisioned through
specific marketing actions and initiatives that show a lot of promise.

Origin, Definition, and Classification

of Generative AI
Origin

Generative AI finds its roots in the broad areas of AI and machine learning
(ML). Whereas AI and ML have been in existence since the mid-20th
century, GAI began its journey in the 1960s. An early development of a
GAI tool was the ELIZA chatbot which could simulate conversations with
humans based on prior text received. The introduction of Generative Adver-
sarial Networks (GANs) by Ian Goodfellow and colleagues in 2014 was a
watershed moment in the evolution of generative models. This novel frame-
work pits two neural networks against each other, one to generate data and
the other to distinguish between generated and real data, resulting in highly
realistic outputs. Since then, the field has grown to include a wide range
of approaches and models that contribute to the generative aspect of AI.4
Subsequent advancements in computing power and data availability led to
the development of GAI models such as Markov chains and neural networks.
During the late 1990s and early 2000s, with the availability of diverse
datasets, improved computing processes, and an increased body of knowl-
edge, GAI saw developments such as generative adversarial networks (GANs)
that can be used to generate realistic images, text, and other forms of content.
68 V. Kumar and P. Kotler

More recently, additional research and development in this area have led to
the development of richer and more advanced GAI tools such as DALL-E,
and GPT (Generative Pre-trained Transformer) models. These models can
generate incredibly realistic and creative content, which has led to a wide
range of new applications for GAI.
In recent academic discourse, the rise of GAI has been recognized as a
pioneering catalyst for a comprehensive embracement of AI within corporate
spheres.5,6 Marketing emerges as a particularly favored beneficiary as organi-
zations embrace this cutting-edge innovation across all functional terrains.7
One could argue, with substantial evidence, that the brilliance of GAI truly
shines in industries such as marketing and advertising, where impeccable
content becomes an essential bridge between corporations and their various
stakeholders.
Additionally, literature has established that digital intervention enables
firms to curate communications, ultimately enriching the customer journey.8
Such enhancements are precursors to improved brand interactions9 and asso-
ciated increases in allegiance and institutional performance. Anisin10 offers a
compelling argument contending that GAI’s impact dwarfs that of its digital
predecessors, owing primarily to its ability to simulate humanlike content,
providing marketers with a plethora of powerful tools for content refinement.
To marketers, GAI is more than just an efficiency tool; it is a transfor-
mative ally.11 Beyond mere financial prudence and accelerated tasks, the
wonders of GAI enable brands to transcend traditional boundaries, providing
unparalleled personalization unfathomable by manual endeavors alone. With
its ability to communicate dynamically, GAI provides a combination of
tailored visuals, text, and predictive insights, paving the way for cost-effective,
moment-specific customization.

Definition

Generative AI is a subset of artificial intelligence algorithms and models that

can generate new content that is like but not identical to the data on which
they were trained. These algorithms do more than just analyze input data;
they can also generate entirely new data instances—whether text, images,
sound, or even video—that can be difficult to distinguish from genuine
human-generated data. The term “generative” refers to the creation of some-
thing new rather than the processing or analysis of existing data. GAI has
been defined on similar lines by various organizations (see Table 4.2).
We asked ChatGPT to define GAI, it provided the following definition—
“Generative AI, short for Generative Artificial Intelligence, refers to a subset
 4 Transformative Marketing with Generative Artificial … 69

Table 4.2 Definition of Generative AI offered by various organizations

Organization Definition
Gartner “…AI techniques that learn a
representation of artifacts from data,
and use it to generate brand-new,
unique artifacts that resemble but
don’t repeat the original data.”12
IBM “…deep-learning models that can
generate high-quality text, images,
and other content based on the data
they were trained on.”13
Marketing Accountability Standards “…broad category of artificial
Board (MASB) intelligence (AI) that is meant to
generate something new based on
preexisting materials and
user-defined parameters. The output
of generative AI can be in the form
of new text, images, audio, video,
and combinations of these.”14
World Economic Forum “…a category of AI algorithms that
generate new outputs based on the
data they have been trained on.”15

of artificial intelligence (AI) techniques and models that can generate new
data that is like, or in some cases indistinguishable from, data that could
have been created by humans. Generative AI models are designed to under-
stand patterns and structures within existing data and then generate new data
samples that adhere to those patterns. These models can produce various
types of content, including text, images, audio, and more.”
Despite the variations in the definitions, all the definitions seem to agree
that GAI is a type of AI that can create new things. Further, GAI is a powerful
tool with a wide range of potential applications, and based on subsequent
advancements in technology more innovative and exciting uses for GAI can
emerge in the future.

Classification

Generative AI is classified broadly based on the type of content it generates

and the methods it employs to generate this content. Table 4.3 provides some
examples of classifications.
Based on the classification of GAI, different types of GAI models vary on
the inputs and outputs of the model. We discuss four broad types of GAI
models here. First, text-to-image models are trained on a large set of images
70 V. Kumar and P. Kotler

Table 4.3 Classification of GAI

Classification Meaning
By type of content
Text Models such as the GPT (Generative
Pretrained Transformer) series, can
write essays, code, poetry, or
translate languages
Images GANs (Generative Adversarial
Networks) are well-known for
producing realistic images ranging
from human faces to art
Audio Models that can generate music,
mimic voices, or create sound effects
are known as audio models
Video AI can create video clips or modify
existing footage to create new
scenes or effects
By methodology
Generative Adversarial Networks (GANs) Composed of two networks, a
generator, and a discriminator, that
improve through competition with
one another
Variational Autoencoders (VAEs) Generate data using a probabilistic
approach by learning a latent space
Transformer Models By leveraging attention mechanisms,
these models are especially effective
at generating coherent and
contextually relevant text sequences
Autoregressive Models Learn to generate data one piece at
a time and predict the next item in
a sequence
By application
Content Creation For the creation of creative design,
literature, and digital art
Data Augmentation When data is scarce or imbalanced,
data augmentation is used to
improve datasets in machine
learning
Simulation and Modeling Simulation and modeling are
techniques for creating realistic
environments for training and
research
Source Authors’ compilation
 4 Transformative Marketing with Generative Artificial … 71

Table 4.4 Types of GAI models

Generative AI models Applications Examples
Text-to-image • Image generation • Stable Diffusion
• Image editing • LimeWire
• Jasper
• Canva
Text-to-text • Translation • Quillbot
• Content editing/Writing • GPT-3
• Byword
• HiveMind
Text-to-video, text-to-3D • Video generation • Synthesys
• Video editing • Synthesia
• Game assets • InVideo
• Colossyan
Text-to-task • Software agents • Taskade
• Virtual assistants • TextCortex
• Automation • Otter
• Alexa
Source Authors’ compilation

and each image is captioned with a short text description. These models
are applied for image generation and image editing. Open AI’s Dall-E is
an example of the text-to-image model. Second, text-to-text models take a
natural language input and produce a text output. The models are trained
to learn the mapping between a pair of texts. Third, text-to-video models
generate a video representation from a text input, where the input can range
from a single sentence to a full script. Relatedly, text-to-3D models are models
that create three-dimensional objects that correspond to a user’s text descrip-
tion. Finally, text-to-task models are trained to perform a specific task or
action based on text input. The task could range from answering a ques-
tion, performing a search, making a prediction, etc. The applications of these
models are presented in Table 4.4.
As new models and applications are developed, generative AI’s classifica-
tion is likely to become more nuanced. It represents not only a technical
accomplishment but also a paradigm shift in how we think about machines’
creative capacities and their potential to emulate—and sometimes even
enhance—human creativity.

Some Commercial Applications of GAI

The commercial applications of GAI tools find their origins with the
commencement of Open AI. Open AI is an AI research and deployment
72 V. Kumar and P. Kotler

company that focuses on ensuring that AGI, or artificial general intelli-

gence (i.e., systems that are generally smarter than humans), benefits all of
humanity. Founded in 2015 by notable entrepreneurs from the technology
industry, Open AI is involved in building safe and beneficial AGI and has
been transforming work and creativity with AI. Open AI offers a variety
of models, such as ChatGPT (Chat Generative Pre-Trained Transformer),
Dall-E, Whisper, etc. ChatGPT is an AI chatbot technology that can process
natural human language and generate a response. It interacts with the users
in a conversational way—a dialogue format that makes it possible to answer
follow-up questions, admit mistakes, and reject inappropriate requests.
OpenAI has been making significant advancements in natural language
processing technology.16 OpenAI is currently working on GPT-4, which is
based on a model trained on 1.7 trillion parameters. GPT-4 is expected
to have advanced reasoning, complex instruction, and enhanced creativity.
It will also be able to adapt to user intention and requests to reduce the
likelihood of harmful output.
Another innovation from Open AI is DALL-E, which is a text-to-image
generative AI model. DALL-E allows users to create images by giving text-
to-graphic prompts. It is a neural network that can produce new and often
surreal images in different styles as per the user’s prompts. The name ‘DALL-
E’ is a combination of Spanish surreal artist Salvador Dali and the fictional
robot Wall-E from Disney. The technology uses deep learning models along-
side GPT-3 to understand natural language prompts and generate new
images. Initially, DALL-E generated images using Discreet Variational Auto-
Encode (dVAE). However, DALL-E 2 improved on the methods used and
was able to generate more high-end, photorealistic images.17 DALL-E 3 is
built on ChatGPT and is currently available to ChatGPT plus subscribers.
Google AI developed its large language model (LLM) chatbot, Bard. This
model is based on the Language Model for Dialogue Applications (LaMDA),
an AI language model that can allow users to engage in conversational AI.
This model is trained on a massive dataset of text and code—it can generate
text, translate languages, and write different kinds of creative content. Bard’s
first version, launched in February 2023, uses a lighter model of LaMDA,
requiring less computing power to handle more concurrent users. In addi-
tion to LaMDA, Bard extracts data from the web to provide its users with
various services, including creating different types of content, summarizing
texts, and translating between multiple languages. All of this is offered in
a minimalist interface through a text-based chat. Bard possesses a remark-
able ability to participate in multi-turn conversations, in which the AI can
sustain a consistent topic and persona throughout multiple interactions with
 4 Transformative Marketing with Generative Artificial … 73

a human user. This quality makes Bard especially valuable for applications
like chatbots and virtual assistants. Some of the popular uses of Bard include
content writing, creative writing, marketing material copy generation, and
student writing, among others. Table 4.5 provides a comparison between the
above-mentioned three GAI tools.
To conclude the overview of GAI, the following three vignettes present
the evolution of GAI tools that are influencing many aspects of business and
society.

• Healthcare: Developing new pharmaceutical products is time-intensive and

costly. The entire process (from ideation to launch) could take several

Table 4.5 A comparison of the popular GAI models—ChatGPT, DALL-E, & Bard
ChatGPT DALL-E Bard
What is it? AI-powered AI model that can Large language
chatbot that can create realistic images model chatbot
engage in from text descriptions. developed by
humanlike It can create realistic Google AI. It can
conversations images from text engage in
with users descriptions humanlike
conversations
with users
How does it Uses natural Trained on a massive Uses more recent
work? language dataset of text and data
processing and images, it can sources—includes
machine learning generate images in a information from
to understand variety of the internet,
and respond to styles—realistic scientific papers,
user queries photographs, mathematical
paintings, and expressions, and
cartoons source code that
other tools do not
Popular uses Customer support, Art, design, education, Research,
personal and entertainment education,
assistance, creative writing,
education, etc. customer service,
etc.
Ideal for Generating Generating images of Answering factual
creative text things that do not questions and
formats (poems, exist in the real providing
codes, scripts) world. It can generate up-to-date
realistic images that information to
are difficult to user queries
distinguish from real
photographs
Source Authors’ compilation
74 V. Kumar and P. Kotler

years with firms incurring an average investment of USD 1.5 billion.18

With Generative AI, firms can automate time-intensive tasks such as
drafting clinical trial communications, translating documents into different
languages for different markets, and so on. For instance, Bayer has part-
nered with Google Cloud’s Vertex AI and Med-PaLM 2 to enhance their
clinical trial process. Moreover, the company is also using Google Cloud’s
Tensor Processing Units (TPUs) to perform high volumes of calculations
that can deliver new insights into the drug discovery process.19 Simi-
larly, Microsoft is making a big push with GAI-based tools that can help
healthcare organizations deliver better healthcare. For instance, Microsoft
is developing the Azure AI Health Bot that can pull information from a
health organization’s internal data and integrate data from external sources
to help treat specific diseases and identify internal protocols and processes.
This bot can also be used by patients to ask clarifying questions about their
symptoms and medical terms they encounter. The company has additional
GAI-based initiatives that focus on all stakeholders in the healthcare system
such as patients, doctors, nurses, administrators, clinicians, and medical
specialists, among others.20
• Fashion: The partnership between designers and GAI deals with leveraging
AI’s capability to process datasets aligned to the designer’s imagination.21
The technology holds a lot of promise to be integrated across the industry
(e.g., merchandising, product development, distribution, pricing), where
GAI could enrich product ideation. Leveraging the technology’s ability to
mine through data, understand past product lines, and gain inspirational
imagery and style could lead to augmenting the professionals’ ideas.
• Education: A UNESCO global survey of over 450 schools and universi-
ties found that fewer than 10% have developed institutional policies and/
or formal guidance concerning the use of generative AI applications. This
is a telling finding considering the rapid gains made by GAI in many
aspects of human lives. In this regard, the UNESCO report contends that
education is a fundamentally human experience that relies on social inter-
action to be effective and impactful. Academic studies have also cautioned
about the challenges that this tool throws to educators while identifying
the opportunities that GAI can serve.22,23 By promoting greater awareness
of these applications, educators can effectively incorporate them into class-
room instruction. Additionally, guiding students in discussing the benefits
and drawbacks of AI can lead to a more comprehensive integration of this
technology into education. Ultimately, this approach would enable educa-
tional institutions to develop a deeper understanding of GAI’s capabilities
 4 Transformative Marketing with Generative Artificial … 75

and limitations, which can help them navigate a future where GAI is likely
to play an increasingly dominant role.

Generative AI in the Marketing 5.0 World

Marketing in the realm of GAI has revolutionized the way businesses promote
their products and services. By harnessing the power of AI, marketers can
create dynamic and engaging content that resonates with their target audi-
ence. This cutting-edge technology enables marketers to automate various
aspects of their campaigns, from content creation to customer segmenta-
tion. By leveraging GAI, businesses can streamline their marketing efforts,
saving time and resources while maximizing their reach. Furthermore, GAI
algorithms can analyze vast amounts of data to identify patterns and trends,
providing marketers with valuable insights into consumer behavior and pref-
erences. Expanding on the Marketing 5.0 concept discussed in Chapter 2,
this section presents how GAI operates in the Marketing 5.0 world. Particu-
larly, this section discusses five examples of where GAI is applied through the
lens of Marketing 5.0 and establishes how such actions can also bode well for
humanity.

Data-Driven Marketing Using GAI

The emergence of GAI has made the marketing function a highly sought-
after area due to its capacity to interact with customers, customize content,
and decrease expenses and intricacies. Marketers are now adopting a data-
driven approach to utilize this technology in customer service, with the aim
of personalizing customer experience, increasing sales and retention, and
providing support to frontline staff. Particularly, GAI enables companies to
analyze user data, purchase history, browsing behavior, and demographic
information to create customized messages that resonate with individuals.
This approach allows for high levels of personalization, which can help
build trust and rapport with customers over time. Furthermore, companies
are leveraging generative AI to produce content that is well-structured and
optimized for search engines, improving their online visibility and reach.24
Consider the case of Coca-Cola’s GAI initiative. In March 2023, Coca-
Cola launched a GAI initiative that provided fans with the opportunity to
explore numerous branded elements. These elements included the iconic
Coca-Cola contour bottle, the Spencerian script logo, and various symbols
76 V. Kumar and P. Kotler

from Coke’s advertising history, such as the Coca-Cola Santa Claus and Polar
Bear. This initiative served as a platform for AI-powered experimentation and
creative exploration, allowing fans to engage with these elements in new and
innovative ways. The fan creations led to the designing of out-of-home digital
art meant for billboards in New York and London. The company reported
that the GAI campaign saw nearly 120,000 image creations within 11 days,
all without utilizing paid media, with users spending an average of eight
minutes on the platform. The success of this initiative has provided confi-
dence to the company to roll out more such initiatives.25 Through granting
access to its proprietary data and brand assets, Coca-Cola facilitated an envi-
ronment where participants could generate impactful results and establish a
reference point for future generations of AI developers.

Predictive Marketing Using GAI

Predictive marketing using generative AI involves using algorithms to analyze

data from a variety of sources, including social media, search engines, and
customer behavior. This data is then used to create models that can predict
future trends and consumer behavior. These models can be used to create
targeted marketing campaigns that are more likely to be successful, as they
are based on data-driven insights rather than guesswork. It can also help iden-
tify trends, forecast behavior, predict any impending challenges, and devise
solutions for them.
Consider the case of Jet Blue. The US-based airline has collaborated with
ASAPP, a technology vendor, to adopt a pre-packaged generative AI solution
that enhances and automates its chat channel operations. This implementa-
tion has significantly benefited the airline’s contact center, enabling them to
save an average of 280 seconds per chat. Consequently, this translates to a
remarkable 73,000 hours of agent time saved in just one quarter. With this
newfound efficiency, agents now have more availability to assist customers
with nuanced issues, ultimately improving the overall customer service expe-
rience.26 In the future, this platform will possess the ability to learn from
customer sentiment and the frequency of inquiries to provide decision-
makers with practical recommendations concerning customer-facing actions
and processes.
 4 Transformative Marketing with Generative Artificial … 77

Contextual Marketing Using GAI

Contextual marketing is the activity of identifying and profiling as well as

providing customers with personalized interactions by utilizing technology
interfaces in the physical space. It is the backbone that allows marketers
to perform one-to-one marketing in real-time, depending on the customer
context. By understanding the context in which consumers engage with
their brand, businesses can create highly personalized and timely marketing
campaigns. Whether it is delivering targeted ads based on browsing history
or sending personalized recommendations based on previous purchases, GAI
empowers marketers to deliver seamless and tailored experience to each
customer.
Consider the area of contextual advertising. Nowadays, advertising and
media companies are developing context-driven marketing messages that
speak directly to the consumer’s currently exhibited tastes and preferences.
For instance, Instreamatic, an audio marketing platform, has recently intro-
duced a new product for connected TV.27 This innovative offering gener-
ates various audio versions for a single creative while keeping the visuals
unchanged. Leveraging the power of AI, Instreamatic replaces specific details
in the voiceover, such as mentioning the viewer’s current streaming service
or TV show, as well as highlighting promotional codes, products, or deals
available at specific store locations. This dynamic approach enhances the
personalized experience for viewers and enables advertisers to tailor their
messages more effectively. The aim is to swiftly produce numerous person-
alized versions of the same advertisement, potentially reaching hundreds or
even thousands of variations within seconds.
In this regard, contextual AI is quickly gaining popularity among adver-
tisers and is often seen as an answer to online privacy, intrusiveness, and
irrelevant ads. Seedtag’s contextual AI platform, Lin, empowers brands and
agencies to develop customized creative content that aligns with the context
of the surrounding page-level content.28 This innovative solution enables
advertisers to optimize their ads to seamlessly integrate with the online
environment. By leveraging deep learning, computer vision, and NLP capa-
bilities, Lin comprehends the desired contexts for the client’s ad campaign
and generates prompts to enhance the original creative, resulting in a more
effective outcome. With the ability to create new creatives based on audience
insights and campaign objectives, this AI generative platform offers endless
possibilities while saving valuable time and resources.
78 V. Kumar and P. Kotler

Augmented Marketing Using GAI

Augmented Marketing, powered by GAI, has opened new possibilities for

marketers to enhance their campaigns. With the ability to analyze vast
amounts of data and consumer behavior patterns, generative AI algorithms
can generate creative and compelling content that captures the attention of
potential customers. This technology enables marketers to create personalized
advertisements, product recommendations, and even interactive experiences
that cater to individual preferences and interests. Moreover, with the avail-
ability of augmented reality (AR) and virtual reality (VR) devices, the
integration of GAI with such devices is expected to bring unique personal
experiences to users.
Consider the case of social anxiety. Many people experience awkwardness
or even exhibit social anxiety when engaging in highly involved conversa-
tions such as in social events, public speaking engagements, or preparing for
job interviews, among others. RizzGPT is an innovative augmented reality
eyepiece developed by students at Stanford University to address this issue.29
This eyewear device combines AI and augmented reality to assist individ-
uals during difficult conversations. The eyepiece is equipped with a camera,
a microphone, and an internal projector screen that displays words in front
of the user’s eye. During a conversation, RizzGPT uses its microphone to
monitor the dialogue and transforms it into text. This text is then sent via
GPT-4 and Whisper to generate appropriate responses based on the context
of the questions asked. The response is displayed on the small monocle screen
of the AR glasses after a short delay.30
This technology has the potential to revolutionize the way we commu-
nicate and interact with others. It can help individuals who struggle with
social anxiety or have difficulty understanding others during conversations.
The development of RizzGPT is a significant step forward in the field of
augmented reality and AI, and it will be exciting to see how this technology
evolves in the future. Bryan Chiang, the developer of RizzGPT, believes
that advancements in technology and hardware can lead to more intelligent
responses in a shorter amount of time. He cites examples of how the camera
can be used to identify friends and provide relevant information or even help
with ordering food at a restaurant by reading the menu and using GAI to
suggest the best option. Chiang also mentions that there are many other
possibilities for this technology and that the next generation will be even
more impressive.31
 4 Transformative Marketing with Generative Artificial … 79

Agile Marketing Using GAI

The rise of generative AI in marketing has led to an increase in GAI initia-

tives and budgets across various industries. However, as customer demands
become more complex, companies must also possess organizational agility to
adapt to changing market conditions. This requires the use of decentralized,
cross-functional teams to quickly conceptualize, design, develop, and validate
products and marketing campaigns. The integration of GAI into the agile
marketing process can aid in achieving this goal.
For instance, Mitsui Chemicals, Inc. has successfully utilized GAI and
IBM Watson to enhance its new application discovery process. By inputting
over 5 million points of external big data, including patents, news, and SNS,
into IBM Watson, Mitsui Chemicals has been able to efficiently analyze this
data alongside a specific dictionary for their products. This has resulted in a
significant increase in the volume of their unique dictionary, which has grown
by approximately ten times.32
In addition to this, the efficiency of extracting new applications has also
been improved by three times, allowing Mitsui Chemicals to discover new
applications for their products that exceed human preconceptions and current
knowledge. By utilizing the expertise of their specialists in the sales and busi-
ness domain, Mitsui Chemicals has been able to analyze this big data in a way
that is both agile and accurate, leading to the discovery of new applications
that may have otherwise gone unnoticed.
One example of this is the discovery of a need for antifungal products in
the local railway system, which was identified through SNS analysis. This led
to sales activities for Mitsui Chemicals’ antifungal products, demonstrating
the real-world impact of their new application discovery process. Overall,
Mitsui Chemicals’ use of generative AI and IBM Watson has expanded
the number of new applications discovered by approximately two times,
highlighting the significant benefits of this innovative approach.33

Current Generative AI Applications in Marketing

Expanding the role of GAI beyond the marketing function, we can see that
GAI is poised to transform roles and boost performance across business
functions—sales and marketing, customer operations, and software develop-
ment. In a worldwide survey by McKinsey, it was found that the top five
professions that showed the most automation potential with and without
GAI were educator and workforce training, business and legal professionals,
80 V. Kumar and P. Kotler

STEM professionals, community services, and creatives and arts manage-

ment.34 Table 4.6 provides the automation potential of GAI over non-GAI,
by profession.
GAI aids marketers in various customer-related tasks and has the poten-
tial to be a part of the creative processes in marketing. For instance, in
May 2023, WPP announced a partnership with Nvidia to transform the
way brands create content. Through this partnership, they aim to integrate
generative AI at a bigger and more tailored scale—enabling creative teams
to produce high-quality content faster, with greater efficiency, and in full
alignment with the client’s brand.35 Several studies have identified GAI as a
promising technology that not only presents value-creating opportunities in
marketing but also holds important implications for enhancing human lives.
This section presents five specific application areas where GAI continues to
help companies in developing marketing initiatives.

Table 4.6 Top 10 professions that show the most automation potential for GAI
Automation potential
Automation potential without Generative AI Differential
Profession with Generative AI (%) (%) impact (%)
Educator and 54 15 39
workforce
training
Business and 62 32 30
legal
professionals
STEM 57 28 29
professionals
Community 65 39 26
services
Creatives and 53 28 25
arts
management
Office support 87 66 21
Managers 44 27 17
Health 43 29 14
professionals
Customer 57 45 12
service and
sales
Property 38 29 9
maintenance
Source McKinsey & Company. (June 14, 2023). Automation potential with and
without generative artificial intelligence (AI) in the United States in 2023, by profes-
sion [Graph]. In Statista. Retrieved October 17, 2023, from https://www.statista.com/
statistics/1411571/job-automation-potential-generative-ai/.
 4 Transformative Marketing with Generative Artificial … 81

Understanding Customer Needs to Deploy GAI

Understanding customer needs using generative AI involves leveraging artifi-

cial intelligence techniques to extract valuable insights and information from
customer data. Generative AI can play a significant role in this process by
creating data, content, or responses that mimic humanlike creativity and
understanding. Some of the customer-facing areas that can benefit from the
use of GAI include the following:

• Analyzing Customer Feedback. Generative AI can be used to analyze

customer feedback from surveys, social media, and other sources to identify
common themes and trends. This information can then be used to under-
stand customer needs and pain points. For instance, Amazon uses GAI to
make it easy for customers to assess a product’s review on Amazon’s website.
Using GAI, Amazon is testing an AI feature (limited to the US customers,
as of this writing) to provide a short paragraph on the product detail page
that highlights the product features and customer sentiment frequently
mentioned across written reviews to help customers determine quickly
whether a product is right for them. Figure 4.1 illustrates the concept
currently being tested by Amazon. Such a feature will help customers better
process the product feedback shared by other users, thereby ensuring the
productive use of the customer review feature.

Fig. 4.1 Amazon’s customer review highlights feature developed by GAI

(Source Amazon.com, accessed from https://www.aboutamazon.com/news/amazon-ai/
amazon-improves-customer-reviews-with-generative-ai)
82 V. Kumar and P. Kotler

• Predicting Customer Behavior . Generative AI can be used to predict

customer behavior, such as which products they are likely to buy or when
they are likely to churn. This information can be used to develop targeted
marketing campaigns and improve customer retention. For instance, Stitch
Fix is experimenting with GPT-3 and DALL-E 2 to help stylists quickly
and accurately interpret reams of customer feedback and predict products
that customers would be likelier to purchase. The GAI tool could analyze a
customer’s feedback, including email requests, product ratings, and online
posts. Based on frequently used customer comments for a clothing item
(for example, “good fit,” “cool style,” etc.) DALL-E could generate images
of similar clothing items that the customer would likely want to purchase.
The stylist could then find similar items in Stitch Fix’s inventory and
recommend them to that customer.36
• Creating Personalized Experiences. Generative AI can be used to create
personalized experiences for customers, such as recommending products
or services that they are likely to be interested in. This can help to improve
customer satisfaction and loyalty. For instance, Morgan Stanley is devel-
oping a state-of-the-art AI-powered assistant that will revolutionize the
way wealth managers navigate their extensive internal knowledge base.
This next-generation assistant, built using the advanced GPT-4 technology,
aims to provide quick and accurate responses to the complex queries
of tens of thousands of wealth managers. By leveraging an innovative
combination of search and content creation features, this GAI model will
allow wealth managers to seamlessly access and tailor information for each
client’s unique needs, ultimately personalizing the experience of the service
provided.37

Generative AI can help businesses gain valuable insights into customer

needs. These insights can be used to tailor products, services, and customer
interactions more effectively. However, it is crucial to use these insights ethi-
cally and responsibly, while also respecting customer privacy. Building trust
in the process is essential.

Revisiting Firm Capabilities to Integrate GAI

Companies considering including GAI should revisit their capabilities that

involve building the necessary skills, processes, and infrastructure within
the organization. When integrating GAI into their capabilities, firms should
consider the following aspects: (a) comprehending the potential applications
of GAI for their business, (b) assembling a team with the necessary skills and
 4 Transformative Marketing with Generative Artificial … 83

expertise, (c) investing in the required infrastructure and tools, (d) collabo-
rating with external experts, and (e) fostering a culture of experimentation
and innovation.
When Levi Strauss embarked on integrating GAI into their business, they
addressed the above five points. In 2021, the fashion clothing manufacturer
took a step towards improving its employees’ technological knowledge by
launching a data science boot camp. The program aimed to train workers
with limited technical know-how on how to use NATs in the company’s
design process. Upon completing the training, employees were equipped to
create new AI tools that were relevant to their work. The company’s objec-
tive with this program was to increase the diversity of employees with tech
knowledge. This way, the company can uncover problems that employees
from traditional technology backgrounds might otherwise miss. The program
also helped different teams with different specializations, such as design
and engineering teams, communicate effectively and find common ground.
Additionally, Levi’s also found that the program has improved employee
retention.38
While GAI has the potential to be a disruptive technology, organizations
need a clear strategy that enables them to move from experimentation to
industrialization. To get the value organizations want from emerging tech-
nologies, they need a team to organize their responses to the emergence of
GAI. Changing customer demands and market competition are among the
largest factors influencing the need for GAI. When companies leverage the
first-mover advantage, they can establish a competitive advantage and drive
innovation at levels greater than ever seen.

Designing Marketing Mix Strategies with GAI

In a volatile environment where consumer preferences and demands change

constantly, it can be challenging to determine a marketing strategy to execute.
Today, AI allows businesses to examine these instant changes and adapt to
the fast-paced environment. Breaking down AI’s role in the marketing mix
provides interesting insights into the extent to which it permeated through
the organization.
Product: GAI can be a valuable tool for product development in various
industries. It can help businesses create, improve, and innovate products more
efficiently and effectively. It has brought a shift in the product development
arena. The GAI models can be trained on a large dataset of customer reviews
and product feedback to uncover common themes and potential areas of
improvement. These insights could then be used to develop new products
84 V. Kumar and P. Kotler

that are better at meeting customer needs. Some of how GAI can serve in the
product development process include:

• To brainstorm and generate new product ideas or concepts. AI models

can analyze market trends, consumer preferences, and existing products to
suggest innovative concepts. Moreover, these models can be used to design
product concepts and develop early prototypes.
• To analyze material properties and recommend the best materials and
components for a product, considering factors like cost, durability, and
sustainability.
• To help optimize the supply chain by predicting demand, managing
inventory, and suggesting efficient distribution strategies.
• To implement quality control and testing. GAI can help identify defects or
anomalies in products during the manufacturing process.
• To gather and analyze data from competitors, helping to identify gaps in
the market and potential areas for product differentiation.
• To optimize product designs for energy efficiency and environmental
sustainability, aligning with green initiatives.
• To facilitate collaboration among cross-functional teams working on
product development, fostering idea sharing and innovation.

Several companies are including GAI in the product development process.

For instance, Nike uses GAI to design new shoes that analyze data on millions
of feet to create new shoe designs that are comfortable, stylish, and deliver the
expected performance.39 Similarly, Toyota uses GAI’s text-to-image feature to
design new electric vehicle models by using keywords such as “sleek”, “SUV-
like”, and “modern” to arrive at an early prototype image of the car.40 Also,
Procter & Gamble uses GAI to manage their fragrance development process
to have better control over digital scent creation, increasing speed to market
and elevating processes across product development and design.41
Incorporating GAI into product development requires a thorough under-
standing of the specific industry and the needs of its customers. It is
important to identify how GAI technologies can provide unique solutions.
Collaboration between data scientists, engineers, and domain experts is essen-
tial to maximize the benefits of GAI in this context. To refine GAI models and
improve product development processes over time, continuous monitoring
and feedback loops are crucial.
Price: Generative AI can play a valuable role in making pricing decisions
by providing data-driven insights, automating pricing strategies, and opti-
mizing prices based on various factors. Additionally, this technology can allow
 4 Transformative Marketing with Generative Artificial … 85

firms to predict demand, set competitive prices, and develop personalized

pricing strategies—thus leading to increased profits and improved customer
experience offerings. Some of the key pricing decisions enabled by GAI
include:

• Analyzing customer data, such as purchase history, browsing behavior, and

feedback, to understand customer willingness to pay for different products
and services. This information can then be used to set prices that are both
profitable for the business and attractive to customers.
• Predicting customer demand for different products and services. This
information can then be used to set prices that are aligned with expected
demand.
• Optimizing prices in real-time based on factors such as customer demand,
competitor pricing, and inventory levels. This can help businesses to
maximize profits and minimize losses.

An example of using GAI for pricing decisions can be seen in the case of
Uber Freight’s GAI tool—Insights AI. Using LLMs, Insights AI can facili-
tate data discovery and data exploration and deliver intuitive insights from
Uber Freight’s vast store of transportation data. It can support transportation
teams from very granular, tactical views to the most complex, strategic anal-
yses. Shippers using this tool can realize insights on-demand using natural
transportation language such as “What are my key service drivers?”, “Why did
this happen?”, “What might happen in the future?”, and “What should we do
next?”. Through this tool, the company is looking to significantly change the
way logistics decisions are made across service, cost, routing guides, planning,
and tracking.42
Place: Today’s customers want everything, everywhere, and all the time.
They desire a mix of traditional, remote, and self-service channels—with
an increased preference for online ordering and reordering. Many players in
today’s markets are struggling to create value for their customers in a way that
is strong enough to retain them. Some of how companies are considering the
use of GAI are:

• To analyze data on factors such as population demographics, customer

demand, and competition to identify potential locations for new businesses
or facilities. This information can then be used to prioritize locations and
to make more informed decisions about where to expand operations.
• To optimize the layout of existing businesses or facilities to improve effi-
ciency and profitability. For example, generative AI can be used to identify
86 V. Kumar and P. Kotler

the best location for inventory storage, design a more efficient customer
traffic flow, and optimize the placement of equipment.
• To analyze the impact of place decisions on customers and the community.
For example, generative AI can be used to predict how customers will react
to a new store location or to assess the impact of a new development on
the local community.

Regarding the use of GAI to improve operational efficiency in business

locations, many restaurants are considering the implementation of GAI tools
to enhance their drive-thru business. Major chains such as McDonald’s,
Wendy’s, Panera Bread, Carl’s Jr., Hardee’s, and Popeyes are already testing
AI-powered ordering in their drive-thru formats.43 Wendy’s, for example,
has recently launched FreshAI—a GAI tool that aims to improve the drive-
thru ordering experience for customers. The tool uses an AI-powered voice
experience and a digital menu board to make the interaction as natural as
possible, much like speaking with a crew member. The system can provide
quick answers to customer questions and take accurate food orders, even if
the items are not phrased exactly as they appear on the menu. For instance, if
a customer requests a large chocolate milkshake, the system understands that
it should be a large chocolate Frosty® . Overall, the FreshAI tool enhances the
drive-thru experience, ensuring that customers can place their orders with
confidence, knowing that they will receive exactly what they asked for.44
Promotion: Perhaps the most “visible” part of GAI use in the marketing
mix, GAI models are being trained on customer purchase history and interests
to generate product recommendations, email campaigns, and social media
posts. Some of the popular uses of GAI in this regard include:

• To analyze customer data, such as purchase history, browsing behavior, and

feedback, to identify the customers who are most likely to be interested in
specific promotions. This information can then be used to target promo-
tions more effectively and to avoid wasting resources on customers who are
unlikely to be interested.
• To personalize promotions for individual customers based on their inter-
ests, needs, and purchase history. This can help to make promotions
more relevant and appealing to customers, which can lead to increased
engagement and sales.
• To optimize promotion budgets by predicting the impact of different
promotions on customer behavior. This information can then be used to
allocate promotion budgets more effectively and to maximize the return
on investment.
 4 Transformative Marketing with Generative Artificial … 87

Beyond the typical recommendation engines and AI-curated suggestions,

companies are coming up with interesting and novel uses of GAI. For
instance, the Fashion Innovation Agency (FIA), a fashion company and plat-
form, has been exploring the use of AI to design fashion shows and catwalks.
Recently, FIA utilized AI prompt tools like Midjourney and Stable Diffusion.
They trained the AI model to understand the looks of luxury brands that
inspired them and applied the looks to one male model to create a photo-
realistic video. While they acknowledge the importance of human input in
fashion experimentation, they believe that the new photorealistic opportuni-
ties will help to facilitate the mass adoption of digital fashion and promote
fashion offerings.45

Driving Customer Engagement Through GAI

Customer engagement through GAI involves using artificial intelligence

to create personalized, interactive, and meaningful interactions with your
customers. It enhances customer experiences, fosters brand loyalty, and can
lead to increased customer retention. Amazon, for instance, has been devel-
oping its GAI capabilities to make it easier for sellers on Amazon’s website to
create effective product titles, bullet points, and product descriptions. With
this new feature, sellers only need to provide a brief description of their
product, and Amazon will automatically generate high-quality content for
them to review. This content can be refined further by the sellers or submitted
directly to the Amazon catalog. The use of LLMs in this process will help
sellers create listings that are more complete, consistent, and engaging for
customers. Ultimately, this will lead to an improved shopping experience for
customers.46 Similarly, the Dubai Electricity and Water Authority (DEWA)
has launched a GAI tool—Rammas—that provides 24/7 customer support
and assists customers in finding answers to common questions and requests
such as billing inquiries, outage information, and service requests. Touted as
the first such implementation in the utility industry worldwide, Rammas has
answered more than seven million inquiries as of April 2023.47 Such uses of
GAI are directed at improving and enhancing the quality of living and how
people interact with brands. By creating personalized experiences, automating
tasks, and improving customer satisfaction, GAI can help businesses to build
stronger relationships with their customers and to increase customer loyalty.
88 V. Kumar and P. Kotler

Designing Digital Strategies with GAI

In today’s digital landscape, having a strong online presence is crucial for

businesses to succeed. With generative AI, companies can effectively design
and implement digital strategies that improve various aspects of their online
presence. This includes content creation, customer engagement, and other
important elements that contribute to a successful online brand. By lever-
aging the power of AI, businesses can stay ahead of the competition and
ensure their digital strategies are always up-to-date and effective. While
companies are showing keen interest in GAI, it is still early days for using the
technology in creating complete digital strategies. Some of the early initiatives
employed by companies in designing digital strategies using GAI include:

• Starting Small . As companies explore the potential of GAI, they are taking
a measured and careful approach. While eager to test the technology and
its capabilities, they recognize the importance of avoiding a hasty shift
toward full automation. Instead, they are cautiously implementing GAI
to identify its strengths and limitations and to integrate it seamlessly into
their existing operations. For example, the world-famous painting—The
Milkmaid by Vermeer—has recently been in the news due to some new
findings. Scientists have used X-ray technology to discover new objects
hidden in the painting. Interestingly, Nestlé’s famous yogurt, La Laitière,
available in France, shares its name with the painting. Nestlé saw this as an
opportunity to test their GAI capabilities. Nestlé’s ad agency, Ogilvy Paris,
used DALL-E 2 (outpainting tools) to reveal scenes beyond the borders of
the painting’s frame. With the help of prompts like “a kitchen wall with
copper pans and tools painted by Vermeer,” and through almost 1,000
iterations, Nestlé and the agency revealed an extended version of The Milk-
maid, imagined by AI. This content generated a lot of national and global
interest, despite having zero media budget. The video reached 15 million
people and generated e700,000 of media value. France’s major TV broad-
casting network also covered the news segments about the extended version
of The Milkmaid.48 This is a successful example of how starting small can
lead to impressive results.
• Focusing on Personalized Campaigns. Personalizing digital experiences for
customers based on their interests and needs can be made easier with
the help of Generative AI. This can lead to an improvement in customer
engagement and loyalty, making it essential for businesses to implement
GAI-driven personalization strategies. By tailoring content, recommenda-
tions, and user experiences based on individual preferences and behaviors,
 4 Transformative Marketing with Generative Artificial … 89

businesses can effectively meet the needs of their customers. For instance,
companies like Nestle, Unilever, and Mondelez are conducting early exper-
iments regarding GAI’s potential to generate advertisements that slash the
time and money required for marketing campaigns. For example, WPP
collaborated with Mondelez on a Cadbury campaign in India, featuring
popular Bollywood actor Shah Rukh Khan. With the help of AI, they were
able to generate more than 130,000 social media ads that were customized
for specific local stores, without the need to produce any new ads. This
was accomplished by using preexisting footage of Khan and AI-generated
scripts. This resulted in 94 million video views while spending a fraction
of a traditional ad budget.49
• Using GAI to augment the ongoing efforts, not replace it. As businesses
continue to explore the potential of GAI, they are discovering that the
technology can serve as a valuable addition to the team, enhancing human
creativity and expertise. This approach not only allows employees to focus
on more strategic initiatives but also enables them to leverage the unique
strengths of GAI to achieve greater efficiency and productivity. By working
in tandem with humans, GAI can help businesses unlock new opportuni-
ties and achieve their goals more effectively. For instance, Farfetch is an
online marketplace that specializes in luxury fashion and beauty products.
They utilized Phrasee, a GAI tool, to test various styles, tones, words, and
phrases to determine the most effective language that resonates with their
target audience. The goal was to use this information for email marketing
campaigns. By using this tool, Farfetch was able to optimize subject lines
for its broadcast and trigger campaigns, particularly those that included
abandoned browse, basket, and wish list messaging.50 Since implementing
the tool, Farfetch has achieved impressive results.51 As a result, Farfetch
improved its brand by enhancing what makes it unique, rather than relying
on GAI for a complete marketing overhaul.

Future of Generative AI in Marketing

Generative AI is becoming increasingly prevalent in our daily lives, and it is
being used in various activities. The future of generative AI in marketing is
expected to be transformative and full of opportunities. Technologies such
as GPT-3 and advanced neural networks are already altering the marketing
landscape, and their role is expected to expand significantly. Companies like
Amazon (with its Amazon Bedrock) and Bloomberg (with BloombergGPT)
are developing GAI models and platforms that have enormous potential to
90 V. Kumar and P. Kotler

enhance human lives’ quality and improve businesses’ performance. GAI’s

technical capabilities, which include natural language processing, sensory
perception, and social and emotional reasoning, are being developed at an
accelerating rate. In the coming decades, generative AI is expected to reach
human-level performance. The technology’s ability to generate unique media,
personalize content quickly, and take personalization to a new level is worth
keeping an eye on. With that in mind, the following areas show significant
promise for GAI’s growth in marketing.

Ultra-Personalized Experiences

We are on the verge of a new era of marketing strategy, one in which ultra-
personalized experiences reign supreme. Consider a marketing landscape in
which personalized content strategies are not just a lofty ideal, but the norm.
Marketers may soon find themselves crafting campaigns with razor-sharp
precision, abandoning traditional audience segments in favor of campaigns
that are uniquely tailored to individual users. This shift will be enabled by the
introduction of generative AI, which meticulously customizes every campaign
aspect by utilizing a user’s specific behavioral patterns and profiles to generate
bespoke graphics and content.52
This trend is expected to be accelerated by the integration of immersive
and augmented reality (AR) experiences. Generative AI is on the verge of
dynamically generating AR environments that incorporate not only a user’s
immediate surroundings but also their historical behavior and preferences.
These adaptive AR experiences have the potential to forge a deep, resonant
connection with the individual, resulting in AR campaigns that are not only
visually stimulating but also personally meaningful.53
This paradigm shift also applies to seamless omnichannel engagement.
Whether the touchpoint is a website, a social media platform, or a physical
store, generative AI can ensure that a user’s experience with a brand remains
consistent through harmonized user interactions. Such integrated experiences
form the foundation of a coherent omnichannel strategy, which is quickly
becoming unavoidable in our interconnected world.

Personalized Marketing at Scale

In addition to ultra-personalization, the need for personalized marketing

content for users at a large scale will be critical for the success of
marketing campaigns.54,55 Personalized marketing campaigns that cater to
 4 Transformative Marketing with Generative Artificial … 91

each customer’s unique preferences and needs can be created using GAI.
The campaigns can include personalized content such as social media posts,
email campaigns, landing pages, and personalized experiences like chatbots
and virtual assistants. Many global brands, such as Mondelez and PepsiCo,
have rolled out personalized marketing communication strategies to promote
their brand and engage with their customers.
For instance, PepsiCo and Synthesia worked together on their Messi
Messages campaign, which featured personalized video messages from foot-
baller Lionel Messi for their Lay’s brand. PepsiCo was able to create 650
million tailored video versions in 8 languages using just 5 minutes of Messi
footage to train an AI model. This proves how powerfully personalized
AI can be. Additionally, Virgin Voyages used AI to design a customized
cruise invitation tool that included their Chief Celebration Officer Jennifer
Lopez. The platform enables prospective cruisers to produce AI-powered
video invitations from Jennifer Lopez to invite family and friends to join their
celebratory cruises.56 Recognizing these advancements, startups like Typeface
are emerging to provide dedicated GAI platforms for enterprises to create
customized, on-brand content at scale. These platforms enable companies to
leverage AI while maintaining data security, brand guidelines, and IP owner-
ship. Looking ahead, more such startups and business platforms will emerge
that will allow personalization on a large scale.

New Forms of Creative Content

Generative AI can be used to create new forms of creative content, such

as images, videos, and text. This can help businesses create more engaging
and effective marketing campaigns. The creation of unique types of creative
content made possible by generative AI has transformed how we experience
and interact with art, music, and literature. The limits of human creativity are
pushed by this cutting-edge technology, which uses sophisticated algorithms
to automatically develop creative and distinctive works.
In business, brands can venture into unexplored territory and create
engaging works that defy accepted aesthetic rules by utilizing the poten-
tial of GAI. For instance, RTL Deutschland, Germany’s largest privately
held cross-media company, provides on-demand access to millions of
videos, music albums, podcasts, audiobooks, and e-magazines through its
streaming service—RTL+. The streaming platform largely relies on visuals
to attract viewers. In this regard, the streaming service uses DALLE 2 to
generate personalized images and artwork of the streaming content based
on customers’ interests. Additionally, the business is thinking about ways
92 V. Kumar and P. Kotler

to leverage DALLE 2 to add images to content that does not already have
any, including podcast episodes and audiobook scenes. Instead of repeatedly
using the same generic podcast image, for instance, metadata from a podcast
episode may be used to create a unique image to go with it. Similarly, for a
person who is listening to an audiobook, DALLE 2 might also be used to
create a special picture to go with each scene in each chapter.57 Such initia-
tives have provided the company the ability to discover newer avenues of
creativity on a previously unimaginable scale that is driven by the metadata
about the kind of content a user has previously interacted with.
In the coming years, GAI can usher in a new era of creative content,
offering brands access to a diverse set of marketing teams, creative teams,
content creators, artists, musicians, and writers that can drive exploration
and innovation. Using complex algorithms, this technology can enable the
generation of visually stunning artworks, emotionally evocative music, and
captivating narratives. As GAI continues to advance, it holds the potential to
reshape the creative landscape, pushing the boundaries of human imagination
and inspiring new forms of artistic expression.

Ethical Considerations for Developing Marketing

Campaigns

Generative AI presents ethical considerations that warrant careful attention.

A crucial aspect to consider is the impact of GAI on privacy. With increasing
sophistication, this technology can produce remarkably realistic content (e.g.,
synthetic datasets, and computer-generated artwork). Consequently, concerns
arise regarding the potential misuse of GAI for malicious purposes, such as
disseminating misinformation or manipulating public opinion. Therefore, it
is imperative to address the ethical implications of GAI concerning privacy
and establish necessary safeguards to safeguard individuals from potential
harm.
For instance, consider the development of GAI-generated content. The
ownership and protection of GAI-generated works remain uncertain as
companies across the globe continue to adopt this technology. For example,
the US Copyright Office has issued guidance to clarify when artistic works
created with the help of AI are copyright-eligible.58 Accordingly, the agency
contends that the majority of widely used AI systems, including Midjourney,
ChatGPT, and DALL-E 2, are not capable of producing copyrightable work.
This is because “…the generative AI technologies currently available, users do
not exercise ultimate creative control over how such systems interpret prompts
 4 Transformative Marketing with Generative Artificial … 93

and generate material. Instead, these prompts function more like instruc-
tions to a commissioned artist—they identify what the prompter wishes to
have depicted, but the machine determines how those instructions are imple-
mented in its output” (p. 4).59 However, the policy notes that this “does not
mean that technological tools cannot be part of the creative process” (p. 4),60
and requires copyright applicants to disclose the inclusion of AI-created mate-
rial in their application. While India follows a similar approach to that of the
United States in this regard,61 specific laws for copyrighting AI-generated
content are yet to be established in the European Union and are processed
on a case-by-case basis.62 Therefore, there is a lack of clarity across nations
on how to address the copyright issue arising from GAI-inspired works.
Recognizing this, companies have started recognizing the need to account
for the ethical aspects and are implementing appropriate measures. For
instance, Mars, the pet food manufacturer, is using GAI to help them “…pre-
dict whether cats and dogs could develop chronic kidney disease; speeding up
the sequencing of pet genomes to provide individualized nutrition and care;
and unlocking efficiencies in our manufacturing operations through digital
twin technology”.63 In doing so, the company has realized the ethical risks
involved. To address the potential ethical risks, the organization has imple-
mented a comprehensive approach by forming an enterprise working team.
This team is dedicated to developing a robust framework of policies and
governance about the utilization of GAI. Additionally, strategic alliances with
partners such as Microsoft and reputable non-governmental organizations
like the Responsible AI Institute help the company further enhance its efforts
in ensuring responsible and ethical implementation of AI technologies.
Overall, ethical considerations surrounding GAI require a multi-
stakeholder approach, involving developers, organizations, regulators, and the
public. It is essential to balance innovation with ethical principles, ensuring
that GAI technologies benefit society while minimizing potential risks and
harms.
In addition to the above-mentioned specific examples, it is also possible
that GAI could lead to the realization of entirely new aspects that we cannot
even imagine today. As GAI continues to develop and become more sophis-
ticated, it is likely to have a major impact on the way that marketing is done
in the future.
94 V. Kumar and P. Kotler

Key Terms and Related Conceptualizations

Generative Adversarial Networks (GANs) A framework that pits two neural
networks against each other, one to
generate data and the other to
distinguish between generated and
real data, resulting in highly realistic
outputs
Generative AI (GAI) A subset of deep learning, that uses
supervised, unsupervised, and
semi-supervised machine learning
methods to generate new data
instances based on the learned
probability distribution of existing
data
Text-to-3D GAI models Refers to GAI models that create
three-dimensional objects that
correspond to a user’s text
description
Text-to-image GAI models Refers to GAI models that are trained
on a large set of images, where each
image is captioned with a short text
description
Text-to-task GAI models Refers to GAI models that are trained
to perform a specific task or action
based on text input
Text-to-text GAI models Refers to GAI models that take a
natural language input and produce
a text output
Text-to-video GAI models Refers to GAI models that generate a
video representation from a text
input, where the input can range
from a single sentence to a full script

Notes and References

1. Bloomberg. (June 1, 2023). Generative artificial intelligence (AI)
revenue worldwide from 2020 with forecast until 2032 (in
billion U.S. dollars) [Graph]. In Statista. Retrieved October 10,
2023, from https://www.statista.com/statistics/1417151/generative-ai-
revenue-worldwide/.
2. A McKinsey survey reveals that 60% of respondent organizations with
reported AI adoption are using GAI (Chui, M., L. Yee, B. Hall,
A. Singla, & A. Sukharevsky [2023a], “The state of AI in 2023:
Generative AI’s breakout year,” McKinsey & Company, August 1,
accessed from https://www.mckinsey.com/capabilities/quantumblack/
our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year).
 4 Transformative Marketing with Generative Artificial … 95

3. MarTech. (May 8, 2023). Marketing purposes for which profes-

sionals are using generative artificial intelligence (AI) in the United
States as of March 2023 [Graph]. In Statista. Retrieved October 10,
2023, from https://www.statista.com/statistics/1386786/generative-ai-
marketing-purposes-usa/.
4. Feuerriegel, S., J. Hartmann, C. Janiesch, & P. Zschech (2023). Gener-
ative AI. Retrieved From: https://www.researchgate.net/publication/
370653602_Generative_AI.
5. Dwivedi, Y. K., N. Kshetri, L. Hughes, E. L. Slade, A. Jeyaraj, A. K.
Kar, & R. Wright (2023a). So what if ChatGPT wrote it? Multidis-
ciplinary perspectives on opportunities, challenges and implications of
generative conversational AI for research, practice and policy. Interna-
tional Journal of Information Management, 71, 102642; Dwivedi, Y.
K., N. Pandey, W. Currie, & A. Micu (2023b). Leveraging ChatGPT
and other generative artificial intelligence (AI)-based applications in
the hospitality and tourism industry: Practices, challenges and research
agenda. International Journal of Contemporary Hospitality Management.
https://doi.org/10.1108/IJCHM-05-2023-0686; Kshetri, N. (2023).
The economics of generative artificial intelligence in the academic
industry. IEEE Computer, 56 (8), 77–83.
6. GAI exemplifies a distinct class of AI tools capable of creating seem-
ingly novel content across a variety of mediums, including textual,
visual, and others (Susarla, A., R. Gopal, J. B. Thatcher, & S. Sarker
[2023], The Janus effect of generative AI: Charting the path for
responsible conduct of scholarly activities in information systems.
Information Systems Research, 34 (2), iii–vii. https://doi.org/10.1287/
isre.2023.ed.v34.n2).
7. Dwivedi, Y. K., N. Pandey, W. Currie, & A. Micu (2023b). Leveraging
ChatGPT and other generative artificial intelligence (AI)-based appli-
cations in the hospitality and tourism industry: Practices, challenges
and research agenda. International Journal of Contemporary Hospitality
Management. https://doi.org/10.1108/IJCHM-05-2023-0686.
8. Verhoef, P. C. (2020). Customer experience creation in today’s digital
world. The Routledge companion to strategic marketing, 107–122.
9. Grewal, D., A. L. Roggeveen, R. Sisodia, & J. Nordfält (2017),
“Enhancing customer engagement through consciousness,” Journal of
Retailing, 93(1), 55–64.
10. Anisin, A. (2023), Generative AI for content creation: How marketers
can use it. Forbes. https://www.forbes.com/sites/theyec/2023/08/17/
generative-ai-for-content-creation-how-marketers-can-use-it/?sh=7db
8f8c7619e.
11. A survey conducted by the prestigious Conference Board reveals an
overwhelming sentiment among marketers; 82% see GAI as a sign
96 V. Kumar and P. Kotler

of increased productivity, only 4% believe otherwise (The Confer-

ence Board [2023]. Survey: AI usage for marketers and communi-
cators, August 3, https://www.conference-board.org/topics/AI-for-bus
iness/press/AI-in-marketing-and-communications).
12. Gartner (2023). “Generative AI,” Gartner, accessed from https://www.
gartner.com/en/information-technology/glossary/generative-ai.
13. Martineau, K. (2023), “What is generative AI?” IBM , April 20,
accessed from https://research.ibm.com/blog/what-is-generative-AI.
14. Universal Marketing Dictionary Project (2023), “Generative AI,” The
Universal Marketing Dictionary, accessed from https://marketing-dictio
nary.org/g/generative-ai/.
15. Routley, N. (2023), “What is generative AI? An AI explains,” World
Economic Forum, February 6, accessed from https://www.weforum.org/
agenda/2023/02/generative-ai-explain-algorithms-work/.
16. Open AI released GPT-1 in 2018 and had 117 million parameters. The
model was trained on books to predict the next word in a sentence.
In 2019, they developed GPT-2 with 1.5 billion parameters and the
model could produce a coherent multi-paragraph text. GPT-3 devel-
oped in 2020 had 175 billion parameters and was able to write code,
poetry, translate languages, and answer factual questions. By November
2022, they released GPT-3 and updated the fact-checking and math-
ematical abilities of the model for better accuracy and performance
across more topics.
17. In September 2023, Open AI announced DALL-E 3, which is a signif-
icant leap forward in generating images that strictly align with the
provided text. The model has several capabilities, including speed (the
ability to generate images within a minute), customization, and acces-
sibility (users do not require extensive training or programming skills
to use it).
18. Wouters, O. J., M. McKee, & J. Luyten (2020), “Estimated research
and development investment needed to bring a new medicine to
market, 2009-2018,” Jama, 323(9), 844–853.
19. Balasubramanian, S. (2023), “Bayer is rapidly expanding its footprint
with artificial intelligence,” Forbes, September 4, accessed from https://
www.forbes.com/sites/saibala/2023/09/04/bayer-is-rapidly-expanding-
its-footprint-with-artificial-intelligence/?sh=5ea961724df8.
20. Capoot, A. (2023), “Microsoft announces new AI tools to help doctors
deliver better care,” CNBC , October 10, accessed from https://www.
cnbc.com/2023/10/10/microsoft-announces-microsoft-fabric-and-
azure-ai-tools-for-doctors.html.
 4 Transformative Marketing with Generative Artificial … 97

21. McKinsey estimates that in the next three to five years, GAI could add
up to $275 billion to the apparel, fashion, and luxury sectors’ operating
profits (Harries et al. 2023).
22. E.g. Stokel-Walker, C. (2022). AI bot ChatGPT writes smart essays—
Should professors worry? Nature, accessed from https://doi.org/10.
1038/d41586-022-04397-7; Eke, D. O. (2023). ChatGPT and the
rise of generative AI: threat to academic integrity? Journal of Responsible
Technology, 13, 100060.
23. Yu, H., & Y. Guo, (2023, June). Generative artificial intelligence
empowers educational reform: current status, issues, and prospects.
In Frontiers in education (Vol. 8, p. 1183162). Frontiers. Classify the
applications of GenAI in education into the following four areas: (1)
intelligent teaching systems (personalized course content and teaching
plans based on student’s learning process), (2) intelligent homework
grading (analyzing students’ homework, judging its correctness and
errors, and providing corresponding scores and suggestions), (3) intel-
ligent tutoring system (generation of tutoring content and strategies
based on the analysis of students’ learning situations and personalized
needs), and (4) intelligent speech interaction system (achieving speech
interaction with students to better understand their learning needs and
questions).
24. According to a study conducted by Bain & Company, which involved
around 600 companies across 11 industries, the rapid production of
marketing materials has emerged as a leading use case for generative
AI (Katzin, J., L. Beaudin, & M. Waldron [2023], “Ready for launch:
How Gen AI is already transforming marketing,” Bain & Company,
May 23, accessed from https://www.bain.com/insights/ready-for-lau
nch-how-gen-ai-is-already-transforming-marketing/). The study found
that 47% of the participants either currently use or are consid-
ering implementing this technology for customer engagement and
service applications, and 39% for creating marketing materials more
efficiently.
25. Ostwal, T. (2023), “Coca-Cola’s holiday campaign gets a generative
AI-powered makeover,” AdWeek, November 17, accessed from https://
www.adweek.com/brand-marketing/coca-cola-holiday-campaign-cre
ate-real-magic-cards/#.
26. Bamberger, S., N. Clark, S. Ramachandran, & V. Sokolova (2023),
“How generative AI is already transforming customer service,” BCG,
July 6, accessed from https://www.bcg.com/publications/2023/how-
generative-ai-transforms-customer-service.
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27. Boyle, A. (2023), “This audio startup is using AI to generate ‘contex-

tual CTV ads’,” AdExchanger, August 10, accessed from https://www.
adexchanger.com/digital-tv/this-audio-startup-is-using-ai-to-generate-
contextual-ctv-ads/.
28. Seedtag (2023), “Seedtag launches industry first generative AI capa-
bility for contextual dynamic creatives,” PR Newswire, May 17,
accessed from https://www.prnewswire.com/news-releases/seedtag-lau
nches-industry-first-generative-ai-capability-for-contextual-dynamic-
creatives-301827150.html.
29. Frandino, N. (2023), “AI-powered monocle seeks to add sparkle to
dull human chats,” Reuters, May 25, accessed from https://www.
reuters.com/technology/ai-powered-monocle-seeks-add-sparkle-dull-
human-chats-2023-05-25/.
30. Verma, R. (2023), “Stanford students develop AR glasses that let you
talk to ChatGPT in real time,” Business Insider India, April 3, accessed
from https://www.businessinsider.in/tech/news/stanford-students-dev
elop-ar-glasses-that-let-you-talk-to-chatgpt-in-real-time/articleshow/
99205100.cms.
31. Chitnis, S. (2023), “RizzGPT app inventor hoping to use genera-
tive AI to generate some charisma on demand,” CBS News, July 6,
accessed from https://www.cbsnews.com/sanfrancisco/news/rizzgpt-
app-inventor-hoping-to-use-generative-ai-to-generate-some-charisma-
on-demand/.
32. IBM (2023), “Combining generative AI with IBM Watson, Mitsui
Chemicals starts verifying new application discovery for agility and
accuracy,” IBM , May 25, accessed from https://newsroom.ibm.com/
2023-05-25-Combining-Generative-AI-with-IBM-Watson,-Mitsui-
Chemicals-Starts-Verifying-New-Application-Discovery-for-Agility-
and-Accuracy.
33. Mitsui (2023), “Double the number of new application discoveries
by utilizing generative AI,” Mitsui Chemicals, September 13, accessed
from https://in.mitsuichemicals.com/release/2023/2023_0913.htm.
34. McKinsey & Company. (June 14, 2023). Automation potential with
and without generative artificial intelligence (AI) in the United
States in 2023, by profession [Graph]. In Statista. Retrieved October
17, 2023, from https://www.statista.com/statistics/1411571/job-aut
omation-potential-generative-ai/.
35. Ziady, H. (2023), “The world’s biggest ad agency is going all in on AI
with Nvidia’s help,” CNN , May 29, accessed from https://edition.cnn.
com/2023/05/29/tech/nvidia-wpp-ai-advertising/index.html.
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36. Harreis, H., T. Koullias, K. Te, & R. Roberts (2023), “Generative

AI: Unlocking the future of fashion,” McKinsey & Company, March
8, accessed from https://www.mckinsey.com/industries/retail/our-ins
ights/generative-ai-unlocking-the-future-of-fashion.
37. Chui, M., E. Hazan, R. Roberts, A. Singla, K. Smaje, A. Sukharevsky,
L. Yee, & R. Zemmel (2023b), “The economic potential of generative
AI: The next productivity frontier,” McKinsey & Company, June 14,
accessed from https://www.mckinsey.com/capabilities/mckinsey-dig
ital/our-insights/the-economic-potential-of-generative-ai-the-next-pro
ductivity-frontier#introduction.
38. Harreis, H., T. Koullias, K. Te, & R. Roberts (2023), “Generative
AI: Unlocking the future of fashion,” McKinsey & Company, March
8, accessed from https://www.mckinsey.com/industries/retail/our-ins
ights/generative-ai-unlocking-the-future-of-fashion.
39. Burgess, M. (2018), “How Nike used algorithms to help design its
latest running shoe,” Wired , January 25, accessed from https://www.
wired.co.uk/article/nike-epic-react-flyknit-price-new-shoe.
40. Dreibelbis, E. (2023), “Toyota is using generative AI to design new
EVs,” PC Magazine, June 21, accessed from https://www.pcmag.com/
news/toyota-is-using-generative-ai-to-design-new-evs.
41. Dominguez, L. (2023), “P&G Leans into intelligent fragrance devel-
opment powered by AI,” Consumer Goods Technology, October 3,
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nce-development-powered-ai.
42. Uber Freight (2023), “Uber Freight Insights AI: Bringing the power
of generative AI to enterprise shippers,” Uber Freight, September
28, accessed from https://www.uberfreight.com/blog/uber-freight-ins
ights-ai/.
43. Tyko, K. (2023), “Drive-thru mania pushes chains to rethink restau-
rants,” Axios, August 11, accessed from https://www.axios.com/2023/
08/11/fast-food-drive-thru-restaurants-future.
44. Spessard, M. (2023), “AI and beyond: Wendy’s new innovative restau-
rant tech,” Wendy’s, June 2, accessed from https://www.wendys.com/
blog/how-wendys-using-ai-restaurant-innovation.
45. Zwieglinska, Z. (2023), “How fashion brands are using generative AI,”
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46. Westmoreland, M. B. (2023), “Amazon launches generative AI to help
sellers write product descriptions,” Amazon, September 13, accessed
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from https://www.aboutamazon.com/news/small-business/amazon-sel
lers-generative-ai-tool.
47. Khaleej Times (2023), “Dubai: Dewa announces pilot use of ChatGPT
to boost capabilities of its virtual employee,” Khaleej Times, May 9,
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49. McKay, C. (2023), “Big brands experiment with generative AI for
advertising,” Maginative, August 18, accessed from https://www.mag
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ith,footage%20and%20AI%2Dgenerated%20scripts.
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51. An average click-rate uplift of 38% and an average open rate uplift
of 31% for improving abandoned basket rates. In addition, sales and
other campaign offers saw an average click rate uplift of 25% and an
average open rate uplift of 7% (Phrasee 2023).
52. Pataranutaporn, P., V. Danry, J. Leong, P. Punpongsanon, D. Novy,
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c50886.
54. A 2022 global survey found that 81% of consumers from Singapore
were “definitely likely” or “somewhat likely” to stop using a brand if
it did not personalize their customer experience. 80% from Brazil,
76% from Colombia, 75% from Mexico and 75% from Germany
were the other top 4 countries where the respondents wanted greater
levels of personalisation (Twilio [2022a]. Share of consumers who said
they were likely to stop using a brand if it did not personalize their
customer experience in selected countries worldwide as of January
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55. Another global survey revealed that 34% of business-to-consumer
(B2C) marketers said that their organizations always personalized
customer experiences, while only 11% of consumers agreed (Twilio
[2022b]. Frequency of personalizing experiences according to B2C
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statista.com/statistics/1333313/frequency-personalize-experiences/).
More importantly, while only 3% of B2C marketers said their organi-
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consumers disagreed. Such studies imply that consumers are constantly
looking for personalized experiences from the brands they interact
with.
56. McKay, C. (2023), “Big brands experiment with generative AI for
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 5
Transformative Marketing with Machine
Learning (ML)

Overview
Machine learning (ML) can be defined as computational methods that
use experience to improve performance or to make accurate predictions.1
By considering past information (i.e., referred to as experience), machines
gain the ability to learn while they perform, thereby showing performance
improvement. Past information can be in the form of collected data or infor-
mation actively sourced through interaction with the environment. Learning
quality depends on the volume and quality of data; the key outcome is predic-
tions about key variables of interest. Simply put, ML deals with the process
of training machines to learn over time.2
Machine learning is a technique that utilizes neural networks to iden-
tify and refine factors of importance to predict the probable outcomes of a
given situation. This process requires manual programming upfront to adjust
the factors of importance repeatedly until the desired outcome is achieved
based on the data fed into the algorithm. However, once the algorithm has
been trained using a training dataset, it can analyze new data inputs, recog-
nize patterns, and produce increasingly accurate results without the need for
human intervention. In essence, ML is a way to enhance the intelligence of
machines by developing, comprehending, and evaluating learning algorithms.
This chapter is organized in the following manner. First, a brief history
of the origin of ML is presented, followed by a definition of ML (from a
marketing standpoint), along with three vignettes about ML usage and appli-
cations. Then, the role of ML in the Marketing 5.0 concept is explored. Next,

© The Author(s), under exclusive license to Springer Nature 103

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_5
104 V. Kumar and P. Kotler

some marketing applications of ML are discussed. Finally, the future of ML

for the marketing industry is envisioned via emergent issues in this area.

Origin, Definition, and Components of ML

Machine learning finds its origin in neural networks. First proposed in 1943
by Warren McCulloch and Walter Pitts, they presented that the human
thought process can be replicated through a combination of mathematics and
algorithms.3 Subsequently, in 1950, Alan Turing called for the development
of computers that can “think.”4 Turing’s seminal article was an important call
for research in this area. This was followed by the design of the first artificial
neural network (ANN) by Frank Rosenblatt in 1958 to detect shapes and
patterns.
Early attempts in the 1950s and 1960s to advance the field of ML included
teaching machines to play games like Checkers and making phone calls
sound better to demonstrate that machines can deal with things that are
understandable and complex. However, the interim years in the decades of
the 1970s and the early part of the 1980s saw little impactful work in the
field of ML. This lull was thought to be the outcome of research focusing
on logical, knowledge-based approaches rather than algorithms.5 In the late
1980s, the technique of backpropagation that was advanced by Geoffrey
Hinton for use in shape recognition and word prediction rekindled interest
in ML.6 Soon after, successive ML advancements include the development of
machine-readable text, advancements in text categorization and image clas-
sification, and improvements in short-term information storage and retrieval
from machines’ memory. In the early 2000s, the concept of deep learning was
advanced which was a significant leap in terms of machines’ processing ability
regarding structured data and machines’ ability to learn from knowledge with
lesser human involvement. The deep learning concept has since driven (and
continues to drive) ML developments with various business and end-user
applications. The components of an ML algorithm can be broadly comprised
of the following four elements—data, data mining, data augmentation, and
ML models.
Data. Data always plays a crucial role in building any model. Typically,
humans feed the data along with a set of explicit instructions and train the
machine to repeatedly execute the command. However, with ML algorithms,
as more data is made available, the machine makes self-corrections based on
the accuracy of the output. In other words, it learns, over time, with more
data becoming available. In this regard, the input data may be of two types—
manually labeled and classified to be fed in,7 or data classification rules can
be learned by the machine through a semantic point of view.8
 5 Transformative Marketing with Machine Learning (ML) 105

Additionally, the data being fed may be structured or unstructured.

Whereas ML works remarkably well with large volumes of structured data
(i.e., any data that resides in a database under specific fields with clearly
defined values), it does even more so with unstructured data (UD). The
rise of UD has changed markets and the management of marketing activ-
ities. UD is defined as a single data unit in which the information offers
a relatively concurrent representation of its multifaceted nature without
predefined organization or numeric values.9 Further, the non-numeric, multi-
faceted, and concurrent representation of UD makes statistical methods
difficult or inapplicable. However, because of such characteristics, UD can
be highly beneficial toward deriving new marketing insights, especially along
the following three aspects.

• First, UD does not have a predefined numeric form for the constructs of
interest. Therefore, researchers must conduct pre-processing manually or
automatically before the data is ready for analysis. Nonnumeric properties
in UD offer greater flexibility for researchers to discover new theo-
ries. Highly unstructured data like video are only non-numeric, thereby
requiring researchers to assign values to the data.
• Second, a single unit of highly unstructured data possesses multiple facets,
each with potentially unique information that allows the researchers to
select and analyze facets based on the research goals (especially voice and
video data). Multiple facets in such types of data enable researchers to
provide managers with richer and deeper marketing insights.
• Finally, concurrent representation is the simultaneous presence of multiple
facets in a single data unit. Each facet can provide unique information that
allows a UD unit to describe different phenomena at the same time. There-
fore, researchers can examine different research questions with a single
highly unstructured data unit by exploring the concurrent and dynamic
flow of these unique facets.

Data Mining . Data mining refers to the process of discovering interesting

patterns in databases that are useful in decision-making.10 Data mining uses
a broad family of computational methods that include statistical analysis,
decision trees, neural networks, rule induction and refinement, and graphic
visualization.11 Companies have realized that information about their users
(i.e., preferences, needs, wants, etc.) holds a lot of power in terms of overall
decision-making. With specific reference to marketing, firms collect, store,
and process vast amounts of highly detailed information about customers,
markets, products, and processes through different programs. Data mining
106 V. Kumar and P. Kotler

this information gives businesses the ability to make knowledge-driven

strategic business decisions to help predict future trends and behaviors and
create new opportunities. Further, data mining can assist in selecting the right
target customers or in identifying (previously unknown) customer segments
with similar behaviors and needs. A typical data mining process includes
assessing and specifying the business objectives, data sourcing, transforma-
tion, creation of analytical variables, selecting relevant variables, training
predictive models, selecting the best-suited model, and acting based on the
findings.12 Figure 5.1 illustrates a typical data mining process for marketing
purposes.
Streamlining the laborious processes of data extraction, manipulation,
quality monitoring, and enhancement is crucial. By automating these tasks,
highly skilled quantitative data analysts can allocate their time towards more
valuable tasks. This is where ML comes into play. Through data mining,
companies can explore their data to uncover trends and patterns that can
inform decision-making. On the other hand, ML can leverage existing data
to continuously learn and improve its performance without human interven-
tion. Unlike data mining, ML can detect relationships between different data
points, making it a powerful tool for developing applications.
Data Augmentation for Better Business Insights. While ML can comb
through data to deliver insights, the variety in data that ML can easily
process will provide more layers of insights. In other words, extracting the
data from various sources, transforming it for ML algorithms, and loading it

Learn

(Re)Define Identify Gain

Get Raw
Business Relevant Customer Act
Data
Objectives Variables Insight

. Define . Extract . Rollup data . Train . Deploy models

objectives and descriptive and . Create predictive . Monitor
expecations transactional analytical models performance
. Define data variables . Compare . Enhance models
measurement . Check quality . Enhance models
of success (technical and analytical data . Select models
business) . Select relevant
variables

Fig. 5.1 Data mining process for marketing purposes

(Source Kumar, V., and W. J. Reinartz (2018). Customer relationship management:
Concept, Strategies, and Tools. 3rd edition, Berlin, Germany: Springer-Verlag Berlin
Heidelberg)
 5 Transformative Marketing with Machine Learning (ML) 107

into a structured schema applicable to ML processes is referred to as an ETL

(extract/transform/load) process. While such a process can add much value
to an ML algorithm, it can also be challenging in terms of keeping track of
where the data comes from, and how it is transformed, and loaded for further
analysis. Additionally, given the wide range of data types (i.e., structured, and
unstructured) and data sources (i.e., text, audio, video, location, etc.) that ML
can handle, ensuring the sanity and relevance of the data can be a daunting
task for many companies. This is because the ML process learns based on the
data that is fed, and the quality of data matters a lot.
Types of ML Models. The models used by ML solutions largely fall into
three types—supervised learning, unsupervised learning, and reinforcement
learning. Supervised learning involves creating a concise model that repre-
sents the relationship between predictor features and class labels.13 In this
type of learning, the training data consists of pairs of input and output, where
the output is typically known. For instance, let’s consider a boutique fashion
retailer who wants to categorize their customers as either local or national
to determine shipping fees for deliveries. In this scenario, the input vari-
able for a supervised learning algorithm would be the customer’s state of
residence, which can be obtained from the retailer’s customer database. The
output variables would be assigned a value of 1 if the customer resides in that
state (indicating a local customer) and 0 if the customer resides outside of
that state (indicating a national customer). Decision trees, neural networks,
logistic regression, and k-nearest neighbors are a few examples of this learning
type. Popular applications of the supervised learning model include spam
filtering software and speech recognition software.
Unsupervised learning pertains to making the machine learn about
performing a task without providing explicit instructions on how to do it.
Here, the machine learns by exploiting the innate structures of the data, such
as data variance, separability, and data distribution.14 Dimension reduction
methods and clustering procedures use this type of learning. Commercial
applications of this type of learning can be found in fraudulent transaction
detection software and image recognition software, among others.
Reinforcement learning, also known as semi-supervised learning, pertains
to the learning of a mapping from situations to actions to maximize a
scalar reward or reinforcement signal.15 Here, the machine is not told which
action(s) to take, rather it must discover which action(s) yield the highest
reward by trying them. Feature selection integrates a small amount of labeled
data into unlabeled data as additional information to improve the perfor-
mance of an unsupervised feature selection. Commercial applications of this
learning type include autonomous cars and news recommendation apps,
108 V. Kumar and P. Kotler

among others. A more detailed discussion of these three types of ML models

appears later in this chapter.
In recent years, ML has advanced significantly due to new computing
technologies. ML originated from pattern recognition and the idea that
computers can acquire knowledge without explicit programming. The iter-
ative nature of ML allows models to adapt independently and make reliable
decisions. Collaboration across disciplines has led to remarkable progress in
ML, offering opportunities for users and businesses. The following three
vignettes illustrate the potential of ML and its benefits for companies and
individuals.

Analytics-Oriented Technology

Research reports and business trends indicate that ML is a rapidly growing

business function within firms.16 Yet, companies are also hesitant about the
path forward. So, what is preventing businesses from taking the plunge into
ML to achieve predictive analytics capabilities? Some of the critical factors
that drive a successful ML adoption include developing perceptive manage-
rial judgment, accumulating relevant domain knowledge, implementing a
comprehensive technology-backed strategy, and a well-thought-out imple-
mentation approach,17 Other organizational factors that could impede an
organization’s ML adoption include human talent management, not able
or equipped to interpret results, and dealing with inadequate or irrelevant
data.18
It is here that the distinction between statistical models (SM) and ML
becomes pertinent. While SM (using quantitative techniques) has been iden-
tified as best suited for inference; ML works best for generating predictions.
In this regard, the decision to use SM vs. ML potentially rests on the
following five expectations from managers/researchers—(a) the number of
variables to consider (fewer vs. more), (b) the type of relationships to be
studied (simple interactions vs. higher-order interactions), (c) the type of use
(used one time vs. repeatedly), (d) the nature of use (possibility for learning,
or not), and (e) the timing of use (real-time needs, or not).19 However, this
does not have to be an either-or decision. Both SM and ML can be used
collectively. That is, the convergence of boundaries between SM and ML can
be the way forward.20 As more organizations implement ML solutions, busi-
nesses are using ML in various capacities. Some business areas where ML is
being used include:
 5 Transformative Marketing with Machine Learning (ML) 109

• Marketing—ML is being extensively used in many marketing functions

and e-commerce applications (see Image 5.1).21 Additionally, ML provides
companies with the capabilities to make quick decisions and implement
digital transformation, in-house data management, and insights genera-
tion.
• Healthcare—ML is being increasingly used in the healthcare industry to
enable healthcare providers to glean insights on patient diagnosis and
identify/prevent health risks earlier. Since high-risk patients often require
extra care, monitoring, and treatment, ML is well-equipped to handle the
challenge by identifying high-risk patients to keep healthcare costs down.
Here, ML models can comb through medical data to identify risk factors

Image 5.1 Shopify. Shopify facilitates businesses through its machine-learning capa-
bilities
(Source Photo by Roberto Cortese on Unsplash)
110 V. Kumar and P. Kotler

and potential health issues.22 Subsequently, medical care providers iden-

tify and design a care plan that includes appropriate intervention and care
strategies.
• Food waste—Food waste is a major challenge faced by corporations across
all industries, with potentially lasting implications on the climate and envi-
ronment. Many companies are making efforts to reduce food waste. In this
regard, Hitachi uses AI/ML solutions to monitor and combat food waste
in hospitals. To track what and how much patients are eating, cameras
are mounted on the food trays to take pictures to document what food is
left over. This data is then fed to Hitachi’s deep learning algorithms that
analyze the data to find patterns in the waste that humans would not be
able to as quickly. This would help with food service decisions and patient
care, and the necessary changes that would be required.23

Organizations and technology companies are employing machine learning-

based predictive analytics to gain an edge over the rest of the market. Machine
learning advancements such as neural networks and deep learning algorithms
can discover hidden patterns in unstructured data sets and uncover new infor-
mation. In this regard, ML continues to drive analytics at organizations across
various industries.

Link to Artificial Intelligence

While AI is the broad science of mimicking human abilities, machine learning

is a specific subset of AI that trains a machine to learn. In this regard, AI and
ML are conceptualized to be more aligned with an analytics orientation and
related capabilities among new-age technologies.24 As mentioned earlier, the
varied types of data (i.e., text, image, video, etc.) that are captured, stored,
and used for analytics purposes continue to drive the development of ML
learning models and AI capabilities.
The rapid growth of ML and AI in delivering granular insights, thereby
bringing us closer to the goal of transformative marketing, would have been
nearly impossible for humans alone to accomplish. For instance, advance-
ments in speech and voice recognition have spurred the growth of digital
personal assistants such as Apple’s Siri and Amazon’s Alexa. Facial recogni-
tion continues to power Facebook’s auto-tagging feature and iPhone X’s facial
recognition-based unlocking, and recommendation engines continue to drive
Netflix, Spotify, and Pandora. Therefore, there is a natural link between ML
and AI that is deeply rooted in the continued learning based on data analysis.
This also makes them most conducive towards analytics purposes.25
 5 Transformative Marketing with Machine Learning (ML) 111

Commercial applications involving a combination of AI and ML are

plentiful and can be found across various industries. For instance, this combi-
nation can be seen in transportation through ride-sharing apps (e.g., Uber,
Lyft), online maps (e.g., Google Maps incorporate user-reported traffic inci-
dents like construction and accidents for suggesting the fastest route), and
driverless cars (see Image 5.2).
Similarly, this combination can be found in communication tools such
as emails (e.g., Gmail reads the emails to provide autofill options for email
replies), online writing tools (e.g., Grammarly uses AI, ML, and NLP tools
to suggest writing enhancements and identify potential plagiarism), and in
education technology (e.g., ETS, the online testing service, uses automated
scoring technologies developed using NLP to score the tests).
A prominent case of ML usage is PayPal. PayPal has access to data on
more than 350 million customers and merchants in over 200 markets. A
large part of PayPal’s success is in helping their merchants detect and prevent
fraud. Machine learning plays a role in detecting and mitigating fraud in a
myriad of ways. The algorithms run thousands of queries in milliseconds and
can assess individual customer behaviors in real time. This allows them to
differentiate legitimate customers from fraudulent ones—aiding in approving
authentic transactions and thus creating a seamless experience for trusted
customers.26 Additionally, PayPal’s two-sided network is a rich source of

Image 5.2 Ride-sharing Applications. Ride-sharing apps such as Uber and Lyft use a
combination of AI and ML to provide the most relevant route results
(Source Photo by Fikri Rasyid on Unsplash)
112 V. Kumar and P. Kotler

transaction and risk data from 432 million active global accounts that may
help train algorithms and enhance fraud detection.
The most common frauds that PayPal encounters are of three types and
the company uses ML tools to secure users from these frauds. First, in the
case of signup frauds (i.e., when scammers create new bank or credit card
accounts with stolen or synthetic identities), Paypal uses ML to analyze third-
party data (email address, session data, enrolment data) to help spot and
stop any fraudulent activity. Second, in the case of login frauds (i.e., taking
over an existing customer account, or stealing logins), the fraud is mitigated
by assessing customer behavior data, monitoring devices, IP addresses, and
so on. Finally, regarding payment frauds (i.e., scammers using credit card
details without the cardholder’s knowledge), the company uses ML to analyze
previous transactions to identify anomalies and indicate the occurrence of
fraud.27
While PayPal and other transaction platforms are implementing machine
learning to its full potential, scammers are also constantly testing filters,
and designing new attacks to find a way around them. As e-commerce
continues to grow, machine learning is pivotal for companies’ e-commerce
fraud strategy. In such a dynamic landscape, machine learning and other
new-age technologies will play larger roles in payment fraud detection and
mitigation.

Machine Learning Models

Machine learning is an application of AI that provides systems the ability

to automatically learn and improve from experience without being explic-
itly programmed. Learning in ML assumes three forms—supervised, unsu-
pervised, and reinforcement—and can be understood in terms of inputs,
outputs, and outcomes.28
Supervised learning. This form is often used when the response variables are
to be recorded; for instance, recognizing the hand-written text or identifying
spam emails. Essentially, the learning system uses prior data as training infor-
mation and accordingly presents related predictions for all future outcomes.
This form of learning is often used for research problems in regression and
classification.29
In some cases, the classification is useful when researchers want to iden-
tify the class and group in the response variable, and in some cases may
even involve qualitative information. For instance, a bank may be inter-
ested in predicting whether an individual will default on their credit card
payment, based on income and monthly credit card balance. Further, while
 5 Transformative Marketing with Machine Learning (ML) 113

some methods in supervised learning allow researchers to interpret the coeffi-

cient(s), others do not. Since the response variables are observed in supervised
learning, methods such as leave-one-out cross-validation (LOOCV), K-fold
cross-validation, or validation can be used by researchers to examine the
prediction power of models.30
Unsupervised learning . This form is used when researchers only observe
the input variables x, but not the response variables y. In such situations,
researchers can explore to understand the relationships between the variables
or between the observations. The methods used in unsupervised learning
include association rule learning, principal component analysis, and clus-
tering. Unsupervised learning is important for understanding the variation
and grouping structure of a set of unlabeled data, such as sentiment analysis
and topic modeling. For instance, from online customer reviews about prod-
ucts/services, researchers can mine information from text and emojis used by
customers. A supervised analysis would be possible if researchers had informa-
tion about these customers’ usage patterns of the said products/services. In the
absence of such information, researchers can use natural language processing
(NLP) to classify the sentiment of each customer about products into a cate-
gory scale: negative, neutral, and positive. The comments from customers can
also be classified into some common topics (e.g., product features, product
design, or the quality of service) and their purchase disposition towards such
offerings can be ascertained accordingly.
Reinforcement learning . This form of learning is based on using rewards or
incentives to motivate a given action within a given environment. In terms
of distinction between the supervised and unsupervised forms of learning,
the former focuses on learning from a training set of labeled examples;
whereas the latter focuses on finding patterns hidden within unlabeled data.
In contrast, this type of learning focuses on maximizing reward signals.
However, to discover such actions, the machine has to try actions that it
has not selected before. The machine has to not only exploit what it has
already experienced to obtain a reward but also to explore new things to make
better action selections in the future. The dilemma is that exploration and
exploitation go through the process of trial and error.31
Reinforcement learning can improve customized offers of a product or
services for customers based on their responses to each offer. Customers’
responses such as comments, ratings, past preferences, competitors’ actions,
and current public sentiments work as a dynamic environment for the agent.
The agent function can be assigned different goals by firms such as maxi-
mizing profits, sales, or customer engagements. Using reinforcement learning
114 V. Kumar and P. Kotler

can help firms respond to customers’ needs and competitors’ marketing strate-
gies faster and more efficiently than statistical models without knowing the
specific functions of the surrounding environment.

Machine Learning in the Marketing 5.0 World

Machine learning has become an indispensable tool in the field of marketing.
It allows businesses to optimize their marketing strategies by predicting
customer behavior, segmenting audiences, and recommending personalized
content. With ML algorithms, marketers can analyze customer data from
various sources such as social media, website interactions, and purchase
history to gain a deeper understanding of their target audience. This knowl-
edge can then be used to tailor marketing messages and offers to specific
customer segments, increasing the chances of conversion and customer satis-
faction. Expanding on the Marketing 5.0 concept discussed in Chapter 2,
this section presents how ML operates in the Marketing 5.0 world. Particu-
larly, this section discusses five examples of where ML is applied through the
lens of Marketing 5.0 and establishes how such actions can also bode well for
humanity.

Data-Driven Marketing Using ML

One of the key benefits of data-driven marketing using ML is that it allows

marketers to make more informed decisions. By analyzing data, marketers can
gain insights into customer behavior and preferences, which can be used to
develop more effective marketing strategies. Additionally, machine learning
algorithms can be used to automate certain aspects of marketing, such as ad
targeting and content creation, which can save time and resources.
For instance, Lenskart, an online eyewear platform, utilizes machine
learning techniques to enhance the customer experience. By employing these
advanced tools, Lenskart assists customers in selecting the perfect frame,
minimizing uncertainties and the need for product returns or exchanges.
Within the Lenskart application, users are presented with options such as
“curated for you” or “view similar,” which provide personalized recommen-
dations to help them find the ideal product. Through the application of
machine learning on diverse data points, Lenskart ensures that these recom-
mendations are tailored to each customer, making the search process effortless
and efficient.
 5 Transformative Marketing with Machine Learning (ML) 115

Lenskart utilizes various methods to gather customer data and analyze their
behavior. This includes monitoring the products customers view, added to
wishlists, added to carts, and ultimately purchased. Additionally, Lenskart
collects data on customers’ browsing history, buying patterns, sub-brands
purchased, and ratings. By assigning different weights to these interactions
based on their significance (with purchasing being the highest and viewing
being the lowest), Lenskart applies a series of ML algorithms to predict
customers’ future purchases. This data-driven approach allows Lenskart to
personalize the shopping experience and offer tailored selections that align
with individual preferences. As a result, Lenskart enhances customer satis-
faction and drives conversions through the power of ML-driven predictive
analytics.

Predictive marketing using ML

The integration of machine learning into predictive marketing has trans-

formed the way businesses approach customer acquisition and retention. By
harnessing the power of machine learning algorithms, marketers can now
identify potential customers with a high likelihood of conversion and tailor
their marketing efforts to effectively engage and convert these prospects.
Additionally, machine learning can help businesses identify customers who
are at risk of churn, allowing them to implement targeted retention strategies
to keep these customers loyal.
For instance, ASOS, a prominent British fashion and cosmetics e-
commerce company, boasts a vast customer base of more than 25 million
active users across the globe. The company has implemented machine
learning (ML) to enhance its personalization efforts, going beyond recom-
mending similar items to suggest complementary pieces that can create a
cohesive look. To achieve this, ASOS has integrated an ML tool that analyzes,
and groups items based on their attributes, ensuring they match stylistically
and can be worn together.32
The ML model is trained using a dataset called Buy the Look (BTL), which
consists of nearly 600,000 outfits carefully curated by ASOS stylists. This
dataset is derived from ASOS product description pages, ensuring that each
product in the catalog appears at least once as a seed product. By sequen-
tially adding items and re-scoring, new outfits can be generated. Each outfit
comprises a seed product and a variable number of styling products, such as
pairing a dress with a pair of shoes and a bag. ASOS has designed an outfit
template, which consists of specific product types that should be included to
complete the outfit. By harnessing the power of AI and ML, ASOS not only
116 V. Kumar and P. Kotler

stays attuned to evolving consumer trends and preferences but also revolu-
tionizes the way customers engage with their brands. The outcomes have been
remarkable, as evidenced by a remarkable 329% surge in before-tax profits
and a substantial 19% rise in global retail sales throughout the year 2020.

Contextual Marketing Using ML

Contextual marketing encompasses the process of identifying, profiling,

and delivering customized interactions to customers in the physical space,
by comprehending their engagements with the brand’s digital touchpoints.
Machine Learning assumes a critical role in this process, as it empowers the
analysis of a multitude of data points to discern meaningful patterns and
trends.
For instance, McDonald’s Hong Kong implemented a system where
customers could access coupons through their mobile app, which aimed
to promote both new or seasonal items and their regular menu options,
including value combos. However, initially, this process required a lot of
manual effort and consumed a significant amount of time. To address this
issue, the company decided to develop a more efficient and customer-focused
approach by leveraging machine learning and data science techniques.33
Particularly, McDonald’s Hong Kong faced the challenge of effectively
utilizing the vast amount of data collected from their 245 restaurants, which
serve over a million customers daily. To make informed decisions regarding
coupon promotions, they needed to centralize the data, analyze it to make
predictions, and present it in a way that would provide actionable insights
promptly.
The data collected from the central point-of-sale system is now consoli-
dated into a data warehouse, which was created using Oracle. By utilizing
an unsupervised machine learning technique, the ML tool can analyze the
data and provide recommendations for relevant coupon types to individual
customers based on their purchasing behavior, including recency, frequency,
and monetary value. This has significantly improved the company’s ability
to plan targeted coupon campaigns with greater precision. Additionally, the
data-driven approach and ML capabilities have enabled the company to make
objective, analytical decisions that are more effective. As a result, the company
has estimated that the implementation of this ML system has reduced the
time required for planning and executing weekly coupon campaigns by half.
 5 Transformative Marketing with Machine Learning (ML) 117

Augmented Marketing Using ML

The focus of many discussions has been on the advancement of computa-

tional capabilities, but there is also a growing emphasis on enhancing human
intelligence with the help of technology. Intelligence Amplification (IA) is
becoming increasingly important, as it involves utilizing powerful computa-
tional analysis to enhance human abilities. In the field of marketing, IA takes
the form of augmented marketing, where computers act as support systems
for tasks driven by humans. The goal of augmented marketing is to boost
productivity by automating mundane tasks and aiding humans in making
well-informed decisions.
In addition to its applications in business, machine learning is also utilized
in various other fields, including sports. An example of this can be seen
in the 2005 “freestyle” chess tournament hosted by Playchess.com. This
unique competition allowed participants to form teams with either other
players or computers. What made this tournament particularly intriguing
was the involvement of multiple groups of grandmasters collaborating with
computers. It was widely anticipated that a grandmaster paired with a super-
computer would dominate the tournament. However, contrary to expecta-
tions, the winning team consisted of amateur American chess players who
effectively coordinated and coached their three computers. Their ability to
work in harmony with their machines proved to be more successful than the
combination of a skilled grandmaster and a high-powered PC. This remark-
able outcome emphasizes a key takeaway: the efficiency of a partnership
is determined by the way players and computers engage and collaborate.
On this, the chess grandmaster Garry Kasparov opined, “Weak human +
machine + better process was superior to a strong computer alone and, more
remarkably, superior to a strong human + machine + inferior process.”34

Agile Marketing Using ML

Agile marketing, when combined with machine learning, offers a dynamic

and flexible approach to marketing that is highly responsive to customer
needs. Machine learning algorithms can analyze vast amounts of data,
including customer behavior, preferences, and market trends, to identify
patterns and make predictions. This not only increases productivity but also
allows marketers to experiment and iterate more quickly, testing different
approaches and refining their campaigns based on real-time insights.
Consider the case of Amaggi, a Brazilian agribusiness multinational. With
its vast expanse of over 400,000 hectares of productive planted area, the
118 V. Kumar and P. Kotler

company displays the utmost dedication to sustainable practices. Their

commitment is evident through their investment in precision agriculture,
which aims to minimize environmental impacts. Moreover, Amaggi has a
remarkable track record of embracing digital transformation and leveraging
state-of-the-art technology. To gain a comprehensive understanding of crucial
variables and weather-related effects, the Amaggi team recognized the neces-
sity of acquiring additional information beyond what is collected by field
workers and various sensors measuring factors such as humidity, temperature,
and precipitation.35
Amaggi recognized that it was not feasible for humans to monitor the
complex details of extensive farmlands daily, regardless of the number of
people assigned to the task. To address this problem, they partnered with
Planet, a web-geospatial platform that analyzes and shares Earth-related data,
to utilize satellite imagery. By generating alerts, the company could quickly
understand the issues affecting the crops, make informed decisions, and take
prompt action. This approach proves particularly valuable for crops with
longer growth cycles, such as soya and cotton, which typically span from 90
to 180 days. Failing to respond promptly to any anomalies can have a devas-
tating impact on productivity. By utilizing a vast collection of more than 8.7
million images sourced from the Planet database, Amaggi successfully carried
out trend analysis and adopted an agile strategy to tackle the diverse obstacles
it encountered.

Current ML Applications in Marketing

Firms are always looking for ways to improve data literacy and provide tools
to empower knowledge workers to transform data into insights.36 In this
regard, explorative data visualization tools introduced over a decade ago made
it possible to better understand data, distributions and anomalies, outliers,
and noise in the data. In this capacity, ML served to remove the dependency
on a specialist to design and develop interactive dashboards. A similar trend
continues to add augmented intelligence capabilities leveraging Auto-ML.
For instance, NLP search-based interfaces add the ability to interact with
data through text and voice. Just as smartphones have provided advanced
features to users in a point-and-click format, ML too promises to deliver a
similar ease of use. However, recent developments in ML have also generated
significant interest among users who are feeling the need to go beyond the
point-and-click results it provides. As a result, ML has become one of the
most promising research methods in the marketing field, which also holds
 5 Transformative Marketing with Machine Learning (ML) 119

important implications for the development of marketing strategies. This

section presents five specific application areas where ML continues to help
companies in developing marketing initiatives.

Understanding Customer Needs to Deploy ML

The adoption of ML enables firms to refine their recommendations and

promotions to consumers continuously, based on their behaviors over time.
Recommendation engines are a popular application of ML, wherein users are
matched with offerings that they liked in the past and/or may be interested
in the future. Such curative actions by firms reduce the consumer cognitive
load and take the responsibility of finding the best options for a consumer’s
choice context to the search platform or the brand.37
Several ML applications in marketing reflect the attention given by compa-
nies to addressing customer needs. For instance, Uber uses ML to estimate
arrival times for rides, identify optimal pickup locations, estimate mealtimes
on Uber Eats, and detect fraud. FICO uses ML to develop its credit rating
(FICO scores) as well as to assess risks for individual customers. Amazon
uses ML algorithms that can automatically learn to combine multiple rele-
vant features and past search histories and generate individually customized
search results for customers. Further, banks that provide text recognition on
checks through their apps rely on ML tools.38
A significant part of understanding customers’ needs is knowing the price
they are willing to pay for products/services. Retailers can take advantage of
the tremendous power of ML to build effective pricing automation solutions.
For instance, the Nielsen Global Connected Commerce survey found that
searching for product information, checking/comparing prices, and looking
for deals/promotions/coupons are the most popular activities of internet
shoppers.39 As a result, price setting is a critical marketing function and one
that is likely to resonate closely with consumers. For instance, Airbnb uses a
dynamic price tool that recommends prices to its hosts, considering param-
eters such as seasonality, the day of the week, or special events, and more
sophisticated factors such as photos of the property to be rented or the prices
applied in the neighborhood. Other companies such as Amazon and Uber
have adopted similar approaches.40
120 V. Kumar and P. Kotler

Revisiting Firm Capabilities to Integrate ML

The access to detailed and real-time information about various business func-
tions presents important implications for firm capabilities. In this regard,
the data maturity of organizations is undergoing significant changes. A well-
developed, well-endowed, and well-connected data ecosystem is fundamental
to deriving benefits from deep learning and ML capabilities. For instance,
American Express relies on ML algorithms and data analytics to help fraud
detection in near real-time. As a result, the firm is not only able to save
millions in losses, but also reduce time-consuming manual reviews, costly
chargebacks and fees, and denials of legitimate transactions.41 This also
implies that firms will have to invest in data scientists who can extract
meaning from data and identify ways to develop actionable insights for firms.
Further, the adaptability and customization capabilities of ML applications
have enabled marketers to establish personalized means of communication
with their user base. Employees are now able to access all customer data
and information on a point-and-click interface, connect and interact with
other stakeholders involved in the marketing process, and deliver meaningful
content and offerings. The network-wide interactions now made possible by
the power of data are continuously evolving and are expected to bring in
more changes in the business environment. For instance, Taco Bell uses ML
technology in its app to show users the most relevant menu items, promo-
tions, and content based on their individual preferences, past dining history,
location, weather, and restaurant-specific menus and pricing.42
Additionally, for ML initiatives to succeed, ML must be aligned with firm
goals. Essentially, ML must be an organization-wide initiative spanning hier-
archies, functions, and stakeholders. In this regard, given the interdisciplinary
nature of ML capabilities, firms may even want to consider an interdisci-
plinary format of operation, rather than a traditional hierarchy-based format
(e.g., top-down). This would likely better prepare firms to counter the busi-
ness shifts because of AI integration. For instance, Otto, the German online
retailer uses ML capabilities for forecasting purposes that are 90% accu-
rate in forecasting sales for the next 30 days. The retailer has integrated
these capabilities into inventory management based on sales forecasts, thereby
enabling them to plan order shipments and handle customer returns. Further,
such integrated ML capabilities provide Otto the confidence to order over
200,000 items a month from vendors with no human intervention.43 A
distinguishing feature of Otto’s ML implementation is that, unlike Amazon
or eBay, Otto’s efforts focus on non-customer-facing job functions such as
demand forecasting, order management, merchandising, order fulfillment,
 5 Transformative Marketing with Machine Learning (ML) 121

and product returns rather than designing personalized content and offer-
ings for consumers. Such efforts directly work towards valuable cost savings
for Otto.

Designing Marketing Mix Strategies with ML

As mentioned earlier, ML is appropriately positioned to deliver impactful

results to firms by way of personalization. In this regard, firms design
marketing mix strategies that can deliver personalized content and offerings
to users using ML solutions. Personalization occurs when the firm decides,
usually based on previously collected customer data, what marketing mix is
suitable for the individual.44 Academic research has also discussed various
lenses, in terms of personalization.45 Further,46 identify three levels of person-
alization adopted by firms—mass, segment-level, and individual-level. In
mass personalization, firms personalize the same marketing mix offerings to
customers based on customers’ average preferences. While this may not be
a “true” form of personalization, it does involve considering consumer tastes
and preferences in developing offerings. An example of this type of person-
alization can be found in 3D printing. This technology is being used in a
variety of industries such as medical training kits, automobile manufacturing,
and footwear, among others. For instance, Ecco, a Danish footwear manufac-
turer, captures data in real-time, models the sole, and prints the 3D insole,
all within 1 hour.47
In segment-level personalization, firms first create customer segments and
then personalize marketing mix elements according to each segment. An
example of segment-level personalization can be seen in education technology
or edtech. Toppr is a cloud-based learning service in India where students
learn in real-time through an app that not only provides live education
content, but also tests, sample test questions, chats for answering student
questions, and helpful preparation tips for appearing in exams. Other Indian
companies operating in this market include Unacademy and Vedantu.48
Finally, in individual-level personalization, firms personalize the marketing
mix to each customer’s individual needs, tastes, and behaviors. An example of
individual-level personalization is personalized nutrition. In a rapidly growing
market, personalized nutrition aims to provide users with individual-specific
health choices based on personal health metrics. Companies such as Apple
(Apple Watch), Nestle, Amazon (Amazon Fresh), and Uber (Uber Eats)
are looking to grow significantly in this market with relevant personalized
offerings.49
122 V. Kumar and P. Kotler

A comprehensive implementation of ML for personalization can be seen at

HelloFresh, the meal kit and food-delivery service company. To manage the
competition, and make their offerings more customer-friendly, HelloFresh
uses ML algorithms in a multitude of ways. Since they operate on a flexible
subscription-based model, customers can pause their subscriptions indefi-
nitely. This model, while it offers convenience to their customers, offers a bit
of a challenge for the analysts at HelloFresh. As pauses violate the assump-
tions of traditional contractual CLV models that rely on simple parametric
likelihood functions, they had come up with CCV (customer campaign
value)—which measures the profit generated by a customer within each
window between two conversion events.
By reframing customer profitability in this way, they introduced
Morpheus—an algorithm that uses ML techniques to offer weekly customer-
level predictions. Morpheus has 1360 different gradient boosting models,
each trained on a specific customer segment that is defined by a market,
time horizon, customer type, and so on. The algorithm uses hundreds
of predictors from various data sources from HelloFresh’s Enterprise Data
Warehouse, Google Analytics, and third-party datasets that were custom-
built for the company. These predictors provide essential information about
customer engagement, incentives, pricing, ordering patterns, and user behav-
iors, among others. Through these features, Morpheus aids marketers in
predicting future profitability from various perspectives such as customer
segments, customer responses to recipe swaps, product experiences, and so
on.
Morpheus has been integrated across functional departments within
HelloFresh such as marketing, finance, product, and operations. The oper-
ations team uses the insights from Morpheus to answer questions in line
with recent industry trends. The marketing team uses Morpheus to under-
stand the impact of business decisions on consumer behavior and nudge
customers—thus encouraging conversions. Through the individual predic-
tions from Morpheus, HelloFresh can engage in customized and personalized
communication with their customers. In the future, the company aims to
democratize access to high-quality ML models for predictive analytics across
the entire organization.
The impact of personalization initiatives by firms using ML solutions can
be discerned by considering the four primary marketing mix elements—
product, price, promotion, and place. Product personalization is seeing a
steady increase in interest from firms, particularly driven by the prolifera-
tion of channels, especially new electronic channels, and an openness on the
part of customers to interact through a multitude of channels. As a result,
companies are now more equipped to test the omnichannel model, which
 5 Transformative Marketing with Machine Learning (ML) 123

focuses on the interplay between channels and brands.50 In other words, the
omnichannel extends beyond the typical channel management strategies to
include a seamless transition between channels and superlative user experi-
ence.51,52 Firms have gone beyond the “Recommendations for You” feature
offered by Amazon and Netflix. For instance, Netflix personalizes the artwork
of movie titles based on ML algorithms that can pick out which images
may best resonate with the users. Additionally, they also have plans to create
personalized movie trailers based on the streaming histories of individual
viewers.53
Personalization via prices operates on the concept that customers derive
varying levels of utility from firm offerings, and therefore vary in their will-
ingness to pay.54 In this regard, personalization of pricing can happen based
on location, seasonality, and stated preferences of users, among others. ML
continues to be used in such a form of personalization, owing to its rich data
and analytic capabilities with information. For instance, the Munich-based
Bavaria Boutique Hotel has implemented an AI/ML-driven pricing solution
that considers the entire customer journey of potential guests, checks the
prices and offers of relevant competitors (in Munich and the surrounding
areas), accounts for important social events happening in the region, inte-
grates additional costs of online travel platforms, and considers organizational
key performance indicators (KPIs), among others, in generating appropriate
price recommendation multiple times during the day in real-time. This
approach is markedly different from the typical approach of setting room
rates that were set manually based on experience. Such a pricing solution
is expected to optimally determine room rates with the market, thereby
improving turnover.55 ML is also being used in traditional retail settings
to determine the pricing strategy. For instance, Walmart has set up a cloud
network driven by ML algorithms that constantly feeds data and analytics to
store employees in real time. This has allowed them to stay competitive with
Amazon on pricing, whereby they can adjust prices at its physical locations
almost instantly across entire regions.56
Personalization activities in promotion have received a significant uptick in
attention since the availability of individual-level data.57 The individual-level
data allows firms to perform a wide range of customer-related actions such
as audience segmentation, dynamic online content creation, targeted promo-
tional offers and discounts, and personalized campaigns, among others. Firms
are increasingly using ML algorithms to drive such promotional activities.
For instance, the Kansas City Chiefs are using ML algorithms to improve
the fan experience. A decision cloud platform allows the team to connect
124 V. Kumar and P. Kotler

multiple levels of fan data to many different offers, promotions, and solic-
itations. Additionally, the ML solution allows the team to ensure that the
promotional content and offers are delivered only to those fans who would
be most likely to purchase, and not cannibalize their retail sales.58
Personalization via the place element has changed significantly since the
inception of e-commerce. What traditionally pertained to the physical loca-
tions of firms, now applies also to their online presence. For instance,
Mystore-E, a Tel Aviv-based clothing store, has designed its stores to mimic
the experience of a website within a store.59 Using digital displays and
augmented reality, customers can virtually try on products. With ML capa-
bilities, employees then receive notifications that match customers’ choices
to provide highly personalized and curated offerings. Such initiatives provide
customers and firms the ability to respond immediately to communication
messages initiated by either party. Other instances of personalization that blur
the distinction between physical and digital space include Macy’s On Call (a
mobile digital assistant that personalizes the customer’s shopping experience
and provides recommendations and directions to items around the store),60
and Hilton’s Connie (a robot concierge that uses NLP capabilities to provide
personalized recommendations of places to visit and restaurants to try for the
guests),61 among others.

Driving customer engagement through ML

Traditional customer relationship management was based on the notion of

differences in the cost of serving customers. With the increase in automa-
tion, the heterogeneity in the cost of serving customers decreases. This
implies that the main difference in customer profitability on digital plat-
forms is driven by customer retention and the gross margin provided by the
consumers. In other words, in the new-age technology world, customer prof-
itability must be viewed from a different viewpoint. The ML algorithms run
on customer transaction data, among others, to improve their predictions.
The algorithms also benefit from customer heterogeneity regarding customer
preference, demographics, transaction frequency, and spending potential.
Training of ML algorithms behind the curation engines, and the voice or
image recognition software requires product preference inputs across a gamut
of customers to better discriminate between products preferred by the highly
profitable customers and low profitable customers. Further, the lower cost of
serving customers implies that firms can make personalized product recom-
mendations and serve customers across a range of profits. This implies that
the knowledge value of customers (i.e., information voluntarily shared by
customers to the firms towards the enhancement of future firm offerings)
 5 Transformative Marketing with Machine Learning (ML) 125

increases with the marginal improvement of the ML algorithms’ predictive

accuracy provided by the customers’ transactions.62 As a result, high knowl-
edge value customers need not necessarily be higher profitable customers or
customers with a high referral value.
Companies such as Google, Netflix, and Amazon that are geared towards
building network effects (i.e., providing products for free or a nominal
subscription), also focus on broadening their user base. The data collected
from the portfolio of offerings (i.e., Google Search, Gmail, Amazon Prime)
provides the basis for the development of recommendation algorithms that
then provide autocomplete/recommendation results for search terms, emails,
movies, music, related articles, and similar product bundles.
The success of an engagement strategy is dependent on customers devel-
oping an emotional attachment to the firm.63 Even though customers may
not prioritize direct engagement with firms, many firms such as Wendy’s,
Target, Patagonia, Chick-fil-A, and Whole Foods continue to trigger conver-
sations about social topics and issues that are important to consumers
to interact directly with customers, and thereby achieve a deeper level of
engagement.64 Firms are realizing that designing and delivering personal-
ized experiences for multiple customer preferences and engagement segments
constitute a valuable customer engagement strategy. In this regard, new-
age technologies (and particularly ML) enable companies such as Disney,
Amazon, Netflix, and Google to deliver such personalized experiences in
physical and online environments.

Designing Digital Strategies with ML

The new-age technology landscape, including ML capabilities, places firms

in an ecosystem that is characterized by smart objects that deliver intuitive
digital services across an ever-expanding network of various stakeholders. The
creation of such an ecosystem consisting of new-age technologies (including
ML), essentially consolidates multiple functionalities on one digital platform
thereby contributing towards increasing consumer convenience. Consumers
benefit from the offers and rewards that the firm provides within this
ecosystem. The machine-to-human interaction capabilities that the firm
develops serve important roles in improving consumer welfare as they can
provide convenience, peace of mind, and timely insights to consumers.
Consumers can assign relatively straightforward tasks or queries to intelligent
agents, thus minimizing their effort. By analyzing data on broader trends
as well as individual behaviors, a firm can develop targeted and individually
relevant offers and solutions for their customers.
126 V. Kumar and P. Kotler

Firms are cognizant of the potential of ML and new-age technologies

in furthering their digital strategies. For instance, fashion retailer Burberry
uses ML capabilities and big data to identify counterfeit products, improve
sales, and build and enhance personal relationships with customers. To do
so, Burberry uses data gathered from its reward and loyalty programs to
develop personalized digital and in-store shopping experiences for individual
customers. Other instances of digital strategies adopted by firms include
Uber’s use of ML capabilities to estimate arrival times for rides, identify
optimal pickup locations, estimate mealtimes on UberEATS, and detect
fraud; FICO’s use of ML capabilities to develop its credit rating (FICO
scores) as well as to assess risks for individual customers; and Amazon’s use
of ML algorithms that can automatically learn to combine multiple relevance
features and past search histories, and to generate individually customized
search results for customers.

Future of ML in Marketing
Given ML’s proficiency and veracity in powering digital initiatives within
firms, the future looks firmly entrenched in a digital, learning environment.65
Such a development could raise questions on the relevance of customer
relationship management (CRM) technologies currently adopted by many
companies worldwide. In other words, will ML (and potentially other new-
age technologies) replace CRM technologies? This is an important issue
as companies have invested millions into setting up their current CRM
infrastructure.
Research has posited that new-age technologies can potentially augment
the capabilities of existing CRM technologies by enhancing the efficiency,
effectiveness, responsiveness, and personalization of marketing strategies and
activities.66 For instance, ML can help CRM systems by automating routine
tasks such as data input, forecast updating, determination of call lists,
and other routine customer management tasks. By helping CRM systems
identify behavioral patterns and preferences, they can automate and person-
alize customer responses, communication material, data collection, pricing
quote generation, and other customer management actions. Over time, ML
algorithms can expedite customer segmentation, lead customization, and
marketing element customization. Employees can thus productively apply
their time toward relationship-building and engagement activities. Similarly,
other new-age technologies can complement CRM systems and capabilities
firms have in place currently. Overall, the new-age technologies can work
 5 Transformative Marketing with Machine Learning (ML) 127

well with existing CRM technologies; and through such a combination firms
would realize enhanced value creation. In this regard, the future of ML for
marketing purposes appears to be promising and varied. While we can expect
progress in ML capabilities in many organizational areas, three areas that
stand out are discussed here.

ML and Customer Churn Analytics

Managing customer churn is a prickly issue impacting businesses across

several industries such as telecommunications, financial services, retailing,
and e-commerce, among others. When faced with customer churn, managers
face several important questions such as: (a) How do we identify the
customers who are likely to churn? (b) When are they likely to churn? (c)
Should we intervene and, if so, when? and (d) What should the interven-
tion offer(s) be to prevent churn? When left unaddressed, customer churn
can prove very costly to a company, and could negatively impact the firm’s
performance in four ways. First, firms could lose out heavily on the revenue
stream due to customer churn. Second, it becomes difficult for a firm to
break even as it would have lost the opportunity to recover the acquisition
cost from the churned customer. Third, a firm would also lose the opportu-
nity to up-sell/cross-sell to customers who have defected, thereby causing a
loss of potential revenue. Finally, potential negative word-of-mouth from the
defected customers impacts future customer acquisition of a firm.
Before the advent of new-age technologies, research studies used exten-
sive statistical modeling to address this issue. Using tests and control groups
was a popular technique that could adequately demonstrate the impact of
customer intervention strategies. For instance, using such intervention strate-
gies, a telecom firm realized a net revenue gain of $345,000 (after accounting
for the cost of intervention) and, an 860% increase in ROI.67 However,
in the current era of new-age technologies firms are increasingly looking
toward ML-based algorithms to counter customer churn. The ML algorithms
could work in tandem with existing customer management models that can
effectively address customer churn.
Addressing churn can also be a challenge in an ML-enabled environ-
ment.68 The challenge relates to how firms use machines (and ML algo-
rithms) to interact with consumers. As machines become more conversant
and interactive, firms must be careful in ensuring that machines accurately
capture and transmit the firm’s (or brand’s) personality. Additionally, firms
must also understand how to engender consumer trust through ML algo-
rithms. This calls for firms to move away from the static imagery often
128 V. Kumar and P. Kotler

involved in display advertising and media-related messages typically involved

in intervention offers to a dynamic and interactive environment of voice-
enabled virtual assistants and virtual reality.
In implementing human-machine combinations, research has identified
the existence of an uncanny valley when balancing the deployment of virtual
assistants to completely reflect humans versus maintaining some artificiality.
The uncanny valley hypothesizes that a person’s response to a humanlike
robot would abruptly shift from empathy to revulsion (and even eeriness)
as it approached, but failed to attain, a lifelike appearance.69 In this regard,
recent field implementations that involved human–machine interactive envi-
ronments have demonstrated uneasiness in the humans involved.70 Firms
such as Poncho (from the Weather company), Slack, and Autodesk are trying
to find the right balance for their AI bots between providing a human versus
a machine interface.
However, recent advancements in ML have gained tremendous precision
and the distinction between human-created and machine-created content is
barely visible. This has led to a situation where people are slowly developing
an appetite for such content and offerings. Examples of such solutions include
Adobe’s Adobe Cloak (a video editing tool) and Lyrebird (a voice imita-
tion algorithm), among others.71 (see Image 5.3). All these instances suggest
that firms should design sophisticated multi-sensory solutions that provide
personalized attention to users and must understand the human-machine
interface to design effective customer intervention actions to successfully
address churn.

Improvement to demand forecasting

Effective demand management allows firms to better plan and employ firm
resources that can ultimately create more value for them and their customers.
By leveraging the power of insights enabled by ML algorithms, firms can
identify upcoming trends and craft responses in anticipation (e.g., design new
offerings, update delivery mechanisms, etc.). The interconnectivity between
business functions and the automation of analytical and business processes
can help firms respond to these trends more efficiently and effectively. By
anticipating customer needs, firms can surprise and delight customers with
offerings that are aligned with their requirements.
Many firms gainfully employ ML algorithms for a wide range of actions
that collectively help them manage demand and ensure users always have
the best experience. For instance, the online streaming platform Netflix uses
ML algorithms for making various predictions such as network quality to
 5 Transformative Marketing with Machine Learning (ML) 129

Image 5.3 Video and Music Editing Software. Video and music editing software
work in tandem with humans to create content that can be personalized and highly
engaging
(Source Photo by Jakob Owens on Unsplash)

determine the quality of video to provide; drop in network connectivity; and

predicting what a user will play next in his viewing list to cache the video in
the device before the viewer hits play, enabling the video to start faster and/or
at a higher quality, among others.72 Such predictions allow Netflix to effec-
tively plan its video lineup that satisfies user expectations. Other examples of
ML use towards forecasting include the case of Domino’s predicting when
orders will be ready;73 and Kraft Heinz towards demand forecasting during
major events such as the Super Bowl, and for aiding in restocking decisions
at retail outlets.74
As a result of more granular insights, increased automation, and greater
interconnectivity of business functions, firms can improve their product
development and enhancement processes and achieve process optimization.75
In the future, we can expect this trend to only continue and bring plentiful
gains to firms and consumers. Some areas that are already seeing impressive
progress in this regard include applications such as smart warehousing and
smart transportation enable intuitive demand fulfillment, warehouse automa-
tion, and route optimization for maximum efficiency (see Image 5.4). For
instance, Volvo employs ML capabilities to predict failure and breakdown
rates to determine the inventory volume of spare parts.76 As firms continue to
invest more resources into ML development, a prescient approach to demand
forecasting can be developed that can drive more value for firms and users.
130 V. Kumar and P. Kotler

Image 5.4 Machine Learning-powered Warehousing Solutions. Machine learning

solutions deployed at warehouses aid in demand fulfillment, warehouse automation,
and route optimization for maximum efficiency
(Source Photo by Nana Smirnova on Unsplash)

Strategy Development for Customers and Products

The continuous developments made in ML algorithms ultimately get tested

in business settings to see the real-world impact. Such developments lead to
ML-based solutions that are instrumental in enabling firms to (a) manage
customers, (b) develop new products/product concepts, (c) enhance promo-
tion strategies, and (d) create effective brand-customer engagement. Among
other activities, the insights from ML solutions can help firms manage their
existing customers’ needs and develop new products to cater to evolving
consumer needs at an individual level.
An important area where ML continues to contribute towards strategy
development in a firm-customer interface is the area of chatbots and intel-
ligent agents (see Image 5.5). Using NLP, chatbots and intelligent agents
can communicate like humans. Specifically, using technologies like deep
learning, genetic algorithms, and natural language processing, machines can
be trained to generate insights to accomplish specific tasks by processing large
amounts of data and recognizing patterns in the data that are employed for
personal and business uses. Popular solutions for personal uses that involve
 5 Transformative Marketing with Machine Learning (ML) 131

ML include personal assistants (e.g., Alexa, Siri, Cortana), travel planning

(e.g., Mezi), music (e.g., Pandora), financial planning (e.g., Olivia), language
translation (e.g., Liv), and smart-home solutions (e.g., Nest), among others.
Similarly, popular solutions for business uses that involve ML include plug-
and-play solutions for business needs (e.g., Fluid AI), e-commerce and digital
marketing (e.g., Sentient), process automation (e.g., Amazon MTurk), face
recognition (e.g., Haystack), legal language assistant (e.g., Legal Robot), and
credit scoring (e.g., Lenddo), among others. Such intelligent agents can
respond to basic user queries and recognize and respond accordingly. Addi-
tionally, in a customer interface, such agents know when customers need to be
transferred seamlessly to human representatives, leading to efficient customer
service and lower costs.
Even the e-commerce domain is expected to be irreversibly impacted by
ML capabilities that can positively impact strategy development. For instance,
ML solutions such as shopping bots can monitor and compare prices, suggest
repurchases, and even make purchases on behalf of humans via bot-to-bot
interactions. Overall, ML can help firms master knowledge of consumer pref-
erences, and deliver personalized products, pricing, and advertising content
through relevant channels. Such actions, in the future, can help further

Image 5.5 Chatbots and intelligent agents. Chatbots and intelligent agents use ML
capabilities to assist customers in making informed choices
(Source Photo by Matthew Henry from Burst)
132 V. Kumar and P. Kotler

strategy development for products and customers to extract more value for
all.

Key Terms and Related Conceptualizations

The process of discovering interesting

patterns in databases that are useful in
Data mining decision-making
ETL (extract/transform/load) process Extracting the data from various sources,
transforming it for ML algorithms, and
loading it into a structured schema
applicable to ML processes
Individual-level personalization Firms personalize the marketing mix to
each customer’s individual needs, tastes,
and behaviors
Intelligence amplification Using powerful computational analysis to
enhance human abilities
Machine learning Deals with the process of training
machines to learn over time.
Mass personalization Firms personalize the same marketing mix
offerings to customers based on
customers’ average preferences
Personalization A strategy deployed by the firm, usually
based on previously collected customer
data, on what marketing mix is suitable
for an individual
Reinforcement learning, or semi-supervised Models where the machine is not told
learning which action(s) to take, rather it must
discover which action(s) yield the
highest reward by trying them
Segment-level personalization Firms first create customer segments and
then personalize marketing mix
elements according to each segment
Structured data Any data that resides in a database under
specific fields with clearly defined values
Supervised learning models Models where the learning system uses
prior data as training information and
accordingly presents related predictions
for all future outcomes.
Uncanny valley The hypothesis that a person’s response
to a humanlike robot would abruptly
shift from empathy to revulsion (and
even eeriness) as it approached, but
failed to attain, a lifelike appearance
Unstructured data A single data unit in which the
information offers a relatively
concurrent representation of its
multifaceted nature without predefined
organization or numeric values.
Unsupervised learning models Models that make the machine learn
about performing a task without
providing explicit instructions on how
to do it
 5 Transformative Marketing with Machine Learning (ML) 133

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USD 59 billion in 2020. This is expected to grow to USD 250
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06, 2023, from https://www.statista.com/outlook/tmo/artificial-intell
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(10.6%), and security (10.1%). Further, the report identifies the USA,
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21. Shopify uses ML solutions to determine the closest and most effi-
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demand and inventory allocation, and route orders to the closest fulfill-
ment center based on inputs like locations of businesses, product
details, shopping behaviors, etc.; Cannon, J. (2019), Shopify launches
machine learning powered network for US merchants. Shopify, June
 5 Transformative Marketing with Machine Learning (ML) 135

20, accessed from https://martech.org/shopify-launches-machine-lea

rning-powered-network-for-us-merchants/.
22. Quotient Health uses ML to design electronic medical record systems
that are optimized and standardized to lower medical costs; and PathAI
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of new-age technologies on marketing: A research agenda,” Journal
of Business Research, [accessed from https://www.sciencedirect.com/sci
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available data, to better understand its devices and customers.
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models.
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 5 Transformative Marketing with Machine Learning (ML) 137

43. Bughin, J., E. Hazan, S. Ramaswamy, M. Chui, T. Allas, P. Dahlström,

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45. Research contends personalization to be a largely firm-controlled
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S., and S. Sarkar (2003), “The role of the management sciences
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model for marketing,” Journal of Interactive Marketing, 20 (1), 1–16).
Additionally, research has conceptualized personalization as a process
that interlinks customers and marketers (Murthi, B. P. S., and S.
Sarkar (2003), “The role of the management sciences in research on
personalization,” Management Science, 49 (10), 1344–1362), and that
interaction solidifies the relationship between customers and marketers
(Simonson, 2005; Wind, J., and A. Rangaswamy (2001), “Cus-
tomerization: The next revolution in mass customization,” Journal of
Interactive Marketing, 15 (1), 13–32).
46. Bleier, A., A. D. Keyser, and K. Verleye (2018), “Customer engagement
through personalization and customization,” in Customer Engagement
Marketing, R. W. Palmatier, V. Kumar, and C. M. Harmeling (Eds.),
pp. 75–94.
47. Vinoski, J. (2020), “New research shows consumers already expect
mass personalization. time to get ready!” Forbes, January 20, [accessed
from https://www.forbes.com/sites/jimvinoski/2020/01/20/new-res
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get-ready/#44fed95a223e].
48. Sriram, M. (2019), “Toppr launches live classes to boost growth,”
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1566813568679.html].
138 V. Kumar and P. Kotler

49. Fitzgerald, M. (2020), “Personalized nutrition could be the next

plant-based meat, worth $64 billion by 2040, says UBS,” CNBC ,
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50. Verhoef, P. C., P. K. Kannan, and J. J. Inman (2015), “From Multi-
channel retailing to omni-channel retailing: introduction to the special
issue on multi-channel retailing,” Journal of Retailing, 91(2), 174–81.
51. Further, a survey by the CMO Council and SAP Hybris found that
47 percent of consumers would abandon a brand that delivers poor,
impersonal, or frustrating experiences.
52. Brynjolfsson, E., Y. J. Hu, and M. S. Rahman (2013), “Competing
in the age of omnichannel retailing,” MIT Sloan Management Review,
54 (4), 23–29.
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AI,” CBS News, August 19, [accessed from https://www.cbsnews.com/
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54. Esteves, R. B., and J. Resende (2016), “Competitive targeted adver-
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Amazon,” Reuters, February 14, [accessed from https://www.reuters.
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57. Wedel, M., & P. K. Kannan (2016), “Marketing analytics for data-rich
environments,” Journal of Marketing, 80 (6), 97–121.
58. Vaccaro, A., S. Mager, N. Groff, and A. Bolante (2019), “Beyond
marketing: Experience reimagined,” Deloitte Insights, January 16,
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note-sup-3].
59. Windyka, K. (2018), “In-Store platform uses AI to digitally
personalize shoppers’ experience,” PSFK , September 11, [avail-
able at https://www.psfk.com/2018/09/mystore-e-ai-personalized-sho
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 5 Transformative Marketing with Machine Learning (ML) 139

60. White, D. (2016), “Artificial intelligence transforms the in-store shop-

ping experience with the pilot of “Macy’s On Call”,” IBM , July 20,
[accessed from https://www.ibm.com/blogs/watson/2016/07/artificial-
intelligence-transforms-store-shopping-experience-pilot-macys-call/].
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concierge,” USA Today, March 9, [accessed from https://www.usa
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connie-hiltons-new-robot-concierge/81525924/].
62. Kumar, V., B. Rajan, R. Venkatesan, and J. Lecinski (2019), “Under-
standing the role of artificial intelligence in personalized engagement
marketing,” California Management Review, 61(4), 135–55.
63. Pansari, A., & V. Kumar (2017), “Customer engagement: the
construct, antecedents, and consequences,” Journal of the Academy of
Marketing Science, 45 (3), 294–311.
64. Venkatesan, R. (2017), “Executing on a customer engagement
strategy,” Journal of the Academy of Marketing Science, 45, 289–293.
65. Kumar, V. (2021). Intelligent marketing: Employing new age technologies.
Sage Publications.
66. Kumar, V., D. Ramachandran, and B. Kumar (2020), “Influence
of new-age technologies on marketing: A research agenda,” Journal
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67. Kumar, V. (2008), Managing Customers for Profits, Upper Saddle River,
NJ: Wharton School Publishing.
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standing the role of artificial intelligence in personalized engagement
marketing,” California Management Review, 61(4), 135–55.
69. Mori, M., K. F. MacDorman, and N. Kageki (2012), “The uncanny
valley,” IEEE Robotics & Automation Magazine, 19 (2), 98–100.
70. These instances include (a) consumers experiencing uneasiness when
they first used a driverless car (Knight, W. (2016), “Novelty of driver-
less cars wears off quickly for first-timers,” MIT Technology Review,
October 18, [accessed from https://www.technologyreview.com/s/602
689/novelty-of-driverless-cars-wears-off-quickly-for-first-timers/]), (b)
users inclined to believe human forecasters more than machines, even
when the machines are more accurate (Dietvorst, B. J., J. P. Simmons,
and C. Massey (2016), “Overcoming algorithm aversion: People will
use imperfect algorithms if they can (even slightly) modify them,”
Management Science, 64 (3), 1155–1170), and (c) doctors exhibiting
lack of trust with recommendations from IBM Watson about medical
140 V. Kumar and P. Kotler

diagnostics (Polonski, V. (2018), “People don’t trust AI—here’s how

we can change that,” phys.org, January 10, [accessed from https://phys.
org/news/2018-01-people-dont-aihere.html]), among others.
71. Upson, S. (2017), “Artificial intelligence is killing the uncanny valley
and our grasp on reality,” Wired , December 16, [accessed from https://
www.wired.com/story/future-of-artificial-intelligence-2018/].
72. Ekanadham, C. (2018), “Using machine learning to improve
streaming quality at Netflix,” Netflix Tech Blog, March 22, [accessed
from https://netflixtechblog.com/using-machine-learning-to-improve-
streaming-quality-at-netflix-9651263ef09f].
73. Whitehead, S. A. (2020), “What pizza operators can learn from
Domino’s use of AI,” Pizza marketplace.com, January 15, [accessed
from https://www.pizzamarketplace.com/articles/what-all-pizza-operat
ors-can-learn-from-dominos-use-of-ai/].
74. Himes, M. (2020), “AI is coming to a grocery store near you,”
BuiltIn.com, January 29, [accessed from https://builtin.com/artificial-
intelligence/kraft-heinz-machine-learning-ai].
75. Davenport, T. H., and R. Ronanki (2018), “Artificial Intelligence for
the Real World,” Harvard Business Review, 96 (1), 108–116.
76. Marr, B. (2016), “Big data at Volvo: predictive, machine-learning-
enabled analytics across petabyte-scale datasets,” Forbes, July 18,
[accessed from https://www.forbes.com/sites/bernardmarr/2016/07/
18/how-the-connected-car-is-forcing-volvo-to-rethink-its-data-str
ategy/#3ea34de13e8d].
 6
Transformative Marketing with Metaverse

Overview
Imagine a world in which the lines separating the real and virtual vanish,
allowing people to travel through gorgeous landscapes, meet up with friends
for a game on the other side of the globe, or create something entirely original
and personalized. Welcome to the Metaverse!
The metaverse is a revolutionary frontier that is capturing people’s atten-
tion globally as the digital world develops at an unprecedented rate. The
concept of the metaverse encompasses a range of interconnected virtual
realms that can be accessed through augmented and virtual reality technolo-
gies. Rather than being limited to a two-dimensional screen, it expands into
a three-dimensional existence. Within these digital spaces, individuals have
the freedom to assume any identity, engage in various activities, and establish
connections that surpass the boundaries of the physical realm.
The metaverse is built upon a complex network of interconnected tech-
nologies such as virtual reality (VR), augmented reality (AR), blockchain,
artificial intelligence (AI), and others. These technologies work together
seamlessly to provide users with an immersive and unified digital experience.
They are the foundation of a transformative era that is reshaping our inter-
actions, collaborations, and the formation of communities within the digital
world. Metaverse, which initially emerged from the gaming industry, has now
extended its impact beyond that domain. It now encompasses virtual market-
places, educational platforms, social gatherings, and professional conferences,
forming a diverse ecosystem that is revolutionizing businesses and reshaping
our online interactions.

© The Author(s), under exclusive license to Springer Nature 141

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_6
142 V. Kumar and P. Kotler

The metaverse has become a focal point for the business world as it seeks
to establish connections with its target audience. Major players such as Meta
(formerly known as Facebook), Microsoft, and Nvidia Corporation are dedi-
cating substantial financial resources to constructing a digital realm that aligns
with the concept of the metaverse. Not only are retail giants like Gucci,
Nike, and Gap venturing into the metaverse to explore customer engage-
ment possibilities, but entertainment brands like Disney, fast-food chains like
McDonald’s and Chipotle, and professional sports brands like the Atlanta
Braves are also joining the ranks of companies interested in leveraging the
metaverse for interaction and involvement.
This chapter is organized in the following manner. First, a brief history
of the origin of the metaverse is presented, followed by a definition of the
metaverse (from a marketing standpoint), along with vignettes about the
metaverse’s usage and applications. Then, the role of the metaverse in the
Marketing 5.0 concept is explored. Next, some marketing applications of the
metaverse are discussed. Finally, the future of the metaverse for the marketing
industry is envisioned via emergent issues in this area.

Origin, Definition, and Classifications

of the Metaverse
Origin

Neal Stephenson is credited with coining the term “metaverse,” which he

introduced in his 1992 novel Snow Crash. In this literary work, Stephenson
vividly portrays a virtual world that can be accessed by countless individuals
through personalized avatars and creative tools.1
Relatedly, the late 1980s-early 1990s period saw the invention and intro-
duction of the Internet, which brought about revolutionary changes that now
shape our way of life. The notions of digital twins, bitcoins, the “fifth age”
of virtual worlds,2 etc., first appeared in the late 1990s and early 2000s. In
the decade of the 2010s, there were decentralized virtual worlds, augmented
reality (AR) games such as Fortnite (See Image 6.1) and Pokémon Go (See
Image 6.2), and non-fungible tokens (NFTs). These are a few of the signif-
icant occasions that have shaped the development of the networked virtual
and user-generated worlds, which are all reachable via the Metaverse user
interface.3
 6 Transformative Marketing with Metaverse 143

Image 6.1 Fortnite. A person playing Fortnite on a mobile device

(Source Photo by Erik Mclean on Unsplash)

Image 6.2 Pokémon Go. A person playing Pokémon Go on a mobile device

(Source Photo by Mika Baumeister on Unsplash)
144 V. Kumar and P. Kotler

Definition

Considering its nascency, there is no consensus in academic research on the

definition of metaverse. The metaverse was originally imagined as a virtual
reality environment that was semi-physical and in which users interacted
through avatars.4 According to research conducted in the late 2000s, the
metaverse is an immersive virtual environment that is three-dimensional and
allows users to interact with both software agents and other users.5 Consis-
tent with the singular-world viewpoint, studies have recognized the scalable
and social nature of the metaverse, characterizing it as a virtual environ-
ment that facilitates the simultaneous engagement of numerous individuals in
social interactions.6 According to articles in the popular press, the metaverse
is the meeting point of the real world and the virtual world. Here, the conver-
gence of web technologies, extended reality, and the internet has led to the
conceptualization of the metaverse as a virtual environment that combines
the physical and digital.7
The metaverse has evolved alongside technological advancements,
expanding from a singular virtual world to a more comprehensive concept
encompassing multiple interconnected virtual worlds. It has transitioned
from a purely virtual representation to a blended reality perspective, incorpo-
rating various experiences along the extended reality spectrum, such as virtual
reality, augmented reality, mixed reality, and the convergence of other tech-
nologies.8 In essence, the metaverse is now perceived as a hyper-connected
digital universe, seamlessly interlinking different virtual realities. Investing
time and resources in the metaverse is becoming increasingly popular in
today’s society.9 Moreover, it offers the opportunity to connect with others
effortlessly, opens up new avenues for employment, and allows individuals to
express themselves in unique ways.
Metaverse is being widely applied in the field of Information Technology
(IT).10 On the other hand, the education sector is also embracing technology
to enhance learning engagement and effectiveness.11 By incorporating the
metaverse into the learning process, students are provided with a unique expe-
rience and a virtual space for socializing, fostering their creativity. Moreover,
the metaverse enables learning materials to be tailored to individual students,
promoting a student-centered approach to education.12 The interconnected-
ness and immersive nature of the metaverse set it apart from other online
experiences, making it even more appealing. Businesses can leverage this
understanding to make informed investments in the right type of metaverse.
 6 Transformative Marketing with Metaverse 145

Classification

Metaverses can be categorized into two types: traditional and blockchain-

based. Traditional metaverses are typically centralized and do not utilize
blockchain technology. In a traditional metaverse, a single company owns
and operates the entire virtual world, giving them complete control over all
aspects of the metaverse. This centralized approach allows for real-life activi-
ties to be performed with a certain level of accuracy, remote collaboration to
create new products, and enhanced customer experiences. The metaverse is
governed by internal servers and rules, ensuring that one entity oversees the
entire network.
On the other hand, blockchain-based metaverses are decentralized and
owned by the community. In these metaverses, no single entity has control
over the virtual world, and users have ownership and control over their data
and assets. The virtual communities within these metaverses operate within
the boundaries set by the community. With decentralization, users gain more
power over the administration of the metaverse, allowing them to expand the
universe and create immersive experiences for each other. In this model, the
creators of the metaverse oversee the platform rather than a central authority,
promoting a more democratic and inclusive environment.
Despite being in its early stages, the metaverse has already witnessed the
initial steps towards a digital revolution. Prominent global corporations are
dedicating substantial resources to the advancement of metaverse platforms
and technologies. Simultaneously, independent creators are crafting mesmer-
izing virtual worlds and immersive encounters, challenging the boundaries of
what can be accomplished. Table 6.1 provides the types of metaverses and
exemplar offerings that represent opportunities and utilizations within the
metaverse.

Metaverse in the Marketing 5.0 World

Online and virtual marketplaces have revolutionized customer loyalty and
demand by harnessing cutting-edge technologies like AI, ML, and others.
These advancements enable businesses to decipher shopping habits, compre-
hend customer order patterns, and tailor user experiences accordingly. The
concept of the Metaverse, which has been extensively discussed in this
chapter, represents a virtual realm that seamlessly merges the physical and
digital worlds. This integration is made possible by the convergence of
internet and web technologies with extended reality. Within this dynamic
 146

Table 6.1 Types of metaverses

Type of
metaverse Meaning Traditional example Blockchain-based example
Gaming Primarily focus on providing gaming and Fortnite (https://www.fortnite.com), The Sandbox (https://www.
interactive entertainment experiences, Roblox (https://www.roblox.com/) sandbox.game), Axie
centering around gaming mechanics that Infinity (https://axieinfinity.
enable users to participate in gameplay, com/)
hunts, and explore virtual worlds.
Social Encompasses various aspects of social VRChat (https://hello.vrchat.com/), Second Somnium Space (https://som
interaction, communication, and Life (https://secondlife.com) niumspace.com/)
collaboration; fosters connections and
V. Kumar and P. Kotler

facilitates the meeting of new individuals

as well as the strengthening of existing
relationships.
Commerce Users engage in the buying and selling of Shopify (https://www.shopify.com) Decentraland (https://decent
virtual goods and services within a raland.org/)
virtual environment that serves as a
virtual marketplace, facilitating business
transactions and e-commerce activities.
Type of
metaverse Meaning Traditional example Blockchain-based example
Education Enhances the educational journey and AltspaceVR Engage (https://engage
possibilities for its users by offering a vr.io/)
virtual setting where students can attend
classes, collaborate on group projects,
and engage with fellow learners and
instructors.
Enterprise An immersive digital environment that Microsoft Mesh (http://www.microsoft. Cryptovoxels
aims to optimize experiences and com/mesh), NVIDIA Omniverse (https://
decision-making by replicating and www.nvidia.com/en-us/omniverse/)
connecting all aspects of an
organization, through the development
of digital twins.
Sources “Types of Metaverse Explained: A Comprehensive Overview,” March 8, 2023, https://mudrex.com/blog/types-of-metaverse-explai
ned/; “Enterprise Metaverse—The new way of business,” https://www.leewayhertz.com/enterprise-metaverse
6 Transformative Marketing with Metaverse
147
148 V. Kumar and P. Kotler

environment, data modeling tools play a crucial role in optimizing customer

engagement behaviors and purchasing habits. Extensive research indicates
that by utilizing customer engagement tools within immersive virtual spaces,
businesses can create personalized digital shopping experiences that resonate
with individual preferences and needs. Expanding on the Marketing 5.0
concept discussed in Chapter 2, this section presents how the metaverse
operates in the Marketing 5.0 world. Particularly, this section discusses five
examples of where the metaverse is applied through the lens of Marketing 5.0
and establishes how such actions can also bode well for humanity.

Data-Driven Marketing Using the Metaverse

The metaverse provides marketers with a unique platform to engage with

consumers in a more immersive and interactive manner. By leveraging data-
driven marketing techniques within the metaverse, marketers can create
personalized experiences that captivate and engage users on a deeper level.
This can include virtual product demonstrations, interactive advertisements,
and even virtual events and experiences. By utilizing the metaverse for
data-driven marketing, marketers can not only enhance their understanding
of their target audience but also create more impactful and memorable
marketing experiences that drive brand awareness and loyalty.
For instance, Decentraland is an Ethereum-based virtual reality platform
where users can buy, create, and monetize virtual land using their cryptocur-
rency, MANA. It offers a decentralized environment for designing immersive
experiences, customizing avatars, and interacting with others. The platform
also has a digital real estate market and opportunities for content creators
to earn revenue. Brands in Decentraland have reward programs that allow
users to redeem digital assets for discounts in the physical world, helping
to revitalize high streets post-pandemic. The Voice is one brand using this
metaverse.
The Voice, an American singing competition series, made its debut on
NBC in 2011. Contestants are selected through public auditions and receive
training from four coaches who offer guidance and feedback. In November
2022, The Voice expanded its reach by launching a four-day virtual pop-up
event in partnership with NBC at the Metaverse Music Festival in Decen-
traland. This immersive experience allowed the Decentraland community,
music enthusiasts, and festival attendees to participate in the audition process,
engage in themed games to collect notes, and have the opportunity to win
branded merchandise. The fans’ active involvement resulted in an average
 6 Transformative Marketing with Metaverse 149

session duration of 49 minutes, which is 13 times higher than the engage-

ment typically seen on social media platforms.13 By embracing this virtual
space, The Voice effectively develops marketing strategies that resonate with
its audience.

Predictive Marketing Using the Metaverse

Brands are continuously searching for new and creative methods to connect
with their target audience in the ever-changing marketing environment.
Roblox, a popular online platform, has emerged as one such platform where
users can create, share, and play games. This global platform has caught the
attention of brands who are eager to leverage its potential for promotional
and educational endeavors.
For instance, Walmart introduced two innovative virtual experiences,
Walmart Land and Walmart’s Universe of Play, on the popular metaverse plat-
form Roblox in September 2022. These captivating spaces provide customers
with interactive content and entertainment, showcasing the finest aspects
of Walmart’s aisles in a virtual realm. However, consumer advocacy groups
expressed concerns about potential covert marketing to children in these
games. Subsequently, Walmart pivoted in a new direction and launched
Walmart Discovered in September 2023 in Roblox. This world is divided into
different “departments,” (e.g., sports, pets, etc.) wherein, players can shop for
virtual items for their avatar, or enjoy gamified experiences.14
Predictive analytics plays a crucial role in analyzing user interactions within
the virtual Walmart store and forecasting customer behavior. By utilizing
data from the metaverse, it becomes possible to anticipate which products
or sections within the virtual store users are more likely to explore, interact
with, or make purchases. Through the implementation of predictive models,
the virtual Walmart experience in Roblox can personalize recommendations
for individual users based on their previous interactions, preferences, and in-
game behavior. This customization may involve suggesting items or offers
that align with a user’s interests or past purchases. Furthermore, predictive
analytics can assist Walmart in optimizing its in-game marketing strategies by
accurately predicting the most effective methods to engage users, deploying
promotions, or designing interactive elements within the virtual store.
150 V. Kumar and P. Kotler

Contextual Marketing Using the Metaverse

Metaverse-based contextual marketing is revolutionizing the way businesses

connect with their target audience. By leveraging the immersive and interac-
tive nature of the metaverse, companies can create personalized and engaging
experiences for their customers. Unlike traditional marketing methods, which
often rely on static advertisements, contextual marketing in the metaverse
allows brands to seamlessly integrate their products or services into the virtual
environment, making the marketing message more relevant and impactful.
For example, a clothing brand can use data on a user’s virtual wardrobe to
suggest complementary items or offer exclusive discounts, creating a seamless
shopping experience that feels tailored to the individual.
Consider the case of Africarare, the inaugural metaverse in Africa, which
has constructed Ubuntuland to unearth Africa’s latent talent, ingenuity, and
inventiveness, while simultaneously forging connections between Africa and
the global digital economy. Using the $UBUNTU Token or ETH, people can
buy, sell, or rent land in Ubuntuland. Landowners can create various expe-
riences like art exhibitions, retail stores, social interactions, gaming, virtual
concerts, and more. Companies such as Nedbank, MTN, and Primedia are
already part of Ubuntuland15
Now, Africarare has collaborated with Innovation Africa, a non-profit
organization, to establish a unique Innovation Africa village in Ubuntu-
land. This village will serve as a platform to highlight the transformative
efforts of the organization. The primary focus of this partnership is to uplift
rural communities by granting them access to clean water and electricity
through the utilization of Israeli solar, water, and agricultural technologies. By
implementing this innovative approach, the lives of individuals within these
communities will be positively impacted, bringing about significant change.
For instance, Africarare has recently introduced a distinctive collection of
Water Drop NFTs named “Drops of Life.”16 This collection comprises five
water drops, namely Diamond, Gold, Silver, Platinum, and Bronze. Each
drop possesses unique attributes and variations based on the buyer’s donation
type. For instance, the Diamond Drop not only ensures a lifetime supply of
water to a village but also grants the buyer an opportunity to visit the village
and personally inaugurate the water supply. Additionally, it includes a virtual
3x3 village in Ubuntuland, where the buyer can explore comprehensive data
regarding water production in a three-dimensional format. By creating such
virtual spaces in the metaverse, Africarare empowers individuals to make a
significant impact and improve the lives of people and society as a whole.
 6 Transformative Marketing with Metaverse 151

Augmented Marketing Using the Metaverse

Augmented marketing in the metaverse opens up a world of possibilities for

brands and businesses. By leveraging AR and VR technologies, marketers can
create interactive and immersive experiences that captivate consumers’ atten-
tion and leave a lasting impression. Furthermore, by tracking user interactions
within AR and VR experiences, marketers can gain a deeper understanding
of consumer preferences, interests, and purchasing patterns. This data can
then be used to refine marketing strategies, tailor product offerings, and
deliver targeted advertisements, ultimately driving higher engagement and
conversion rates.
For instance, Bon Viv Spiked Seltzer collaborated with immersive produc-
tion firm Aircards to launch a marketing campaign that showed clients
the potential of mixed reality experiences.17 The project was centered on
a cutting-edge out-of-home (OOH) approach in which consumers could
scan a QR code found on many Bon Viv murals located in San Diego and
Los Angeles. Using a code, patrons were able to gain entry to a virtual 3D
vending machine where they could choose and obtain their desired flavor.
The campaign also urged customers to choose digital delivery via Instacart
integration or to visit nearby retail locations where Bon Viv was sold.
An average of two minutes were spent on the seamless experience, and 58%
of consumers clicked through to purchase a can of Bon Viv. For the majority
of traditional digital channels, these outcomes are orders of magnitude higher
than industry averages. The combination of a well-known communication
tool (QR codes) with augmented reality activities to “transport” customers
to a location that appeals to their interests is what makes this campaign so
successful. Customers benefited greatly since they were given a prompt call
to action that they had chosen on their own. Overall, Bon Viv realized a
significant return on investment and the ability to develop a quantifiable
result-oriented marketing campaign.

Agile Marketing Using the Metaverse

Agile Marketing, a dynamic approach that emphasizes flexibility and adapt-

ability, has found a new playground in the metaverse. This emerging tech-
nology allows marketers to transcend traditional boundaries and explore
limitless possibilities. By harnessing the power of the metaverse, marketers
can create interactive campaigns that blur the lines between the physical and
digital worlds. This opens up a whole new realm of opportunities for brands
to engage with their customers in innovative ways.
152 V. Kumar and P. Kotler

For a considerable period, 3D and 3D graphics have been present, but

the metaverse takes it a step further by allowing organizations to quickly
adapt it to specific situations through the use of elements like decentralized
finance, tokenization, and commerce, resulting in an exceptional experience.
For instance, NextMeet, an immersive platform based in India, offers a virtual
conferencing and networking environment in real-time, where users can
interact through avatars in a 3D setting. By prioritizing interactive collabora-
tion, learning solutions, and efficient work practices, the platform strives to
eliminate the sense of isolation and disconnection that can arise from remote
and hybrid work setups.18
Following the COVID-19 pandemic, the company realized the industry
needed to migrate to an online work mode at the earliest, while not
compromising on the quality of workplace interactions. This platform allows
employees to seamlessly navigate virtual offices and meeting rooms in real-
time using digital avatars. They can easily approach a virtual help desk,
deliver live presentations, socialize with colleagues in a networking lounge, or
freely explore a conference center or exhibition using customizable avatars.
By accessing the virtual environment through their desktop computer or
mobile device, participants can effortlessly direct their avatars to move around
the virtual office space. In terms of employee engagement, the platform
offers a unique onboarding experience where new employees can explore the
company by walking through a 3D hall or gallery with interactive stands,
replacing the traditional method of reading an onboarding document.19 Such
a solution enabled companies to quickly migrate to virtual workplaces while
ensuring employees stayed engaged with their colleagues and the workplace.

Current Metaverse Applications in Marketing

Metaverse has the potential to revolutionize customer experiences, customer
engagement with the brand, and the concept of marketing. A virtually
infinite number of users can experience the metaverse synchronously and
persistently, with a massively scalable, interoperable20 network of real-time
rendered 3D virtual worlds that provide continuity of data, including iden-
tity, history, entitlement, objects, communications, and payments, and an
individual sense of presence.21 Businesses can use the metaverse to change
their business methods, regardless of their size or target audience.22 This
section presents five specific application areas where the metaverse continues
to help companies in developing marketing initiatives.
 6 Transformative Marketing with Metaverse 153

Understanding Customer Needs to Deploy

in the Metaverse

During the 1990s, the internet faced criticism for being a passing trend, but
it soon gained momentum. The growing number of consumers embracing
the internet brought about a significant transformation. In a similar vein,
the metaverse has captured the attention of consumers, signifying a notable
shift in how technology is utilized.23 Customers are drawn to novel experi-
ences, and embracing new technologies such as the metaverse enables them
to revolutionize customer experiences in a sustained manner.
Applications of the metaverse that go beyond gaming are becoming more
and more apparent. They are incredibly influencing immersive experiences in
sports, entertainment, retail, and education. High-end labels such as Gucci
and Balenciaga have developed virtual showrooms that allow clients to peruse
and engage with merchandise in an incredibly lifelike three-dimensional
setting. Using their smartphones, users can virtually try on makeup with
L’Oréal’s Modiface app. Virtual employee training, teamwork with avatars,
virtual prototyping in manufacturing and construction, virtual car showroom
displays, and other less discussed enterprise applications and opportunities
of the metaverse. It is interesting to note that governments are also exper-
imenting with metaverse technology. For instance, Seoul announced the
launch of Meta Seoul, a digital replica of South Korea’s capital city Seoul
where users can participate in a range of different activities. The virtual city
will house all the tourist sites and attractions that people can visit from the
comfort of their homes, among other key places of interest and even the
Mayor’s Office. Other global cities such as Sharjah, Dubai, and Hong Kong
have also announced similar such initiatives.24
Gen Z is a powerful force when it comes to the demographic tailwinds
influencing the metaverse’s adoption in the corporate world. Compared to
earlier generations, the income-earning population is more accustomed to
virtual goods, virtual worlds, and virtual transactions.25 Companies must
determine their marketing objectives before deciding whether or not to
implement the metaverse (in fact, doing so is not an option). This is depen-
dent upon their brand positioning, the tastes of their current and prospective
audiences, etc. After the objectives are established, the businesses must
determine which platforms offer the best odds and brand alignment.
154 V. Kumar and P. Kotler

Revisiting Firm Capabilities to Integrate in the Metaverse

There are several platforms available for Metaverse implementation, including

Roblox, Fortnite, Decentraland, Minecraft, and Meta’s Horizon Worlds.
Selecting the appropriate platform is crucial for a successful implementation.
Roblox is widely recognized for its extensive and diverse user base, making it
an ideal choice for those interested in user-generated content and younger
audiences. Gucci, for instance, conducted numerous brand activations on
Roblox and achieved remarkable success when it launched a metaverse version
of its Gucci Garden, attracting 19.9 million visitors within two weeks.26 On
the other hand, Fortnite is particularly suitable for social gamers who enjoy
competitive battle gameplay. Ralph Lauren capitalized on this platform by
introducing a digital clothing and accessories collection in the Fortnite Item
Shop, which was further complemented by a physical clothing line inspired
by the digital collection. Notably, the collaboration also marked the first
redesign of the iconic Ralph Lauren Polo Pony logo in 55 years.27
Despite the negative experiences encountered by Meta in the metaverse,28
companies like Nvidia are forging ahead with this technology.29 In a recent
development, Nvidia introduced the NVIDIA Omniverse, a design and
simulation platform, in September 2023, to further their progress in the
metaverse. However, despite these advancements, there are still challenges to
overcome. Intel, for example, argues that a significant increase in computing
power, around 1,000 times greater than the current capacity, is necessary to
sustain the vision of the metaverse.30
The firm’s current computing capacity required to power the metaverse
is expected to be addressed through the implementation of algorithms and
software enhancements. Technologies such as ML-powered neural networks
and AI-enhanced computational techniques have the potential to enhance
computing capacity and ensure the development of a robust hardware
roadmap. As businesses strive to bring their metaverse vision to fruition, it
is crucial for them to also prioritize strategies that mitigate the heightened
energy consumption resulting from these advancements. Once the potential
of these capabilities is recognized and efforts are made to make them meta-
verse-ready, companies must shift their focus towards designing marketing
mix strategies that align with the metaverse concept.
 6 Transformative Marketing with Metaverse 155

Designing Marketing Mix Strategies in the Metaverse

The metaverse offers immense marketing prospects for businesses of various

scales and industries. It is poised to redefine how organizations engage with
their target demographics, erasing the boundaries between the physical and
virtual realms. As the virtual landscape expands, marketers are evolving their
conventional strategies to cater to the distinct requirements of the metaverse.
Consequently, the traditional marketing mix model is no longer effective and
necessitates adaptation.
Product. In the realm of digital transformation, the shift from physical to
virtual products has become increasingly prevalent. While companies have
started to design products in metaverses (See Image 6.3), organizations are
also leveraging immersive technologies to enhance their offerings. Consider
the following cases:

• Nike offers virtual sneakers, clothing, and accessories within their virtual
world, Nikeland. This innovative approach allows customers to not only
get involved in the design of shoes but also make purchases and showcase
their unique style and individuality.31
• Ikea has introduced a captivating AR game called “The Little Adven-
ture” for families who visit their stores in Sweden. By accessing the game
through Instagram, customers can immerse themselves in an interactive

Image 6.3 Product design using Metaverse. Product design and ergonomic features
can be configured on the metaverse
(Source Photo by XR Expo on Unsplash)
156 V. Kumar and P. Kotler

experience that focuses on educating and engaging children about marine

life. Through virtual swimming with different sea creatures, kids can learn
about them and gain knowledge about the ocean. The game also addresses
important themes such as littering and pollution prevention, showcasing
Ikea’s dedication to promoting plastic recycling, as evidenced by their
Blåvingad collection featuring ocean-themed soft toys and children’s acces-
sories made from ocean-bound plastics.32
• Obsess has developed the AVA virtual platform, which draws inspira-
tion from Shopify’s traditional web grid interface model. This platform
empowers brands to create and oversee their immersive 3D virtual store-
fronts, allowing them to adapt and modify merchandising, content,
and styling dynamically throughout the year, thereby ensuring a next-
generation shopping experience for their customers.33

These examples indicate that the field of product engagement and self-
expression is changing, and virtual and physical experiences are starting to
converge.
Price. The metaverse is increasingly being recognized as a platform where
consumers can interact with brands and make purchases.34 This perception
among customers can potentially lead to a willingness to pay higher prices,
as it sets the brand apart from its competitors. The use of AR and VR
elements to enhance existing products also contributes to this differentiation.
Conducting thorough market research is crucial in determining the added
value of metaverse elements and the corresponding price premiums. Pricing
activities in the metaverse include purchasing virtual land in platforms like
Decentraland, buying and selling NFTs, and obtaining exclusive access to
metaverse experiences. Cryptocurrencies have emerged as a popular method
of conducting transactions within the virtual realm. Many companies have
adopted Ethereum or their unique virtual currencies to facilitate purchases,
providing a secure and decentralized payment system that promotes seamless
transactions and builds trust between buyers and sellers.
The metaverse presents a distinct pricing landscape compared to tradi-
tional spaces, as evidenced by the significant price difference between Gucci’s
virtual sneakers, priced at $12.99, and their real-life counterparts, which
can cost up to $1,000. To maintain appropriate pricing within the meta-
verse, companies have the opportunity to employ various strategies. One
such strategy involves leveraging the capabilities of the metaverse to gather
and analyze consumer data, enabling retailers to develop a comprehensive
understanding of their customers’ preferences and behaviors. This accurate
segmentation of virtual consumers not only enhances retailers’ understanding
 6 Transformative Marketing with Metaverse 157

of their target audience but also strengthens customer loyalty. Additionally,

companies can adopt competitive pricing approaches, closely monitoring
competitors’ prices and adjusting their own accordingly. Another viable
option is algorithm-based pricing, where pricing algorithms utilize consumer
data to determine the optimal price for a product. These are just a few
examples of the pricing strategies that can be employed in the metaverse.
Place. The metaverse market is projected to experience significant
growth,35 indicating that retailers and brands will need to enhance their
presence within this virtual realm. Alongside the ongoing debate regarding
the metaverse’s viability as a standalone sales channel, there is considerable
discourse surrounding the overall concept of what a metaverse space might
entail. Generally, the metaverse refers to a shared virtual environment that
emerges from the fusion of physical and virtual realities. It is commonly
perceived as a space where individuals can engage with computer-generated
surroundings and interact with other users in real-time. Consequently, the
metaverse offers a wide range of possibilities, spanning from imaginative
realms to replicas of real-world locations (such as the ruins of Olympia, the
Taj Mahal, or Niagara Falls) to hybrid spaces that blend elements of the real
and virtual worlds (such as museums featuring art exhibits—See Image 6.4 )
to interactive playgrounds for gaming and even custom-made spaces (such as
virtual replicas of workplaces, educational institutions, or hospitals). While
the specific context may shape the nature of the metaverse, the place itself
plays a pivotal role in fostering user engagement.
Promotion. In the metaverse, promotion goes beyond conventional
marketing. For instance, Nike is developing NFTs—unique, blockchain-
secured tokens—for digital goods to demonstrate ownership in its
“.SWOOSH” platform.36 Additionally, they are holding virtual races and
product showcases for users to take part in. Another noteworthy trend is
influencer marketing in the metaverse. People can communicate in immer-
sive ways in the metaverse, giving public relations (PR) new opportunities
to differentiate themselves from the competition. By combining metaverse
elements into virtual events, PR firms can leverage the metaverse to foster
brand engagement and create memorable customer experiences. The meta-
verse is also changing the social networking scene; when it is integrated
into social media, marketers can make money, expand their user base, boost
engagement, etc. The Horizon Worlds by Meta is an example of this, where
users can hang out with friends, play games, and attend events.
In general, businesses prepared to invest have a lot of options in the meta-
verse. To provide customers with the most immersive experiencesv possible,
158 V. Kumar and P. Kotler

Image 6.4 Metaverse in public spaces. Metaverse can be used in public spaces such
as museums to blend physical and virtual worlds
(Source Photo by Sophia Sideri on Unsplash)

every component of the marketing mix is being redesigned to accommodate

the special qualities of the Metaverse.

Driving Customer Engagement Through the Metaverse

The metaverse can help put consumers in the driver’s seat in three major
ways, thus driving customer engagement.37 First, the metaverse creates new
ways to discover and explore products. For example, the Miami-based cruise
line Celebrity Cruises has embraced the metaverse in full to reach out to new
travelers. Celebrity Beyond is the first virtual cruise ship to be introduced
in the metaverse.38 Interested parties can take a thorough 360-degree tour
of the ocean liner before setting sail on a real trip. Additionally, passengers
can engage with the captain’s AI-powered avatars to learn important details
about the layout and amenities of the ship. Businesses can incorporate more
excitement, customization, and interactivity into their customer interactions
by utilizing the emerging metaverse.
 6 Transformative Marketing with Metaverse 159

Second, the metaverse facilitates the fusion of virtual and physical product
experiences. In the metaverse, customers are presented with a combination
of physical and virtual goods, in contrast to traditional commerce where
customers typically order physical products online and consume them offline.
For instance, in 2022, Coca-Cola commemorated its anniversary in the meta-
verse on International Friendship Day.39 The collectible, which emphasized
themes of unity and connection through a design modeled after the bubbles
inside a Coke bottle, was airdropped into the digital wallets of current Coca-
Cola collectible owners. By allowing the recipients to share collectibles with
a friend, the open blockchain community of the brand’s fans was expanded.
Lastly, brands are increasingly turning to the metaverse to create cohe-
sive, realistic, and customized interactions. Digital humans, or AI-powered
customer agents, are used for this. For example, Hanwa Life, a life insur-
ance provider in South Korea, created Hannah, a virtual financial advisor,
to represent the company’s digital initiatives to bring the metaverse to life.
This “virtual human” will assist not only clients (mainly millennials and Gen
Z consumers) looking for a more customized experience but also insurer
employees, whose workload will be reduced.40
All things considered, the metaverse shows promise as a potent tool for
companies looking to interact and engage with clients in novel and creative
ways. The metaverse empowers consumers to take charge of their journey by
providing new avenues for product exploration, combining real and virtual
experiences, and utilizing AI-powered digital humans. This, in turn, fosters
consumer satisfaction and brand loyalty. We can anticipate even more creative
methods from companies to firmly place the customer at the center of their
operations as the metaverse develops.

Designing Digital Strategies Within the Metaverse

Using the special qualities of the metaverse to accomplish particular objectives

is part of designing digital strategies within it. Businesses and individuals can
experiment with different approaches to optimize their impact, engagement,
and presence as the metaverse develops.
To develop a digital strategy, it is crucial to have a clear understanding
of how the metaverse should be structured. This initial step involves three
key actions. First, it is important to determine the level of centralization or
decentralization that the metaverse will possess. This means recognizing that
the metaverse will likely consist of a diverse landscape, with both central-
ized platforms like Meta’s Horizon Worlds and decentralized networks such
as The Sandbox. The chosen strategy must be flexible enough to navigate and
160 V. Kumar and P. Kotler

adapt to these different environments. Second, careful consideration must be

given to decisions regarding avatars and their interoperability. Avatars serve
as digital representations of individuals in the metaverse, and it is essential
to establish their identity and ensure seamless movement between platforms.
Lastly, while the metaverse offers limitless possibilities for hyper-realistic expe-
riences that blur the boundaries between the physical and virtual worlds, it is
important to remain focused on creating meaningful engagement for users.
It is easy to become overwhelmed by the vast potential of the platform, so
efforts must be made to ensure that the immersive nature of the metaverse is
purposeful and engaging.
After determining the structure, several other aspects require attention.
First, it is important to understand the target audience of the metaverse
relevant to the company or brand. This includes identifying whether the audi-
ence consists of gamers, professionals, or consumers seeking new experiences.
Second, it is crucial to establish the value proposition of the metaverse. This
can involve creating virtual products, hosting interactive events, or offering
gamified experiences. Third, incorporating engaging and interactive content
that goes beyond traditional formats is essential. This can include integrating
augmented reality/virtual reality, as well as creating 3D environments. Addi-
tionally, building a community around the brand through interactive spaces
and meaningful connections is vital. Lastly, finding ways to monetize the
presence in the metaverse, such as through virtual goods or tokenization, is an
important consideration. By combining these factors, businesses and individ-
uals can develop digital strategies that align with the unique characteristics
of the metaverse, enabling meaningful interactions and the achievement of
objectives within this emerging virtual space.

Future of Metaverse in Marketing

Perhaps the biggest chance to completely rethink the customer experience
is presented by the metaverse. Notwithstanding its existence, not everything
about the metaverse is perfect. The current state of customer experiences and
methods for creating them is called into question by the metaverse. A few
challenges that businesses must overcome include choosing the best metaverse
platform (one that aligns with the brand’s target demographics, real estate
costs, and growth prospects), coming up with novel ways to engage with
customers and give them genuine experiences, and monitoring performance
using metrics appropriate for the metaverse. As the metaverse continues to
develop, several challenges and considerations arise, encompassing technical,
 6 Transformative Marketing with Metaverse 161

social/ethical, and economic aspects. This section discusses these aspects as

they relate to the future of the metaverse.

Technical Considerations

With the metaverse serving to blend the physical and virtual worlds, the
technical considerations to mount a metaverse are significant. Among the
considerations, the following three aspects will require attention in the future.
First, the metaverse’s ambitious vision of vast and captivating virtual
worlds is currently constrained by the limitations of existing technology.
Advancements in areas like latency, data processing, and avatar realism are
crucial for its development. Unlike the conventional Web, the metaverse
inherently requires substantial computational resources to function smoothly.
The rendering of virtual environments and the delivery of a seamless user
experience demand significant computational power. While some platforms
attempt to delegate these requirements to users, this approach restricts the
potential user base to individuals with high-performance, expensive, and
well-equipped computers, hindering widespread adoption.41
Second, the accessibility to hardware and infrastructure necessary for a
seamless metaverse encounter is not equal for everyone. Take, for example,
the availability of VR headsets. Although not every metaverse experience
demands a VR headset, many do, and thus, consumers associate the concept
of the metaverse with VR. However, the average prices of VR headsets are
high and show no significant signs of decreasing.42 Moreover, the global
market for VR headsets is anticipated to experience a decline in revenue
growth.43 Similarly, the prerequisites for high-speed internet and powerful
computers can create a barrier of exclusivity, particularly in emerging
economies.
Finally, the rise of multiple metaverse platforms has brought about inter-
operability concerns. In other words, without the ability to seamlessly navi-
gate between platforms, consumers may not find the metaverse appealing.
However, achieving interoperability is not solely dependent on technical
aspects of platform integration, but also on the content that is being shared.
This presents a dilemma as content creators, such as brands and compa-
nies, are unlikely to invest in the metaverse without a substantial audience.
Consequently, the issue of interoperability is closely intertwined with that
of content. Thus, the challenge lies in ensuring smooth user migration and
interaction across various virtual worlds, considering the specific content
involved.
162 V. Kumar and P. Kotler

Social/Ethical Considerations

The development of the metaverse raises various social and ethical concerns
that warrant careful consideration. As this virtual space becomes more inte-
grated into our lives, it is important to address the following issues to ensure
a positive and responsible evolution of the metaverse.
First, the act of extracting data from the metaverse presents significant
challenges. Every action, preference, and interaction within the metaverse
can be meticulously monitored and collected. While the metaverse holds the
potential for immersive experiences, privacy concerns arise. Consequently,
users may unknowingly become targets of potentially harmful advertisements
or fall victim to their data being mishandled. This situation amplifies the
issue of identity theft, particularly in a realm where customizable avatars and
anonymity prevail. The boundaries between real and virtual identities become
blurred, providing an opportunity for malicious individuals to exploit this
for identity theft, financial fraud, or social manipulation. Furthermore, the
risks associated with identity theft may extend beyond the virtual realm and
infiltrate the real world through data breaches.44
Second, negative effects could be experienced on mental health and well-
being. For example, the attraction of carefully designed virtual environments
may result in addiction and escapism, endangering relationships, and obliga-
tions in the real world.45 It is not implausible for users of such a platform to
prioritize their virtual thrills over their career or physical health. Furthermore,
in the metaverse, problems like cyberbullying and harassment that already
exist in the real world can manifest themselves in even more dangerous ways.
A user might, for example, become the object of stalking in the virtual world,
which could be seen as an extension of the real world.
Fourth, the algorithms that are used to build these kinds of worlds in the
metaverse can lead to bias and discrimination. That is, prejudice based on
race, gender, or other characteristics may be sustained by the algorithms that
create the metaverse experiences. Put another way, a user’s perceived identity
as represented by their digital avatar could result in them being refused access
to particular virtual areas or opportunities, or even being treated differently.
Furthermore, this would also include giving some users preferential treatment
based on preconceived notions.
Finally, the metaverse presents issues with inclusivity and accessibility as
well. Not everyone has equal access to engage in the metaverse due to the
technical and technological requirements. This might make already-existing
socioeconomic disparities worse and give rise to a brand-new group of
marginalized people. This has the potential to create a risky precedent with
 6 Transformative Marketing with Metaverse 163

real-world repercussions. Furthermore, although the metaverse can construct

meaningfully interactive worlds for individuals, particularly those with phys-
ical disabilities, it must do so carefully. People with mobility issues would feel
alienated if the virtual world was exclusively made for avatars on foot.

Economic Considerations

As the metaverse involves virtual economies, digital assets, and cross-platform

interactions, the following economic and regulatory considerations become
crucial.
First, the metaverse’s monetization features need to be set up carefully. This
necessitates a strategy that strikes a balance between monetization strategies
and offering engaging experiences. That is, avatars who are constantly inun-
dated with in-app purchases or advertisements might have a poor experience,
which could be bad for the metaverse brands. This also necessitates careful
management of content creators. That is to say, it is challenging to guarantee
the appropriate content for the metaverse without guaranteeing just compen-
sation for content creators, which impedes the richness and diversity of virtual
experiences.
Second, it is important to give careful thought to the governance and
regulatory frameworks. This implies that to appropriately handle concerns
like intellectual property rights, data privacy, and criminal activity within
the metaverse, the current legal frameworks may need to be modified. For
instance, it is necessary to create explicit and straightforward legal redress
for problems like online harassment and disputes over virtual land owner-
ship. Furthermore, the decentralized structure of the metaverse makes it
difficult to create consistent laws and enforce them on various platforms.
To guarantee an exceptional virtual experience when several platforms are
involved, smooth integration with uniform guidelines and standards needs to
be established. This necessitates increased communication and understanding
between nations to create a logical regulatory framework for the metaverse
that safeguards users and promotes responsible development.
Ultimately, to prevent large corporations from controlling online spaces
and resources and perpetuating injustice, fair competition must be main-
tained in the metaverse. Closer cooperation between international govern-
ments is also required in this situation to stop monopolies from forming
and rent-seeking behavior from continuing. Governments and businesses can
guarantee that everyone has an equal opportunity to engage with and profit
from the metaverse by concentrating on bridging the global divide through
programs to increase digital literacy and accessibility.
164 V. Kumar and P. Kotler

Looking ahead, these are just some of the considerations that arise with the
metaverse. Addressing these challenges is crucial to ensure its development
happens responsibly and ethically, benefiting all of humanity. Open dialogue,
collaboration between stakeholders, and proactive development of regulations
and processes are essential steps in navigating this complex landscape.

Key Terms and Related Conceptualizations

Blockchain-based metaverse No single entity has control over the virtual world,
and users have ownership and control over their
data and assets
Interoperability The ability to interact, exchange and make use of
data and resulting information to enable
movement, transactions and participation across
systems, platforms, environments, and
technologies
Metaverse A range of interconnected virtual realms that can
be accessed through augmented and virtual
reality technologies
Traditional metaverse An entire virtual world owned and operated by a
single company that gives them complete control
over all aspects of the metaverse

Notes and References

1. The immersive environment also features an interconnected virtual
economy that seamlessly integrates with the global financial system
(Au, W. J. (2023), “Neal Stephenson isn’t giving up on the meta-
verse—or crypto,” Fast Company, October 8, accessed from https://
www.fastcompany.com/90935596/neal-stephenson-on-reclaiming-his-
metaverse).
2. Richard A. Bartle advanced the concept of a virtual world which is
“…an automated, shared, persistent environment with and through
which people can interact in real time by means of a virtual self ”
(Bartle, R. A. (2010). From MUDs to MMORPGs: The history of
virtual worlds. In Hunsinger, J., Klastrup, L, & Allen, M. (eds.),
International Handbook of Internet Research, pp. 23-39. Springer). He
further offered an evolution of a virtual world to comprise five ages of
development (i.e., 1978–85, 1985–89, 1989–95, 1995–97, and 1997–
Present). In the fifth age, graphics are introduced laying the foundation
for modern multiuser video games and ultimately the marriage of video
games and social interaction technology.
 6 Transformative Marketing with Metaverse 165

3. Dionisio, J. D. N., Iii, W. G. B., & Gilbert, R. (2013). 3D virtual

worlds and the metaverse: Current status and future possibilities. ACM
Computing Surveys (CSUR), 45 (3), 1–38.
4. Perlin, K., & Goldberg, A. (1996). Improv: A system for scripting
interactive actors in virtual worlds. In Proceedings of the 23rd Annual
Conference on Computer Graphics and Interactive Techniques (pp. 205–
216), August.
5. Davis, A., Murphy, J., Owens, D., Khazanchi, D., & Zigurs, I.
(2009). Avatars, people, and virtual worlds: Foundations for research
in metaverses. Journal of the Association for Information Systems, 10 (2),
1.
6. Wright, M., Ekeus, H., Coyne, R., Stewart, J., Travlou, P., & Williams,
R. (2008). Augmented duality: overlapping a metaverse with the real
world. In Proceedings of the 2008 International Conference on Advances
in Computer Entertainment Technology (pp. 263–266), December.
7. Lee, M. Y. H. (2021), “Seoul wants to build a metaverse. A virtual New
Year’s Eve ceremony will kick it off,” The Washington Post, November
28, accessed from https://www.washingtonpost.com/world/asia_paci
fic/metaverse-seoul-virtual/2021/11/27/03928120-4248-11ec-9404-
50a28a88b9cd_story.html.
8. Barrera, K. G., & Shah, D. (2023). Marketing in the Metaverse:
Conceptual understanding, framework, and research agenda. Journal
of Business Research, 155, 113420.
9. The metaverse’s ability to be a platform for overcoming challenges,
fostering creativity and imagination, and improving technological
proficiency and abilities is boosting the investments in this new tech-
nology (Tidio. (2021). Leading benefits of the metaverse worldwide
in 2021 [Graph]. Statista, December 1, accessed from https://www.sta
tista.com/statistics/1285117/metaverse-benefits/). Moreover, it offers
the opportunity to connect with others effortlessly, opens up new
avenues for employment, and allows individuals to express themselves
in unique ways.
10. Ramadhan, A., Pradono Suryodiningrat, S., & Mahendra, I. (2023).
The fundamentals of metaverse: A review on types, components
and opportunities. Journal of Information and Organizational Sciences,
47 (1), 153–165.
11. Hu, P. J. H., & Hui, W. (2012). Examining the role of learning engage-
ment in technology-mediated learning and its effects on learning
effectiveness and satisfaction. Decision Support Systems, 53(4), 782–
792.
166 V. Kumar and P. Kotler

12. Park, S., & Kim, S. (2022). Identifying world types to deliver gameful
experiences for sustainable learning in the metaverse. Sustainability,
14 (3), 1361.
13. Spangler, T. (2023), “‘The voice’ free metaverse experience will let fans
compete in virtual music battles, win prizes and more (EXCLUSIVE),”
The Variety, May 10, accessed from https://variety.com/2023/digital/
news/the-voice-studios-metaverse-free-virtual-launch-1235608477/.
14. Perez, S. (2023), “Walmart returns to Roblox after its first games were
attacked by consumer advocacy groups,” TechCrunch, September 27,
accessed from https://techcrunch.com/2023/09/27/walmart-returns-
to-roblox-after-its-first-games-were-attacked-by-consumer-advocacy-
groups/.
15. Torrao, M. R. (2023), “Welcome To ‘Ubuntuland’—Africa’s First Ever
Virtual Reality Metaverse [Video],” 2OceansVibe, August 29, accessed
from https://www.2oceansvibe.com/2023/08/29/welcome-to-ubuntu
land-africas-first-ever-virtual-reality-metaverse-video/#ixzz8MKmB
XRmI.
16. Africarare (2023), “Metaverse Helps Bring Water to Africa,” Africarare,
march 8, accessed from https://www.globenewswire.com/en/news-rel
ease/2023/03/08/2622834/0/en/Metaverse-Helps-Bring-Water-to-Afr
ica.html.
17. Shlachter, A. (2023), “How AR and the ‘real-world metaverse’ can
augment traditional media,” The Drum, April 11, accessed from
https://www.thedrum.com/opinion/2023/04/11/how-ar-and-the-real-
world-metaverse-can-augment-traditional-media.
18. Bhura, S. (2022). “After Facebook’s Meta, some Indian companies
are rolling out ’native metaverses’,” The Week, February 6, accessed
https://www.theweek.in/theweek/leisure/2022/01/27/after-facebook-
meta-some-indian-companies-are-rolling-out-native-metaverses.html.
19. Purdy, M. (2023). Building a great customer experience in the meta-
verse. Harvard Business Review, April 3, accessed from https://hbr.org/
2023/04/building-a-great-customer-experience-in-the-metaverse.
20. The World Economic Forum defines interoperability as “The ability
to interact, exchange and make use of data and resulting information
to enable movement, transactions and participation across systems,
platforms, environments and technologies” (World Economic Forum
(2023), “Interoperability in the Metaverse,” World Economic Forum,
January, accessed from https://www3.weforum.org/docs/WEF_Intero
perability_in_the_Metaverse.pdf).
 6 Transformative Marketing with Metaverse 167

21. Ball, M. (2022). The metaverse: And how it will revolutionize everything.
Liveright Publishing.
22. By 2026, around 25% of people are expected to spend at least one
hour daily in the metaverse, as per Gartner. The main benefit, cited by
39% of respondents, is the metaverse’s power to help users overcome
challenges like physical disabilities (Pratt, M. K. (2022), “10 real-
world use cases of the metaverse, and examples,” TechTarget, November
22, accessed from https://www.techtarget.com/searchcio/feature/Exa
mples-of-the-metaverse-for-business-and-IT-leaders).
23. Hazan, E., Kelly, G., Khan, H., Spillecke, D., & Yee, L. (2022).
Marketing in the metaverse: An opportunity for innovation and
experimentation. The McKinsey Quarterly.
24. CNBC (2023). “Exploring Seoul’s newly opened metaverse city and
others like it,” CNBC-TV18, January 18, accessed from https://www.
cnbctv18.com/technology/exploring-seouls-newly-opened-metaverse-
city-and-others-like-it-15707621.htm.
25. For instance, Snapchat’s Gen Z survey found that 60% of the soon-
to-be largest consumer base say AR experiences feel more personal
(Snapchat (2022), “Gen-Z in 2022,” Snapchat, accessed from https://
downloads.ctfassets.net/inb32lme5009/1rPnekNZuxpa48Gd8tG9z4/
77217b80f5b0ea535324b3437b9988ab/Gen_Z_in_2022_Culture__
Commerce__and_Conversations.pdf).
26. Hazan, E., Kelly, G., Khan, H., Spillecke, D., & Yee, L. (2022).
Marketing in the metaverse: An opportunity for innovation and
experimentation. The McKinsey Quarterly.
27. Tsiaoussidis, A. (2023), “Every single Fortnite collab & crossover in
battle royale’s history,” Dexerto, December 7, accessed from https://
www.dexerto.com/fortnite/every-fortnite-collab-crossover-battle-roy
ale-history-1645672/
28. Thorbecke, C. (2023), “What metaverse? Meta says its single
largest investment is now in ‘advancing AI’,” CNN , March 15,
accessed from https://edition.cnn.com/2023/03/15/tech/meta-ai-inv
estment-priority/index.html.
29. NVIDIA (2021), “NVIDIA brings millions more into the meta-
verse with expanded omniverse platform,” NVIDIA, August 10,
accessed from https://nvidianews.nvidia.com/news/nvidia-brings-mil
lions-more-into-the-metaverse-with-expanded-omniverse-platform.
30. Gartenberg, C. (2021), “Intel thinks the metaverse will need a
thousand-fold increase in computing capability,” The Verge, December
168 V. Kumar and P. Kotler

16, accessed from https://www.theverge.com/2021/12/15/22836401/

intel-metaverse-computing-capability-cpu-gpu-algorithms.
31. Sutcliffe, C. (2022), “21m people have now visited Nike’s Roblox
store. Here’s how to do metaverse commerce right,” The Drum,
September 22, accessed from https://www.thedrum.com/news/2022/
09/22/21m-people-have-now-visited-nike-s-roblox-store-here-s-how-
do-metaverse-commerce.
32. Mileva, G. (2023), “IKEA launches interactive AR game to teach chil-
dren about marine life,” AR Post, February 24, accessed from https://
arpost.co/2023/02/24/ikea-ar-game-children-marine-life/.
33. Chan, A. (2023), “Obsess launches AVA, A dynamic self-serve, DIY
tool that allows brands to quickly change and manage merchandising,
visual display, and content for their virtual storefronts,” Forbes, April
14, accessed from https://www.forbes.com/sites/angelachan/2023/
04/14/obsess-launches-ava-a-dynamic-self-serve-diy-tool-that-allows-
brands-to-quickly-change-and-manage-merchandising-visual-display-
and-content-for-their-virtual-storefronts/?sh=42490e05388e.
34. According to a U.S. survey conducted in 2022, 87% of users who are
already using the Metaverse or who wish to use it in the future said they
thought it would have a big impact on how they shop and interact with
brands (Sitecore (2022), “Consumer Perceptions about the Metaverse,”
Sitecore, August, accessed from https://www.sitecore.com/blog/metave
rse/2022-research).
35. The global metaverse market was projected to be valued at USD 65.5
billion in 2022. This is anticipated to increase to USD 82 billion
in 2023 and then soar to USD 936.6 billion by 2030 (Grand View
Research (2023), “Metaverse market revenue worldwide from 2022
to 2030 (in billion U.S. dollars) [Graph],” Statista, February 27,
accessed from https://www.statista.com/statistics/1295784/metaverse-
market-size/).
36. Akolkar, B. (2023), “Nike soon to bring its popular. SWOOSH NFTs
to EA Sports Games,” Coinspeaker, June 2, accessed from https://www.
coinspeaker.com/nike-swoosh-nfts-ea-sports-games/.
37. Purdy, M. (2023). Building a great customer experience in the meta-
verse. Harvard Business Review, April 3, accessed from https://hbr.org/
2023/04/building-a-great-customer-experience-in-the-metaverse.
38. Dawes, J. (2022), “Celebrity cruises enters the metaverse with a virtual
ship tour,” Skift, December 14, accessed from https://skift.com/2022/
12/14/celebrity-cruises-enters-the-metaverse-with-a-virtual-ship-tour/.
 6 Transformative Marketing with Metaverse 169

39. Wright, W. (2022), “Coca-Cola toasts one year in the metaverse with
International Friendship Day NFT drop,” The Drum, July 27, accessed
from https://www.thedrum.com/news/2022/07/27/coca-cola-toasts-
one-year-the-metaverse-with-international-friendship-day-nft-drop.
40. Si-young, C. (2022), “Hanwha Life Insurance unveils ‘virtual human’
in digital push,” The Korea Herald , November 8, accessed from https://
www.koreaherald.com/view.php?ud=20221108000593.
41. Rush, J. (2023), “It’s time we had a frank discussion about the
state of the metaverse,” Fast Company, September 22, accessed from
https://www.fastcompany.com/90955919/its-time-we-had-a-frank-dis
cussion-about-the-state-of-the-metaverse.
42. In 2018, the average cost of a virtual reality headset was USD 385
worldwide. Since then, the price has risen to USD 422 in 2023 and
is predicted to remain stable in 2028 at roughly USD 420 (Statista
(2023), “Virtual reality (VR) headset average price worldwide from
2018 to 2028 (in U.S. dollars) [Graph],” Statista, September 14,
accessed from https://www.statista.com/forecasts/1338351/vr-headset-
average-price-worldwide).
43. The consumer electronics market’s VR headset segment saw a 45.4
percentage point increase in global revenue between 2019 and 2021;
however, between 2022 and 2028, it is expected to decline by 29.8
percentage points (Statista (2023a), “Revenue growth of the VR
headsets market worldwide from 2019 to 2028 [Graph],” Statista,
September 14, accessed from https://www.statista.com/forecasts/133
1894/vr-headset-revenue-growth-worldwide).
44. Over 40% of participants in a 2021 global survey cited privacy
concerns as one of the main threats posed by the metaverse
(PC Magazine (2021), “Dangers of the metaverse according to
internet users worldwide in 2021 [Graph],” Statista, December
1, accessed from https://www.statista.com/statistics/1288822/metave
rse-dangers/). Similarly, in a 2021 study among Southeast Asian
nations (Singapore, Malaysia, Indonesia, and the Philippines), worries
about data security and privacy were the main reason more than
60% of respondents felt negatively about the metaverse (Techsauce
(2022), “Leading reasons for feeling negative about the metaverse
in Southeast Asia in 2021, by country [Graph],” Statista, January
13, accessed from https://www.statista.com/statistics/1292195/sea-
top-concerns-about-the-metaverse-by-country/).
170 V. Kumar and P. Kotler

45. In a 2022 US survey, 60% of participants preferred metaverse activ-

ities to escape real-world challenges, mainly due to rising living
expenses. Additionally, 46% used the metaverse as an escape from
COVID-19 risks. It is worth noting that a mere 17% of the partic-
ipants stated that they did not utilize the metaverse as a form of
escapism (Sitecore (2022a), “Real-world issues that would make meta-
verse enthusiasts in the United States inclined to use the metaverse to
escape the real world as of August 2022 [Graph],” Statista, October
19, accessed from https://www.statista.com/statistics/1346320/us-met
averse-real-world-issues-escape/).
 7
Transformative Marketing with the Internet
of Things (IoT)

Overview
In today’s highly connected world, it is not only humans who establish
connections, but devices do too. Through our daily lives, we see devices
controlled through sensors and remotely located software such as connected
streetlights, self-driving vehicles, smart home security systems, connected
wearable devices, and much more. These devices collect, communicate, and
process information in real-time through the internet to perform or aid in
performing certain defined tasks. This elaborate and growing network of
devices connected through the Internet is referred to as the Internet of Things
(IoT). Simply put, any physical device can become an IoT device when
connected to the internet.
Consider the case of digital screens installed in retail stores. When viewed
from a distance, these screens look like big electronic billboards with ads.
When a customer approaches these screens, the advertising images turn into
digital representations of the products inside the cases, including any stockout
information.1 Using this, the brands can reach shoppers on smart screens
that dynamically adjust to shopper behavior and data-driven context at the
point of decision in-store. The privacy-safe IoT sensors and AI software can
turn a screen (end caps, walls, banner aisles, windows, and coolers) into a
smart screen, powering a dynamic and more relevant customer experience
that adapts to the shopper based on their attention, distance, motion, and
actions. More brands such as Anheuser-Busch InBev, Nestle, PepsiCo, Tyson,

© The Author(s), under exclusive license to Springer Nature 171

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_7
172 V. Kumar and P. Kotler

Unilever, and Red Bull use this for marketing their products. This tech-
nology was pioneered by Chicago-based Cooler Screens which partners with
Walgreens, Kroger, and CVS for this initiative.
The digital screens are equipped with IoT sensors and other technology,
enabling them to function as both merchandising and advertising platforms.
These screens are also being used to collect data about shoppers (what prod-
ucts they are viewing and interacting with). This data can be used by retailers
to improve their marketing approaches and tailor to customer requirements
better. This technology is also used to display content including product
information, promotion videos and images, social media feeds, weather,
news, and so on. It benefits retailers by increasing sales (promoting products
and engaging shoppers), improving merchandising (collecting data on user
behavior and tailoring marketing strategy), and reducing energy costs (digital
display instead of glass doors). It also benefits the customer through engaging
shopping experience and building knowledge of product features.2 As we
witness around us, the number of connected things/devices is increasing at a
rapid rate,3 with cellular IoT being a significant driver for the proliferation.4
Such a connected environment holds immense potential to continuously
impact our daily lives, and significantly shape the world of business.
This chapter is organized in the following manner. First, a brief history
of the origin of IoT is presented, followed by a definition of IoT (from a
marketing standpoint). Then, a discussion on the various classifications of
IoT is presented spanning individual to commercial uses such as wearables,
smart homes, and industrial automation. Next, some marketing applications
of IoT focusing on understanding customer needs, revisiting firm capabili-
ties to integrate IoT, designing IoT-focused marketing mix strategies, driving
customer engagement (CE) through IoT, and designing digital strategies with
IoT are discussed. Finally, the future of IoT for the marketing industry is
envisioned through specific business- and customer-facing tasks such as the
role of IoT in shaping modern transportation, developing, and managing
smart cities, and powering key business processes.

Origin, Definition, and Classifications of IoT

The IoT is a term generally applied to a network of connected devices

communicating with each other and with human beings.5 First proposed
in 1999, the credit for coining this term goes to Kevin Ashton.6 However,
it wasn’t until 2003 that IoT got noticed by way of its early application—
Radio Frequency Identification (RFID). In 2003, Walmart required their
major contractors and suppliers to mark their shipments with RFID tags
 7 Transformative Marketing with the Internet … 173

for inventory control.7 This was one of the earliest industry adoptions of
RFID that subsequently made the case for the use of internet-connected
devices to manage commercial processes. In this regard, the International
Telecommunications Union (ITU) defines IoT as a “global infrastructure
for the information society, enabling advanced services by interconnecting
(physical and virtual) things based on existing and evolving interoperable
information and communication technologies.”8 This definition recognizes
the far-reaching and significant personal, commercial, and societal implica-
tions of IoT, and paves the way for considering IoT as a major game changer.9
Currently, with the widespread implications and applications of IoT, the
relevance of IoT is noticeable in five key areas—transportation and logis-
tics, healthcare, smart environment, personal and social uses, and futuristic
ideas.10
In terms of IoT classifications, research has proposed various classifica-
tion structures. For instance, Gluhak et al.11 classify IoT based on challenges
encountered in IoT such as scale, heterogeneity, repeatability, mobility,
and user involvement, among others. Similarly, Gubbi et al.12 classify IoT
based on application areas such as personal and home, enterprise, utilities,
and mobile. Further, Sundmaeker et al.13 propose a classification based on
connectivity across time, place, device, person(s), content, path/network,
and tasks/services. Given the marketing scope of this book, a classification
based on IoT aggregation structures is presented here. Consequently, IoT
can be aggregated along the following dimensions—individuals, organiza-
tions, industry, and national. A brief description of these four dimensions
is discussed here.

Individuals

At the individual level, IoT devices work towards assisting in typical everyday
activities through the detection and capturing of information. Information
thus recorded is then shared in real-time with the computing infrastruc-
ture for subsequent analysis and interpretation of insights. Accordingly,
user-friendly communication in the form of alerts and notifications is trans-
mitted to the user, whereas further detection and analyses continue in the
background which is not visible to the user. The resulting communica-
tion between users and devices, and within the various connected devices is
streamlined and consistent. In this manner, IoT devices can be an inconspic-
uous part of daily human lives, while constantly enhancing the performance
of regular functions, and eliminating the involvement of human intrusion.
174 V. Kumar and P. Kotler

Examples of individual IoT applications are plenty including wearables, auto-

mated driving, and home automation, among others. For instance, Evo is a
popular health and wellness app that connects to customers’ smartphones
and wearable devices and captures data on customers’ activities such as steps,
exercise, sleep, and stress levels. The application analyzes this data to deliver
customized wellness programs designed to achieve goals set by the customers
themselves.14

Organization

At the organization level, IoT makes large-scale data capture possible—

billions of devices and objects are connected on a network, each one being
uniquely identifiable and constantly providing data that can be further
utilized to influence the devices and objects in the physical world.15 As a
result, the benefits to organizations from IoT exceed beyond sensing and
monitoring capabilities. Essentially, the data captured by the sensors involving
billions of events represents the true value of IoT.16 Such a scenario allows
firms to develop strategies and respond in ways that deliver maximum value
to the end user. For instance, the Hamburg Port Authority installed more
than 300 roadway sensors to monitor traffic in the port area and to track the
wear and tear on bridges. Sensors are also used on waterways with radar and
automatic identification systems that enable coordination of ship traffic and
offer an integrated solution to manage roadway traffic disruptions that may
occur when ship traffic requires bridge closures around the port area.17
In this regard, Kumar et al.18 propose that IoT can be viewed as a data-
oriented technology that provides firms with access to greater and more
granular data on their end customers or users. Accordingly, they contend
that IoT is foundationally based on the sensing, recording, and exchange of
real-time data about the state of devices and objects in the physical world.
This enables streamlined communication among the connected devices that
aid users in easing the performance of everyday actions. As a result, IoT-
implementing firms stand to gain by the generation of insightful marketing
actions, which is in turn made possible by the real-time collection and analysis
of end-user information.

Industry

IoT has gained a firm place in several industries, wherein all major players in
those industries employ IoT-driven solutions to deliver value-based offerings.
 7 Transformative Marketing with the Internet … 175

Prominent industries to adopt IoT on a large scale include manufacturing,

transportation, healthcare, retail, and construction.19 The insights gener-
ated from IoT data reveal patterns in consumer behaviors. Firms can utilize
these insights to provide better customer experience by offering person-
alized recommendations, real-time alerts, and relevant promotional offers.
By monitoring devices, controlling usage, and proactively initiating mainte-
nance requests, firms can expect increased productivity, improved efficiency,
and reduced operating costs. Prominent examples of IoT uses by a large
number of firms in the respective industries include supply chain manage-
ment, inventory management, and loss prevention in the retail industry;
fleet management, asset protection, and operation efficiency in the manu-
facturing industry; and device monitoring, health monitoring, and facilities
management in the healthcare industry.

National

With the rapid increase in IoT adoption among users and companies, govern-
ments are also getting actively involved in using IoT to conduct governmental
operations and manage national resources. Research has suggested the need
for national strategies for the promotion of IoT at a national level. For
instance, New and Castro20 (p. 3) suggest that considering “market failures,
the need for an innovation-friendly regulatory environment, and the need to
promote equity, governments should develop comprehensive national strate-
gies that remove obstacles and support the development and widespread
adoption of the technology.” As a result, governments around the world have
begun promoting IoT solutions actively to manage national resources such
as energy sources (e.g., solar, wind, biofuels, etc.), urban city planning, and
governmental services to citizens.
Considering governmental initiatives in IoT, companies have responded
positively with many companies investing heavily in developing IoT capabil-
ities. For instance, the adoption rate of IoT in developed countries such as
the USA, Germany, France, China, and Japan is more than 80%.21 Addition-
ally, developing countries such as Brazil and India are investing heavily in IoT
solutions. For instance, the Brazilian government announced an IoT strategy
in 2017 to accelerate its deployment to modernize private and public services
through IoT innovations and to foster entrepreneurship and new business.22
Similarly, the IoT connections in India are expected to reach 1.9 billion
in 2020 from 60 million in 2016. As a result, the Indian government is
actively involved in the adoption of IoT through initiatives such as the Smart
Cities mission that aims to “drive economic growth and improve the quality
176 V. Kumar and P. Kotler

of life of people by enabling local area development and harnessing tech-

nology, especially technology that leads to Smart outcomes” by developing
100 smart cities (p. 6).23 This includes developing smart solutions to suit
India’s needs in terms of utility management, city planning and administra-
tion, education, and citizen services, among others. Governments worldwide
are realizing that the true potential of IoT may not be realized by relying only
on market actions by companies, but also require active government partic-
ipation and monitoring. This trend will likely continue in the coming years
as this technology matures.
Overall, IoT is rapidly gaining momentum among users, firms, and
governments in recent years as a result of advancements in computing
technologies. IoT-enabled devices remotely monitor, control, and manage
a network of connected devices. The key elements of IoT include (a) the
involvement of sensors as the core of this technology that allows for the
collection of device-level data, (b) the ability to capture information regarding
physical actions, and transmit such information to elicit pre-defined reac-
tions, (c) the presence of information infrastructure, which can generate
insights in real-time, and can be instantly communicated to the connected
devices, and (d) the opportunity to make information exchange easier and
better for all the people and devices existing in a IoT-device connected
network. To conclude the overview of IoT, the following three vignettes
present the possibilities of IoT and how companies and users are deriving
value from such offerings.

Wearables

Wearables is a popular application of IoT that is gaining immense trac-

tion among users. While IoT largely involves machine-to-machine (M2M)
connectivity (e.g., sensors, RFID, etc.), the wearables operate on machine-
to-human (M2H) connectivity. This presents important implications for
marketers and product managers concerning satisfying user needs. Such
M2H applications have made technology and consumer-level data insepa-
rable. Consumers are now interacting with technology at several points in a
typical day and sharing information about themselves and with firms. They
expect products, services, and insights that are individually tailored to their
needs and preferences. Technology now provides firms with the data to create
marketing strategies, the tools to analyze and secure data, and eventually
deliver on the strategies. The granularity of available data has the power
to help firms create individually customized marketing strategies, that can
 7 Transformative Marketing with the Internet … 177

encourage greater CE with firms. In such a consumer landscape, wearable

technology is gaining a firm foothold in everyday life.
Wearables consist of devices such as fitness trackers (e.g., Fitbit, Apple
Watch, and Samsung Galaxy Fit, etc.), health monitors (e.g., continuous
glucose monitors, insulin pens, connected inhalers, etc.), and medical moni-
tors (e.g., remote patient monitoring, ingestible sensors, heart rate monitors,
etc.) (see Image 7.1). These wearables collect and process data related to
various aspects of health and fitness routines that can be used by the
user and in combination with medical practitioners to manage healthcare
options. Wearables perform a range of activities from monitoring/preventive
health functions to medical treatment functions. For instance, wearables can
measure heart rate, detect muscle activity, monitor stress levels, track sleep
patterns, and assess mental attention timelines, among others. These func-
tions may be performed by wearable devices such as wristbands, rings, or
even clothing.24 Based on the data collected and analyzed, these devices can
deliver personalized, task-specific recommendations for the users.
Further, since most wearables have open application programming inter-
faces (APIs), the involvement of third-party applications adds more value to
users and product developers. For instance, Fitbit offers wearable devices to
enable users to lead an active lifestyle. The Fitbit API enables third-party
applications to access the activity data to create solutions for gaining health
insights, making health changes, and managing health data, among others.
As a result, the device manufacturers and API developers collectively offer

Image 7.1 Wearable. Personal wearables such as the Apple Watch can perform and
monitor a wide range of actions
(Source Photo by Luke Chesser on Unsplash)
178 V. Kumar and P. Kotler

a wide range of solutions that keep users engaged in their healthcare needs.
Therefore, it should come as no surprise that the wearables industry is rapidly
growing.25

Smart Homes

With governments involved in establishing smart cities, the micro level

consists of smart homes that are evolving at a fast pace. A smart home is
a regular home, which has been augmented with various types of sensors
and actuators.26 Collectively, smart cities and smart homes aim to make
better use of available resources and enhance the quality of the services, while
reducing the operational costs involved in delivering the services.27 Further,
the creation of smart homes whereby activities are monitored and managed
augurs well for the establishment of the well-being of the users (see Image
7.2).
Research has investigated consumer well-being and has conceptualized it
as “a state of flourishing that involves health, happiness and prosperity;”28
as reflective of the personal and societal aspects of human development;29
or an alignment of individual and societal needs.30 In a NAT environment,
Kumar and Ramachandran31 conceptualize consumer well-being as a multi-
dimensional concept that describes a state of health and happiness for each
stakeholder across physical, emotional, financial, societal, and environmental

Image 7.2 Smart Homes. Consumers can connect and control their devices via
Google Home
(Source Photo by Bence Boros on Unsplash)
 7 Transformative Marketing with the Internet … 179

dimensions, as relevant to the stakeholder. The well-being concept of smart

homes is reflected in the ambient assisted living (AAL) applications of IoT
solutions that are directed at improving the lifestyle of the users.32 In this
regard,33 provide AAL to encompass technical systems to support elderly
people and people with special needs in their daily routines. Additionally,
they contend that the main goal of AAL is to achieve benefits for the indi-
vidual (increasing safety and well-being), the economy (higher effectiveness
of limited resources), and society (better living standards). As a result, an
AAL environment typically consists of services, products, and concepts that
are connected, context-sensitive, personal, adaptive, and anticipative. Such an
environment is made possible by IoT solutions that focus on user needs and
preferences.
Within smart homes, smart appliances and IoT devices simplify
consumers’ lives by automating routine tasks and reducing the need for
human intervention.34 For example, June is an intelligent oven that can iden-
tify what is being cooked via a camera, provide suggestions on the cooking
procedure, and allow remote tracking via connected devices. In combina-
tion with AI and ML analyzing IoT data continuously, consumers find
themselves receiving personalized communication and relevant insights, and
having better experiences with the devices. Evo is a popular and insightful
health and wellness app that gathers biometric data from consumers’ smart-
phones and wearables and applies data and behavioral science to deliver
custom-made wellness programs.35

Industrial Automation

Perhaps the biggest impact of IoT can be observed in the area of industrial
automation. Historically, through the various industrial revolutions, one of
the focus areas has been the reduction or elimination of human interven-
tion in industrial processes. In this pursuit, several technologies have served
(and continue to serve) industries such as information and communication
technologies, ethernet, and wireless networks, among others. Consequently,
efforts to design and model processes that are independent of routine human
interventions have typically involved a combination of sensors, devices, and
actuators.36
The notion of interconnected production processes involving automa-
tion to form a cohesive ecosystem was first propounded via agent-based
distributed manufacturing systems.37 In the current NAT environment, IoT
serves as the new technology platform through which industrial automa-
tion is planned and delivered. Further, the ecosystem is comprised of several
180 V. Kumar and P. Kotler

mechanical machinery, sector-specific systems, and related software inputs.

Specifically, the industrial automation ecosystem broadly comprises orig-
inal equipment manufacturers (OEMs) and system integrators, component
suppliers, and software/applications developers and providers.38
The development of the automation-driven ecosystem along with the
increasing use of smart technologies for industrial production has led to
the conceptualization of the term “Industry 4.0” that refers to a new-age
industrial revolution wherein Internet technologies are used to create smart
products, a smart production, and smart services.39 This is also reflected
in the following elaborate definition of IoT provided by the IEEE IoT
Community:

Internet of Things envisions a self-configuring, adaptive, complex network that

interconnects ‘things’ to the Internet through the use of standard communica-
tion protocols. The interconnected things have physical or virtual representa-
tion in the digital world, sensing/actuation capability, and a programmability
feature and are uniquely identifiable. The representation contains informa-
tion including the thing’s identity, status, location, or any other business,
social, or privately relevant information. The things offer services, with or
without human intervention, through the exploitation of unique identifica-
tion, data capture and communication, and actuation capability. The service
is exploited through the use of intelligent interfaces and is made available
anywhere, anytime, and for anything taking security into consideration.40

The global industrial automation market shows vibrancy.41 Additionally,

companies are also looking specifically at Industrial IoT (IIoT) solutions
to enhance revenue generation potential that focuses on user needs. The
IIoT offers several organizational benefits such as increasing production effi-
ciency, output management, and efficient resource deployment. Specifically,
companies are beginning to realize benefits from industrial automation that
include (a) the accurate identification of when machinery parts/components
may need replacements, (b) the identification of potential failures in co-
dependent processes that could lead to undesirable outcomes, (c) the cost
savings from eliminating nonessential maintenance, (d) the advanced analytic
insights on asset maintenance and overall productivity, and (e) the efficient
(re)deployment of maintenance and design teams by preempting equipment
failures, among others.42
 7 Transformative Marketing with the Internet … 181

IoT in the Marketing 5.0 World

IoT enables marketers to enhance customer engagement and loyalty
through interactive experiences. Through these devices and their capabilities,
marketers can (a) gain deeper customer insights to preempt/suggest solutions
for customers (e.g., notify exactly when a customer needs a new ink cartridge
for their printer), (b) tailor their messaging and offers to individual needs
and preferences, (c) understand how customers interact with their products
and identify areas for improvement, (d) analyze IoT data to predict future
customer behavior (e.g., sending a maintenance reminder before a device
breaks down), and (e) trigger contextually relevant marketing messages based
on real-time data. Expanding on the Marketing 5.0 concept discussed in
Chapter 2, this section presents how IoT operates in the Marketing 5.0
world. Particularly, this section discusses five examples of where IoT is applied
through the lens of Marketing 5.0 and establishes how such actions can also
bode well for humanity.

Data-Driven Marketing Using IoT

Data-driven marketing using IoT involves leveraging the vast amount of data
generated by Internet of Things devices to make informed decisions, person-
alize marketing strategies, and optimize customer experiences. For example,
smart fitting rooms equipped with IoT technology can provide personalized
recommendations based on customers’ body measurements and style prefer-
ences. This not only improves the shopping experience but also increases the
likelihood of making a purchase. Similarly, IoT-enabled loyalty programs can
reward customers for their engagement and purchases, fostering a sense of
loyalty and encouraging repeat business.
For instance, consider the packaging industry that is undergoing a signif-
icant transformation due to the integration of smart and connected tech-
nologies. This convergence is not only adding value to packaging but also
generating a wealth of data that can provide valuable insights to busi-
nesses, inform product design, and offer customers new experiences. One
example of this is Wiliot, a provider of ambient IoT platforms. They have
recently introduced the capability to sense and analyze humidity levels of
individual products in real-time throughout the supply chain.43 This is
made possible through their battery-free, real-time locating visibility plat-
form, which connects the digital and physical worlds using Wiliot Cloud and
Wiliot IoT Pixels. These low-cost, self-powered devices are attached to prod-
ucts and packaging, continuously transmitting data to the Cloud via standard
182 V. Kumar and P. Kotler

Bluetooth devices. This innovative solution not only reduces operational costs
and errors but also ensures the safety, integrity, freshness, and sustainability
of moisture-sensitive products on a large scale.
With the addition of humidity sensing to Wiliot’s visibility platform,
companies can now enhance their ability to safeguard moisture-sensitive
products. This feature complements the existing capabilities of temperature,
location, and carbon emissions sensing. By leveraging this comprehensive
set of data, businesses can ensure the end-to-end safety and integrity of
their products at an unprecedented scale. This is particularly crucial for
industries where moisture levels play a significant role in product quality
and freshness. Wiliot’s solution not only addresses these challenges but also
offers a cost-effective alternative to traditional tracking methodologies. By
reducing staffing requirements and operational costs, as well as minimizing
error rates, waste, mis-shipments, mis-picks, and out-of-stocks, companies
can streamline their operations and improve overall efficiency.

Predictive Marketing Using IoT

Predictive marketing takes data-driven marketing a step further, using the

power of IoT to not only understand past and present customer behavior
but also predict future actions and needs. This allows businesses to be proac-
tive and anticipate customer wants before they even arise, leading to a more
personalized and impactful marketing experience. Some of the areas in which
IoT can be used for predictive marketing include (a) generating real-time
data streams, (b) identifying patterns and predicting future behavior using AI
and ML, (c) proactive problem-solving and value creation, and (d) adjusting
prices dynamically based on usage patterns and inventory levels, among
others.
For instance, IoT technology is utilized by Procter & Gamble to improve
the manufacturing process of Pampers diapers, which are composed of fluff
pulp, plastics, absorbent granules, and elastics.44 The manufacturing process
is highly automated and involves various techniques, including streaming hot
glue and heat binding. However, if the temperature and pressure of the glue
stream are inaccurate or if the valve becomes clogged and is not promptly
addressed, the resulting diapers must be discarded. Therefore, measures must
be taken to reduce the financial impact of discarding diapers during the
manufacturing process.
The proprietary Hot Melt Optimization technique, utilized by the
company, involves the use of exclusive sensors on the assembly line to collect
data. This data, combined with Microsoft’s predictive analytics and Azure
 7 Transformative Marketing with the Internet … 183

cloud for manufacturing, allows the company to minimize diaper damage

during the manufacturing process and achieve optimal results. To closely
monitor and record glue stream temperature and pressure data, the company
also employs programmable logic industrial controllers and other sensors on
the assembly line. By feeding this data into analytics platforms and in-house
developed code, the company can identify and correct errors or anomalies
in real time without disrupting the manufacturing process. As a result, the
company consistently surpasses its previous manufacturing output since the
implementation of Hot Melt Optimization.
P&G’s manufacturing process undergoes continuous testing against
incoming data using Microsoft’s edge analytics engine in a rules-based
manner. This approach enables the company to identify necessary corrections
hours before errors occur, thereby preventing any production or material loss.
By predicting potential errors, P&G can take proactive measures to maintain
and increase production capacity while reducing unplanned downtime and
scrap generated during production. Since deploying the solution in 11 plants,
P&G estimates it has eliminated 70% of the flawed diapers that have to be
scrapped.

Contextual Marketing Using IoT

In a world where marketing messages are tailored to your current circum-

stances, seamlessly integrating into your everyday routine, the concept of
contextual marketing powered by the IoT becomes a tangible reality. Gone
are the days of generic advertisements; contextual marketing leverages real-
time information from interconnected devices to provide highly pertinent
and personalized messages precisely when they hold the most significance.
This approach fosters a more captivating customer experience, resulting in
improved conversion rates, heightened brand loyalty, and ultimately, a boost
in revenue.
For instance, London-based knitwear company Sheep Inc. is taking big
strides toward being the first carbon-negative fashion brand globally.45 To
achieve this, Sheep Inc. sources from the most environmentally friendly
sources it can find, such as manufacturers that only use renewable energy
sources or carbon-neutral farms, and then multiply the remaining carbon
footprint of each of its components by ten. The outcome of this is the
introduction of a crew neck sweater design that was made entirely of
biodegradable, ZQ-certified Merino wool. An NFC tag with a distinct serial
number is attached to the hem of every sweater. Full information about the
garment’s manufacturing process and carbon footprint can be accessed by
184 V. Kumar and P. Kotler

scanning it with a smartphone. The tag is composed of ecological plastic,

which is 100% carbon-neutral polyamide derived from renewable castor bean
oil, even though it is not yet biodegradable. When it comes time to throw
away the sweater, which will completely decompose in a year, the tag is easily
removed and recycled.
To bring in context to the company’s sustainability initiatives, Sheep Inc.
uses IoT to engage and inform customers as they move toward carbon
neutrality. The company gives users access to the identity of the sheep that
provided the wool using an RFID tag embedded in each sheep’s ear. In
addition, the tag can transmit routine updates regarding the sheep’s where-
abouts, regular activities, health, significant life events, information about its
offspring, and even when it gets a haircut. This gives customers a chance
to interact with the business, learn about its manufacturing process, and get
closer to the natural world.

Augmented Marketing Using IoT

The realm of augmented marketing with IoT involves the integration of

digital encounters into the physical world, resulting in interactive and capti-
vating brand experiences. As an example, imagine our coffee cup in the
morning displaying tailored news updates as it brews, or our grocery shelf
highlighting ingredients for a delectable meal based on our dietary prefer-
ences. Furthermore, our car windshield could project turn-by-turn navigation
enhanced with nearby points of interest. Although these scenarios may appear
imaginative, augmented marketing with IoT extends beyond mere visual
appeal. Its purpose is to revolutionize our brand interactions, rendering them
more pertinent, captivating, and ultimately, unforgettable.
For instance, consider the California-based mapping platform, Mapbox,
which allows developers to create unique interactive maps and applica-
tions for businesses.46 To improve key mapping and visualization features,
the company has now teamed up with Qualcomm Technologies, a pioneer
in the IoT and smartphone ecosystem. The Qualcomm Aware Platform’s
configurable API-first architecture was created for developers, allowing for
interoperability with partner clouds. Mapbox believes that companies in
supply chains and logistics will be able to build a complete hardware, connec-
tivity, and service solution for the specific real-time location intelligence they
require thanks to the customizable design and the ability to integrate tailored
location features with Mapbox mapping and routing APIs.
The Qualcomm Aware Platform will assist Mapbox users with real-time
asset visibility and control, whether it is determining how a winter storm
 7 Transformative Marketing with the Internet … 185

will affect operations, monitoring the length of time a shipment is sitting at a

specific location, or identifying potential hazards and finding alternate routes.
Augmenting IoT capabilities with existing features is expected to enable users
with accurate monitoring and strong connectivity even in situations where
devices are submerged, indoors, or offline.

Agile Marketing Using IoT

Agile marketing is an iterative and flexible approach to marketing that

emphasizes collaboration, adaptability, and customer feedback. When
combined with the IoT, which involves connecting physical devices to the
internet to collect and share data, marketers can leverage real-time insights
and automation to enhance their strategies. For instance, IoT can be used
in agile marketing campaigns in various ways such as using IoT sensors to
track customer behavior in physical stores, using IoT devices to collect data
about customer usage of products and services, using IoT data to trigger and
measure the effectiveness of marketing campaigns, among others.
Consider Fasal, an Indian agritech startup, that has developed an innova-
tive plug-and-play IoT solution specifically designed for farmers. This system
incorporates remote sensors that are capable of collecting real-time data on
various factors such as crop conditions, soil quality, rainfall, moisture levels,
and other weather conditions.47
By utilizing AI and ML, the collected data is processed to generate
customized insights and predictions that are delivered to farmers through
the Fasal app in their local languages. These valuable insights enable farmers
to effectively manage irrigation, control pests and diseases, apply fertilizers,
fungicides, and pesticides, and make necessary adjustments to optimize crop
growth conditions. Notably, advanced algorithms in the IoT system can even
predict seasonal crop diseases up to a week in advance, empowering farmers to
take proactive preventive measures. Additionally, this solution addresses the
important issue of over-irrigation by encouraging water conservation through
the “Water Credit” initiative. Under this initiative, farmers who maintain a
specific water level for a certain number of hours in a month are eligible for a
full refund of their monthly subscription fees. This initiative has successfully
saved billions of liters of fresh water, even in the most arid regions of India.48
Overall, the implementation of this IoT solution has resulted in a signif-
icant increase in crop yields of 30-40%, a notable reduction in pests and
diseases by 50-60%, and a substantial decrease in water usage by 30%. Conse-
quently, farmers have experienced a remarkable 50% reduction in input costs,
186 V. Kumar and P. Kotler

making their agricultural practices more agile, sustainable, and economically

viable.

Current IoT Applications in Marketing

With the emergence of IoT, the ways consumers interact with firms are
undergoing significant changes. In accommodating IoT, firms are now
increasingly focusing on delivering superior experiences and engaging with
consumers through IoT-driven offerings.49 This has resulted in firms devel-
oping IoT solutions that offer various value propositions such as novelty,
aesthetic design, convenience, low price, superior performance, and so on.
As a result, IoT has become one of the most promising technologies that not
only presents value-creating opportunities in marketing but also holds impor-
tant implications for the development of marketing strategies. This section
presents five specific application areas where IoT continues to help companies
in developing marketing initiatives.

Understanding Customer Needs to Deploy IoT

IoT allows firms to improve their capabilities which results in increased

convenience for users and ease in performing routine tasks. The connectivity
of IoT devices allows customers the convenience and flexibility of being able
to remotely monitor, control, and manage all of their connected devices at the
click of a button. For instance, smart locks such as August, Friday, and Wyze
allow remote access control reserved for authorized members of a household
and always secure the home. Such smart locks also prominently feature guest-
access controls and information logs regarding the device’s usage. In addition
to keeping homes safe, such smart devices address several consumer needs
such as reducing the stress of losing keys, the ability to lock/unlock homes
remotely, compatibility with traditional door lock systems, and pleasing
aesthetics for homes, among others.
Incorporating customer needs into developing IoT solutions is perhaps
most evident in the retail industry where retailers have implemented tech-
nologies such as geofencing for location-based marketing purposes. For
instance, fashion retailer Sephora uses geofencing via a companion store app
that uses customers’ past purchase history to suggest product recommen-
dations whenever a customer enters the store.50 Similarly, Walgreens uses
geofencing to improve participation in their rewards program by promoting
coupons and deals when customers enter the geofenced location.51 Further,
 7 Transformative Marketing with the Internet … 187

Burger King has established geofences around its competitors to woo

customers to their stores.52 Instances of other industries using IoT-driven
data include the use of telematics data (i.e., data about a moving vehicle
collected using an onboard device) in the insurance industry.53 and the use of
sensors in the real estate industry to help better manage energy usage, envi-
ronmental comfort, and security.54 A unifying theme in implementing such
geofencing activities is the firms’ attention to delivering personalized content
and offerings that their customers would prefer.

Revisiting Firm Capabilities to Integrate IoT

To successfully integrate IoT, firms must assess or reassess their capabilities

to determine the degree of firm adoption of IoT in the marketing aspect.55
The implementation of IoT in firms provides them with the ability to sense,
communicate, and respond to the needs of their environment. This creates
opportunities for firms to understand customer usage patterns and builds
on the firm’s intellectual capital that can be sold or used as the basis for
either internal innovation or external collaboration. Therefore, IoT helps
firms develop dynamic capabilities that hold important implications on the
business models of the implementing firms and help them on the path
towards establishing competitive advantage. In this regard,56 contends that
strong dynamic capabilities enable the creation and implementation of effec-
tive business models. Using this perspective, Dunaway et al.57 define IoT
capabilities as “a unique type of IT capability that relies on the network of
physical objects to sense new opportunities and threats, to move resources to
address those new opportunities, and to reconfigure IT assets.”
Alternatively, Day58 offers that since dynamic capabilities are impacted by
an inside-out orientation of the firm (i.e., a perspective that begins within the
firm and looks outward to the market), from a marketing standpoint, it limits
the firm’s ability to detect and respond to immediate market changes. In this
regard, adaptive marketing capabilities have been conceptualized to enable
organizations to be sensitive to the emerging trends in the environment, to
be agile in rapidly making necessary adjustments in implementation activities,
and to be willing to learn through experimentation.
The differences in academic perspectives notwithstanding, firms continue
to develop capabilities that can help them implement IoT in their enter-
prises. The development of such capabilities includes, among other things,
(a) the creation of an enterprise-wide data strategy that can integrate and
inform how data can power the IoT-driven initiatives, (b) the identification
188 V. Kumar and P. Kotler

of IoT to further existing and new business functionalities, (c) the develop-
ment/refinement of necessary talent pool to spearhead IoT initiatives, and
(d) the constant monitoring of customer needs and preferences to develop
appropriate IoT solutions. The benefits of developing capabilities can be seen
in the case of companies such as DHL, GE, SAP, Google, and Oracle which
have adopted continuous efforts in building firm capabilities to enable the
deployment of IoT solutions.59

Designing Marketing Mix Strategies with IoT

As mentioned earlier, IoT operates in the domain of functionality, offering

ease of use and convenience to users through the application of sensors.60
This implies that the detection and capture of real-time data through various
devices for subsequent analysis, interpretation, and implementation into
marketing activities becomes the fundamental operating principle of IoT. As
a result, reflecting the insights from the IoT devices becomes apparent when
considering the marketing mix variables. Successful companies have realized
impressive wins in each of the four key marketing mix variables—product,
price, place, and promotion, as seen from the following examples.
Product. The traditional approach to developing products involves signifi-
cant amounts of market research, customer feedback, and technical research,
among others. In the NAT environment, companies are now able to integrate
IoT at the product development stage so that the technology can continue to
be one of the key drivers of growth and usage of the product. For instance,
Diageo, the global alcohol producer, developed a “smart bottle” to enhance
the consumer experience by using printed sensor tags.61 These tags can detect
both the sealed and opened state of each bottle. This approach scores over the
conventional static quick response (QR) codes that may pose challenges in
opening and reading content. The sensor tags in the bottle can dynamically
detect if a bottle is sealed or open with the simple tap of an NFC smart-
phone. Further, the tags and the sensor information will allow Diageo to
send personalized communications to consumers who read the tags with their
smartphones. Additionally, it allows the company to send well-timed relevant
marketing messages, along with promotional offers and exclusive content.
Price. When operating in price-sensitive markets, price is a heavily used
marketing tool to ensure revenue growth and customer acquisition. In this
regard, competitive pricing strategies can appeal to price-conscious shop-
pers that can make them stay with the company. The importance of pricing
strategies can be seen in consumer-driven industries such as retail and fast-
food restaurants. For instance, in 2018, Burger King established geofences
 7 Transformative Marketing with the Internet … 189

around McDonald’s locations in the U.S. and used that to promote their
Whoppers for only one cent. For a limited time, using the Burger King app,
customers were able to get the 1-cent deal when they were within 600 feet
of a McDonald’s. With this novel method of combining an IoT application
(i.e., geofencing) with mobile capabilities, Burger King was able to attract
customers from their main competitor using a low-priced promotion deal.62
Place. Location-driven marketing actions are usually effective when the
intended reason is well-conceptualized. This is especially true in industries
such as retail and media services where hyper-localized offerings can go a
long way in engaging with customers. In such a scenario, IoT possesses the
right capabilities to not only collect continuous data but also render smart,
context-specific, highly personalized experiences, all in real time. For instance,
the beacon technology (i.e., small radio transmitters that transmit data work
over Bluetooth) is being used by many companies to provide hyper-specific,
location-targeted content, directly to users. Organizations such as Walgreens,
Major League Baseball, Kenneth Cole, and London’s Heathrow Airport have
used beacons to provide localized promotions, content, and personalized
experiences that are meant to resonate well with their user base.63
Promotion. Marketing promotions also yield immense benefits to firms
when done well at the local level and in the right context. Such a measure
would augur well for the brand (in terms of establishing relevance to its users)
and for the users (in terms of deriving value from the offerings). The power of
such promotions is best observed in consumer-facing firm actions that create
a lasting impact on the users. For instance, Nivea developed a promotional
campaign for the Brazilian market aimed at increasing customer acquisition
for their product, Nivea Sun Kids. The campaign focused on the theme of
protection and was directed at parents. A magazine ad for Nivea Sun Kids
was run that included a tear-out bracelet that could be placed on a child’s
wrist. This bracelet could be paired with the Nivea Protects app and be used
to prevent the child from becoming lost on the beach. Accompanying adults
could then identify the child on the app, and choose the distance the child
could go on the beach before an alert would sound. The app would subse-
quently receive an alert when the distance was exceeded. Further, a radar
feature allowed the adults to know if they were getting nearer or farther
from children.64 In addition to being an innovative use of the IoT, the Nivea
campaign also generated impressive sales within its product segment in that
region and had a high download rate for its app.
190 V. Kumar and P. Kotler

Driving Customer Engagement Through IoT

Customer engagement is receiving increasing attention among firms world-

wide, given its positive impact on the firm’s bottom line. Here, enjoyable
customer experiences pave the way for a positive CE and better brand
outcomes.65 Such industry impacts continue to spur innovative offerings
from firms, along with academic interest in improving CE.
Academic research has identified CE as a key success factor for firms.66 In
this regard, value contribution from customers to the firms extends beyond
just purchase transactions to also include non-purchase-related customer
behaviors.67 ,68 Pansari and Kumar69 identified the components of CE to
be direct and indirect customer contributions, and the antecedents of CE
to be satisfaction and emotion. Further, Kumar et al.70 proposed a concep-
tual framework, especially for the service setting, that identifies an interaction
orientation approach and an omnichannel model resulting in the creation
of a positive service experience. They argue that the positive service experi-
ence ultimately impacts CE by ensuring customer satisfaction and creating
emotional bonds with the firms. They also identify that customers’ perceived
variation in service experience moderates the influence of service experience
on satisfaction and emotional attachment, which ultimately impacts CE.
In the NAT environment, IoT presents various opportunities for firms
to ensure CE through their interactions and minimize variations in service
experience that could potentially enhance CE. In this regard, IoT is being
used in industrial and consumer settings to ensure CE. In industrial applica-
tions, IoT is used for various functions such as preventive maintenance (e.g.,
ABB and Hitachi use IoT solutions to monitor sensor health and optimize
production), asset management (e.g., Capgemini and the Istanbul Airport
have installed sensors to monitor building performance and ensure efficient
internal ambiance), smart energy systems (e.g., Honeywell and Verizon are
increasing their IoT capabilities by developing a platform that can host
smart sensors, controllers, and other connected pieces of hardware on elec-
tric grids that can deliver energy savings and reduce outages), and fleet
operations (e.g., fleet management companies such as Bransys use sensors
to help fleet managers monitor the performance of their vehicular assets
including temperature-controlled delivery systems, and Tesla uses over- the
-air IoT connectivity to perform software updates remotely on almost all car
operations, thereby saving trips to the service center), among others.
In consumer applications, IoT is being used for various functions such
as home security (e.g., Ring and ADT provide IoT-driven home security by
integrating features such as learning thermostats, smart plugs, home access
 7 Transformative Marketing with the Internet … 191

Image 7.3 Smart Thermostats. Smart home energy management systems such as
Nest can automatically regulate room temperature based on learning energy usage
patterns over time
(Source Photo by Dan LeFebvre on Unsplash)

control, and surveillance systems), healthcare (e.g., pharmaceutical compa-

nies such as GlaxoSmithKline and Boehringer Ingelheim develop sensors to
be used in connected inhalers to provide better treatment care and insights),
wearables (e.g., Apple Watch and Fitbit health monitoring functions through
the devices, and companies such as Ambiotex and Under Armour offer
athletic gear with built-in sensor chips for fitness tracking and monitoring),
and senior care (e.g., the water-resistant Kanega watch meets the needs of
seniors with functions such as medication reminders, GPS locator, an emer-
gency call button, and so on; and Luna Lights offers senior-friendly lighting
solutions for night time use such as illuminating pathways and emergency call
buttons), among others. Overall, IoT is being used in a variety of consumer
and industrial settings where the result seems to be improving CE (see Image
7.3).

Designing Digital Strategies with IoT

While many firms have already instituted technology components such as

sensors, IoT, 3D printing, and so on in varying measures, the challenge
of creating a unified system of network with symbiotic interdependencies
remains critical to the success of firms. Few firms have been successful in
creating such digital strategies that guide the effective implementation of
NATs. For instance, through sensor-equipped products, Nike can know with
192 V. Kumar and P. Kotler

great precision how individual customers use their shoes. This heightened
awareness can allow Nike to orient itself to its customers with far greater accu-
racy than what was possible through conventional means. Furthermore, by
strategically harnessing sensor data, Nike can also embrace its own emerging
digital ecosystem. It can, for instance, tap into other connected products such
as a Fitbit or an Apple watch, social networks such as Facebook or Twitter,
or a large community of app developers to generate new mass-customized
services.71 Such a development of a cohesive strategy has been proposed to
result in the creation of a competitive advantage.72
In this regard, Kopalle et al.73 offer that digital ecosystems can be created,
particularly by legacy firms, to create value through the establishment of
a digital customer orientation, which refers to offering customized and
enriched customer experiences by embracing digital ecosystems. They further
offer that a digital customer orientation operates on three critical concepts
viz., in-use information, digital customers, and digital experience. In the case
of the Nike example discussed above, the in-use information is apparent with
the involvement of sensors that continuously collect information regarding
current use that can also be used for generating future insights. Digital
platforms would refer to the firms’ presentation of their offerings primarily
through smartphone apps or the Internet. However, many firms continue
to deliver their offerings in the traditional and digital routes. For instance,
the same Nike consumer may use a sensor-equipped shoe for jogging but
another shoe for walking. Finally, the digital experience refers to the sharing
and amplifying of the value of the in-use information obtained from digital
customers. Nike, for instance, can amplify the value of its in-use information
generated from its sensor-equipped shoe by sharing it with other connected
products and the app developer network for developing third-party apps that
can generate even more value for the users.

Future of IoT in Marketing

IoT is emerging as a game changer for firms in the way they interact with the
end users. The rise of platforms to nurture firm-customer engagement has led
to the emergence of agents that operate between customers and providers.
In the case of NATs, and IoT in particular, emerging business models aid
in easing the processes, ushering in automation of insight generation, and
improving an organization’s capacity to track and respond to evolving user
needs. IoT is quickly gaining traction as a technology that can operate in the
 7 Transformative Marketing with the Internet … 193

background discretely while delivering functional benefits to the user in real-

time.74 This ability of IoT makes it important for organizations to include it
in their technology portfolios. In this regard, the future of IoT for marketing
purposes appears to be promising and varied. While we can expect progress
in IoT capabilities in many organizational areas, three areas that stand out are
discussed here.

IoT and Transportation

The transportation industry holds a pivotal place in the world economy

with significant socioeconomic benefits. However, the industry also creates
negative impacts on environmental systems that comprise air, water, and
soil resources.75 Given these significant negative impacts, governments and
companies are developing solutions that can counter the negative effects.
In this regard, IoT presents valuable opportunities for developing smart
transportation solutions.
Traditional methods adopted in the transportation industry often worked
in silos with limited interconnectivity. New advancements, particularly
considering IoT, are giving rise to smart transportation systems that adopt
a global view of all the components of the transportation system. The smart
use of transportation enables passengers to select a more cost-saving option
that is of a shorter distance and the fastest route, which saves a significant
amount of time and energy. Specific examples of such smart transportation
technology include sensors in vehicles for collision avoidance, anti-skidding,
efficient tracking, predictive maintenance, and so on.76
Further, smartphone apps powered by IoT are increasingly being used to
gain granular insights and offer solutions in real-time. A recent mobile-based
IoT application will enable users to determine their arrival time and manage
their schedule more efficiently across various transportation approaches. For
instance, in the Phoenix metro area, Valley Metro is launching a new version
of their smartphone app that will enable users to receive real-time travel
information, purchase tickets for both public and private transportation
modes, and utilize an optimized trip planning service that integrates taxis,
ride-sharing, and bike-sharing services.77 Such innovative offerings have the
potential to shorten travel time, thereby saving time and energy for the users,
and potentially extending resource utilization for the city governments. Addi-
tionally, this can remarkably reduce CO2 emissions and other air-polluting
gasses from transportation.
Similarly, research has proposed using data from the users’ mobile devices
to predict and manage traffic congestion.78 As a practical application of this,
194 V. Kumar and P. Kotler

the city of Mulhouse in France was able to use mobile data to measure the
pedestrian movement in the city center and understand the visitor demo-
graphics. This meant it could revitalize the business conditions of the city
by evaluating the impact of hosting events, planning business hours of the
shops in the city center, and offering timely, and relevant citizen services,
in addition to managing pedestrian flow and managing city congestion.79
Further, research has also proposed the placement of sensor units in specified
locations on the road for data collection and communication, with potential
applications for monitoring vehicular traffic, coordinating with city utility
vehicles, and administering weather advisories, among others.80 As research
continues in this area, we can expect more IoT solutions to develop smarter
transportation options.

Smart Cities

Cities worldwide are increasingly facing pressure to manage their growth and
the deployment of resources to meet their needs. The concept of smart cities
evolved in the early 2000s with the earliest conceptualization of a smart city
referring to a “…city that monitors and integrates conditions of all of its crit-
ical infrastructures…”.81 While several conceptualizations of smart cities have
been advanced, a feature that stands out in most of the conceptualizations is
the focus on computing and data technologies.82
Here, IoT can present valuable opportunities for creating smart cities
by enabling various devices and software to communicate with each other
through the Internet. Such a connection can create a network of things that
interact in a smart way that would provide innovative city development solu-
tions such as public transit solutions, public utilities and services, traffic
monitoring and management, energy consumption, infrastructure mainte-
nance, and citizen services, among others (see Image 7.4). Additionally,
building managers and property developers worldwide are looking to incor-
porate IoT devices and solutions into their infrastructures to reduce costs
and improve the quality of their buildings. In this regard, cities around the
world such as Barcelona in Spain, Las Vegas in the U.S., Padova in Italy, and
Kashiwa-no-ha in Japan have undertaken plans to develop smart cities using
IoT.

• The city of Barcelona has created an integrated city-wide fiber optics

network, providing free high-speed Wi-Fi that supports the IoT. Further,
by integrating smart water, lighting, and parking management, Barcelona
 7 Transformative Marketing with the Internet … 195

Image 7.4 IoT Warning Applications. IoT applications for smart cities such as this
one, LOCUS, provide a direct connection between the citizens and the information
system of the city in a visualized form
(Source Photo by Balázs Kétyi on Unsplash)

saved e75 million of city funds and created 47,000 new jobs in the smart
technology sector.83
• The city of Las Vegas has installed IoT sensors to manage its traffic conges-
tion and environmental issues. For instance, the sensors can detect carbon
dioxide levels and nearby traffic conditions to determine the optimal traffic
light duration by considering traffic wait times and the generation of
exhaust.84 Further, this smart city project is expected to use renewable
energy sources such as solar, wind, and water, operate as an off-the-grid
user, feature buildings with zero net energy consumption, and incorporate
photovoltaic glass in buildings so that the building exterior can operate as
solar panels.85 These proposed features in Las Vegas are possible through
IoT devices and the interconnectivity it provides.
• The city of Padova in Italy has implemented an urban IoT system,
which is a communication infrastructure that provides unified, simple,
and economical access to a plethora of public services that offer poten-
tial synergies and increase transparency to the citizens.86 The IoT system
196 V. Kumar and P. Kotler

can collect valuable city data such as temperature, humidity, light patterns,
and benzene levels (from traffic). Such information can help cities better
plan energy production and consumption for efficient usage.
• The city of Kashiwa-no-ha in Japan has adopted an energy-conscious smart
city project to promote resilience in the city. Using IoT, the city created a
smart energy management system that reduces the area’s energy usage by
26% through optimization of electricity distribution. In this connection,
Japan has adopted a national initiative known as Society 5.0, which aims
to realize a data-driven, human-centric, next-generation society that uses
NATs such as IoT. This initiative is designed to apply to all citizens of the
country, regardless of location, including the elderly population in rural
areas, and emphasizes solving social issues while harmonizing sustainability
and economic growth.87

Real-Time Buying Process and Purchasing

The adoption of NATs such as IoT allows firms to develop new business
models that are platform-based and technology driven. While the benefits of
IoT implementation are apparent on the customer-facing side of the business,
the internal benefits of such implementations may always not be the case.88
Retailers are testing IoT solutions for customer-facing and non-customer-
facing purchase instances. In terms of customer-facing purchase instances, the
Amazon Go store combines machine vision, IoT sensors, and a mobile app
swiped at the store entrance to create what it calls “just walk out technol-
ogy” (see Image 7.5). The company has created a cashier-less retail setting
where the customers can buy necessary products, charge them to their linked
Amazon account, and simply walk out of the store when done, all without
any interaction with the store employees. Such a setting not only creates
an innovative business process but also secures the company several avenues
for data collection and insights generation. In terms of non-customer-facing
settings, beacons, and smart warehouses allow retailers to make merchan-
dising and inventory management efficient. For instance, Kontakt is an IoT
provider that makes beacons that can be used to track the movement of
people and things in the commercial setting, in addition to monitoring
ambient conditions such as light, heat, humidity, and so on.
Another area where IoT is making a positive impact is with the manage-
ment of returnable transport packaging or returnable transport items (RTP/
 7 Transformative Marketing with the Internet … 197

Image 7.5 Amazon Go store. An Amazon Go store that uses a combination of

machine vision, IoT sensors, and a mobile app to facilitate contactless retail customer
transactions
(Source Photo by Simon Bak on Unsplash)

RTI) that include reusable pallets, racks, containers, trays, cylinders, crates,
and so on. This alternative to disposable packaging assumes importance in
the wake of sustainable supply chain practices expected by eco-conscious
consumers and economical operations management adopted by various
companies. In this regard, research has studied an RTI closed-loop supply
chain where the receiver of the goods sends the RTI back to the sender which
can be reused in subsequent shipments.89,90
Whereas RFID technology was used to track and monitor RTIs,91 the
solution was less than ideal given the shortcomings in the RFID tech-
nology such as heavy investment, significant coordination between manu-
facturer and channel partners, and RFID tag range considerations, among
others. IoT circumvents most of these challenges due to its wireless, low-
emission networks—such as the 0G network, which specializes in sending
and receiving messages made up of small amounts of data across long
distances. Such a solution allows organizations to track and manage RTIs
with a considerably lesser investment of time and capital.92 The logistics
industry is responding positively to this technology with companies like An
Post, an Irish logistics provider, implementing smart tracking devices that
198 V. Kumar and P. Kotler

allow them to monitor the location of their assets, and using 0G network
connectivity.93 As IoT continues to spur advances in research and practice
of developing efficient and effective connected devices, we can expect more
value-generating innovations for firms and users.

Key Terms and Related Conceptualizations

Adaptive marketing capabilities Capabilities that enable organizations to be

sensitive to the emerging trends in the
environment, to be agile in rapidly making
necessary adjustments in implementation
activities, and to be willing to learn
through experimentation
Ambient assisted living Technical systems to support elderly people
and people with special needs in their daily
routines. Typically consists of services,
products, and concepts that are connected,
context-sensitive, personal, adaptive, and
anticipative
Consumer well-being A multidimensional concept that describes a
state of health and happiness for each
stakeholder across physical, emotional,
financial, societal, and environmental
dimensions, as relevant to the stakeholder
Digital customer orientation Offering customized and enriched customer
experiences by embracing digital
ecosystems
Industrial IoT (IIoT) A network of connected devices that seeks
to enhance revenue generation potential
through a focus on user needs
Industry 4.0 A new-age industrial revolution wherein
Internet technologies are used to create
smart products, smart production, and
smart services
Internet of Things (IoT) An elaborate network of devices connected
through the Internet
IoT capabilities A unique type of IT capability that relies on
the network of physical objects to sense
new opportunities and threats, to move
resources to address those new
opportunities, and reconfigure IT assets
Smart city A city that monitors and integrates
conditions of all of its critical infrastructures
Smart home A regular home that has been augmented
with various types of sensors and actuators
(continued)
 7 Transformative Marketing with the Internet … 199

(continued)
Wearables Devices that can be worn (e.g., fitness
trackers, health monitors, medical
monitors) that collect, and process data
related to various aspects of health and
fitness routines. This data can be used by
the user and in combination with medical
practitioners to manage healthcare options

Notes and References

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204 V. Kumar and P. Kotler

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56. Teece, D. J. (2018), “Business models and dynamic capabilities,” Long
Range Planning, 51(1), 40–49.
57. Dunaway M., Y. W. Sullivan, & S. F. Wamba (2019), “Building
Dynamic Capabilities with the Internet of Things,” In Proceedings of
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58. Day, G. S. (2011), “Closing the marketing capabilities gap,” Journal of
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60. Kumar, V., D. Ramachandran, & B. Kumar (2020), “Influence of new-
age technologies on marketing: A research agenda,” Journal of Busi-
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61. Diageo (2015), “Diageo and thinfilm unveil the connected ‘smart
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62. Taylor, R. (2018), “BK Whoppers are only 1 cent when you order
at McDonald’s,” QSR Magazine, December, [accessed from https://
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206 V. Kumar and P. Kotler

63. Maycotte, H. O. (2018), “What data can a beacon actually collect?”

Multichannel Merchant, April 9, [accessed from https://multichannel
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mobile grand prix,” Ad Age, June 17, [accessed from https://adage.
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wins-mobile-grand-prix/293745].
65. A global survey found that 73% of respondents identify customer
experience as a key factor in determining their purchasing outcomes,
only 49% of the consumers say companies provide a good customer
experience today. The survey also found that 32% of global consumers
will stay away from a brand, following a bad experience—this feature
is higher in Latin America at 49% (Clark, D., & R. Kinghorn (2018),
“Experience is everything: Here’s how to get it right,” PwC , [accessed
from https://www.pwc.com/us/en/services/consulting/library/con
sumer-intelligence-series/future-of-customer-experience.html]).
66. Kumar, V., & W. J. Reinartz (2016), “Creating enduring customer
value,” Journal of Marketing, 80(6), 36–68; Verhoef, P. C., W. J.
Reinartz, and M. Krafft (2010), “Customer engagement as a new
perspective in customer management,” Journal of Service Research,
13(3), 247–52.
67. Kumar, V., & A. Pansari (2016), “Competitive advantage through
engagement,” Journal of Marketing Research, 53(4), 497–514; Pansari,
A., & V. Kumar (2017), “Customer engagement: the construct,
antecedents, and consequences,” Journal of the Academy of Marketing
Science, 1–18.
68. For more detail on customer value contributions to the firms, and
the conceptualizations of CE, please see (Kumar, V, L. Aksoy, B.
Donkers, R. Venkatesan, T. Wiesel, & S. Tillmanns (2010), “Under-
valued or overvalued customers: Capturing total customer engagement
value,” Journal of Service Research, 13(3), 297–310); (Van Doorn, J.,
K. N. Lemon, V. Mittal, S. Nass, D. Pick, P. Pirner, & P. C. Verhoef
(2010), “Customer engagement behavior: Theoretical foundations and
research directions,” Journal of Service Research, 13(3), 253–66).
69. Pansari, A., & V. Kumar (2017), “Customer engagement: the
construct, antecedents, and consequences,” Journal of the Academy of
Marketing Science, 1–18.
70. Kumar, V., B. Rajan, S. Gupta, S., & I. D. Pozza, (2019), “Customer
engagement in service,” Journal of the Academy of Marketing Science,
47(1), 138–160.
 7 Transformative Marketing with the Internet … 207

71. Ramaswamy, V., & K. Ozcan (2018), “Offerings as digitalized interac-

tive platforms: A conceptual framework and implications,” Journal of
Marketing, 82(4): 19–21.
72. Govindarajan, V., & J. R. Immelt (2019), “Digital transformation is
no longer optional for industrial companies. The problem is it’s really,
really hard,” MIT SloanManagement Review, 60(3), 24–33.
73. Kopalle, P. K., V. Kumar, & M. Subramaniam (2020), “How legacy
firms can embrace the digital ecosystem via digital customer orienta-
tion,” Journal of the Academy of Marketing Science, 48(1), 114–131.
74. Kumar, V. (2021). Intelligent Marketing: Employing New Age Technolo-
gies. Sage Publications.
75. The U.S. Environmental Protection Agency (EPA) found that in 2018
the transportation sector generated the largest share of greenhouse
gas emissions at 28%, with emissions primarily coming from burning
fossil fuel for cars, trucks, ships, trains, and planes (EPA (2020),
“Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–
2018,” EPA, March, [accessed from https://www.epa.gov/sites/produc
tion/files/2020-02/documents/us-ghg-inventory-2020-main-text.pdf).
76. Mohanty, S. P., U. Choppali, & E. Kougianos (2016), “Everything
you wanted to know about smart cities: The internet of things is the
backbone,” IEEE Consumer Electronics Magazine, 5(3), 60–70.
77. KTAR (2018), “Valley Metro testing mobile ticket app for buses, light
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78. Martín, J., E. J. Khatib, P. Lázaro, & R. Barco (2019), “Traffic
monitoring via mobile device location,” Sensors, 19(20), 4505.
79. Orange (2018), “How mobile phone data could reduce traffic jams
and train delays,” Orange, December 27, [accessed from https://www.
orange-business.com/en/magazine/how-mobile-phone-data-could-red
uce-traffic-jams-and-train-delays].
80. Al-Dweik, A., R. Muresan, M. Mayhew, & M. Lieberman (2017),
“IoT-based multifunctional scalable real-time enhanced roadside unit
for intelligent transportation systems,” In 2017 IEEE 30th Canadian
Conference on Electrical and Computer Engineering (CCECE), April,
pp. 1–6.
81. Hall, R. E. (2000), “The vision of a smart city,” In Proceedings
of the 2nd International Life Extension Technology Workshop, Paris,
France, September 28, [accessed from http://www.osti.gov/bridge/ser
vlets/purl/773961-oyxp82/webviewable/773961.pdf].
208 V. Kumar and P. Kotler

82. Please see (Washburn, D., U. Sindhu, S. Balaouras, R. A. Dines, N.

Hayes, & L. E. Nelson (2009), “Helping CIOs understand “smart
city” initiatives,” Growth, 17(2), 1-17), (Caragliu, A., C. Del Bo, &
P. Nijkamp (2011), “Smart cities in Europe,” Journal of Urban Tech-
nology, 18(2), 65–82), (Zanella, A., N. Bui, A. Castellani, L. Vange-
lista, & M. Zorzi (2014), “Internet of things for smart cities,” IEEE
Internet of Things journal , 1(1), 22–32), and (Neirotti, P., A. De
Marco, A. C. Cagliano, G. Mangano, & F. Scorrano (2014), “Cur-
rent trends in Smart City initiatives: Some stylised facts,” Cities, 38,
25–36) to learn about the various approaches in conceptualizing smart
cities.
83. Ellsmoor, J. (2019), “Smart cities: The future of urban development,”
Forbes, May 19, [accessed from https://www.forbes.com/sites/jamese
llsmoor/2019/05/19/smart-cities-the-future-of-urban-development/#
1f14fb0f2f90].
84. Horwitz, L. (2017), “Can smart city infrastructure alleviate the strain
of city growth?” Cisco, June, [accessed from https://www.cisco.com/c/
en/us/solutions/internet-of-things/smart-city-infrastructure.html].
85. Blackman, J. (2019), “Cisco to ‘make sci-fi real’ as partner in $7.5bn
Las Vegas smart city project,” Enterprise IoT Insights, August 5,
[accessed from https://enterpriseiotinsights.com/20190805/channels/
news/cisco-to-make-sci-fi-real-in-las-vegas].
86. Zanella, A., N. Bui, A. Castellani, L. Vangelista, & M. Zorzi (2014),
“Internet of things for smart cities,” IEEE Internet of Things journal ,
1(1), 22–32.
87. Buntz, B. (2020), “In Japan, Smart City Projects Have a Social
Dimension,” IoT World Today, February 26, [accessed from https://
www.iotworldtoday.com/2020/02/26/in-japan-smart-city-projects-
have-a-social-dimension/].
88. Research by (Stank, T. P., M. Crum, & M. Arango (1999), “Benefits
of interfirm coordination in food industry supply chains,” Journal of
Business Logistics, 20(2), 21) and (Stank, T. P., S. B. Keller, & P. J.
Daugherty (2001), “Supply chain collaboration and logistical service
performance,” Journal of Business Logistics, 22(1), 29–48) identified
that firms with high levels of supply chain integration and that share
collaborative channel partner relationships are more likely to adopt
technologies that streamlines information exchange and enables faster
inventory responses to changes in demand.
 7 Transformative Marketing with the Internet … 209

89. Glock, C. H. (2017), “Decision support models for managing return-

able transport items in supply chains: A systematic literature review,”
International Journal of Production Economics, 183, 561–569.
90. Wang, M., & L. Zhao (2018), “Pricing decisions and environmental
assessment in a two-echelon supply chain with returnable transport
items,” Procedia Computer Science, 126, 1792–1801.
91. Hellström, D. (2009), “The cost and process of implementing RFID
technology to manage and control returnable transport items,” Inter-
national Journal of Logistics: Research and Applications, 12(1), 1–21.
92. Sainathan, P., and A. M. Giménez (2020), “Returnable packaging
and IoT: Keys to a More Sustainable Supply Chain,” Supply Chain
Brain, January 13, [accessed from https://www.supplychainbrain.com/
blogs/1-think-tank/post/30704-returnable-packaging-and-iot-keys-to-
a-more-sustainable-supply-chain].
93. Business Wire (2020). “An post, the Irish leading mails, parcels and
ecommerce logistics company, revolutionise their supply chain,” Busi-
ness Wire, February 28, [accessed from https://www.businesswire.com/
news/home/20200228005183/en/].
94. Dooley, J. (2019), “Chicago-based Cooler Screens, leverages smart
screens powered by AI and IoT, to enhance the in-store customer
shopping experience at Walgreens,” Clickz.com, December 2019,
[accessed from https://www.clickz.com/cooler-screens-is-bringing-the-
digital-shopping-experience-to-brick-and-mortar-stores/?amp=1].
 8
Transformative Marketing with Robotics

Overview
Robots have continued to capture our imagination since their first introduc-
tion in the 1950s. While academic investigations and commercial develop-
ments in technology continue to shape the field of robotics, popular culture
has also significantly enhanced the popularity of robots in real-world usage.
Movies such as The Terminator, WALL-E , The Matrix, RoboCop, and The
Transformers have etched robots in viewers’ minds. While most of these
movies were set in futuristic times, we are beginning to witness some elements
of robots aiding human lives already.
We are assisted by robots that do specialized tasks while we refocus our
attention on things and issues that we hold dear.1 Specialized robots help
us with everyday routine tasks such as cleaning (e.g., Roomba), smart-home
video surveillance system (e.g., Lighthouse), virtual assistance (e.g., Alexa),
mealtime assistance for senior care and differently-abled people (e.g., Bestic),
personal transporter (e.g., Loomo), and so on. Robots are also involved in
powering routine and advanced tasks such as assisting in banking transactions
(e.g., Nao), serving as baristas (e.g., Café X), assisting around the home (e.g.,
Zenbo), dispensing medication (e.g., Pillo), assisting special-needs children
(e.g., Leka), and so on.
It is noteworthy that some of these robots do not perform the tasks in a
monotonous fashion, but rather learn and apply thinking as they continue to
work. Eventually, they learn more about us and our needs through their inter-
action and get better at performing their tasks. In other words, they provide
personalized service that uniquely matches the needs of every individual.

© The Author(s), under exclusive license to Springer Nature 211

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_8
212 V. Kumar and P. Kotler

Such specialized robots are a representative faction of recent technological

advancements, especially new-age technologies such as artificial intelligence
(AI). They actively shape human lifestyles in almost every aspect of daily life,
and the way they do it is through personalization.2
The prevalence and promise of robotics can be seen in its global growth.3
Specifically, automation studies specific to the United States reveal that Amer-
ican companies could invest nearly $8 trillion in automation technologies by
2030, and that rapid automation of the US service sector could eliminate jobs
two to three times more rapidly than in previous transformations.4 There-
fore, robotics presents valuable opportunities to firms and customers that
could significantly reshape how value is created and transferred in industries
worldwide.
This chapter is organized as follows. First, a brief history of the origin of
robotics is presented, followed by a definition of robotics (from a marketing
standpoint). Then, a discussion on the various classifications of robotics
is presented. Then, the role of robotics in the Marketing 5.0 concept
is discussed. Next, some marketing applications of robotics are discussed.
Finally, the future of robotics for the marketing industry is discussed.

Origin, Definition, and Classifications of Robotics

Origin

Whereas modern-day robotics offer novel and interesting applications, the

roots of robotics can be traced back several centuries to the various ancient
mechanical devices that assisted in performing physical tasks. Over the
centuries, many cultures have viewed self-operating devices, or automa-
tons, with much curiosity. Notable among such devices include Chinese
clock towers built around the tenth century BC and Greek hydraulics
devised around the first century BC. Subsequent creations that included
Arabian water clocks and figurines (first century AD), Leonardo da Vinci’s
mechanical inventions such as mechanical knight and rotor-powered flying
machines (fourteenth century AD), Descartes’ biological machines (seven-
teenth century AD), and Japanese mechanical toys (seventeenth century
AD), continued to propel human inquisitiveness and the desire to create
mechanical devices and life-like figurines that operated independently.
Early twentieth-century literary works contributed conceptualizations of
mechanical devices and humanoids such as The Wonderful Wizard of Oz
series (1900) by L. Frank Baum and the Foundation series (1951–1953) by
 8 Transformative Marketing with Robotics 213

Isaac Asimov, among others. Most notably, the terms “robot” and “robotics”
were first introduced in literary works. Specifically, the term “robot” was first
used in the 1921 Czech play R.U.R. (Rossum’s Universal Robots) which
featured mechanical beings; and the term “robotics” was first introduced
in Asimov’s short stories collection written in the 1940s.5 Largely fueled
by human imagination, the first half of the twentieth century also saw the
development of humanoid robots such as Japan’s Gakutensoku in 1927 and
Westinghouse Electric Corporation’s Elektro in 1939. Such developments
served as forebearers of future growth in biomechanical research and in aiding
humans to perform various personal and industrial tasks.
The second half of the twentieth century began to see more targeted
robotic developments that focused on specific applications centered around
performing defined tasks. This phase was spurred by research and advance-
ments in computing, programming, and machinery and government invest-
ments in building robotic capabilities. In this regard, the first industrial
robot was developed in 1959 by Unimation and subsequently installed in
General Motors in 1961 which was mainly used for moving objects. This
was followed by developments of robotic arms such as The Rancho Arm
(1963), the Orm (1965), the Tentacle Arm (1968), and the Stanford Arm
(1969), which had the flexibility of a human arm. Further, the first mobile
robot that could navigate its surroundings, Shakey, was developed in 1970
using artificial intelligence (AI) technology and fitted with audio and video
capabilities. The 1970s and 1980s produced many “firsts” in robotics such
as the first minicomputer-controlled industrial robot (1974), the first fully
electric, microprocessor-controlled industrial robot (1974), the first motor-
driven robot (1979), the first machine vision-enabled robot (1981), and the
first flexible automated assembly lines (1983), to name a few.6 The following
decades saw the spread of robotics into various disciplines such as healthcare
delivery, underwater vehicles, space exploration, human collaboration, and
home cleaning systems, among others.

Definition

Robots confirm the formal area of study known as robotics. The term robotics
has been defined as the science studying “the intelligent connection of percep-
tion to action” (p. 2).7 Featured originally in his 1942 science fiction short
story Runaround , Issac Asimov proposed the Three Laws of Robotics which
lay down a set of rules for robots to follow. While the Three Laws of Robotics
may have been advanced as a plot device in science fiction writing, public
214 V. Kumar and P. Kotler

Table 8.1 Select definition of robotics

Source Definition
International Organization for The science and practice of designing,
Standardization manufacturing, and applying robots
Lynch and Park9 The creation of machines that can
behave and think like humans
Siciliano and Khatib10 The science and technology of robots
Mentzer and Gandhi11 An automated manufacturing process

interest, and academic inquiry into robotics have since caught the imagi-
nation of many. Academic research in the field of robotics continues to be
shaped by several established research streams such as mechanical engineering,
mathematics, control systems, electrical engineering, and computer science.8
However, there is no consensus on a single definition of robotics with many
scholars and organizations presenting various definitions of robotics (see
Table 8.1).

Classification of Robots

Academic research has conceptualized robots in various ways (see

Table 8.2). Moreover, robots have been referred to as “actuated mecha-
nisms programmable in two or more axes with a degree of autonomy,
moving within its environment, to perform intended tasks” by the Inter-
national Organization for Standardization. Table 8.3 provides seven distinct
classifications of robots as identified by the International Organization for
Standardization.12

Table 8.2 Select conceptualization of robots

Study Conceptualization
Breazeal13 Being able to perceive the world, make independent decisions, and
perform coordinated actions to carry out their tasks
Kaplan14 A physical object (i.e., perceives and acts in a physical
environment), functioning in an autonomous (i.e., programmable,
trainable, and mostly controllable), and situated manner (i.e.,
constantly reacting to their environment by constantly
manipulating information and things)
Kurfess15 Machines or devices that operate automatically or by remote
control
Wilson16 Advanced intelligent systems that can “…perform rule-based work
and tend to be configurable with basic features like
authentication, security, auditing, logging, and exception
handling”
 8 Transformative Marketing with Robotics 215

Table 8.3 Classification of robots

Type of robot What does it do? Some typical examples…
Industrial robot An automatically controlled, Robots for food packaging,
reprogrammable, multipurpose material handling,
manipulator, programmable in biomedical applications,
three or more axes, which can simulators, forging/welding,
be either fixed in place or and coating applications
mobile for use in industrial
automation applications
Service robot A robot that performs useful tasks Robots for domestic tasks,
for humans or equipment entertainment, elderly
excluding industrial automation assistance, home
applications surveillance, and security,
and personal transportation
Personal service A service robot is used for a Domestic help robots, an
robot non-commercial task, usually by automated wheelchair, a
laypersons personal mobility assist
robot, and a pet exercising
robot
Professional A service robot used for a Cleaning robots for public
service robot commercial task is usually places, delivery robots in
operated by a properly trained offices or hospitals,
operator fire-fighting robots,
rehabilitation robots, and
surgery robots in hospitals
Mobile robot Is a robot that can travel under its Unmanned vehicles for land,
control water, and space travel,
robots for oil mining and
rigging, and robots for
surveillance and monitoring
Collaborative A robot designed for direct Picking and packing robots,
robot interaction with a human robots for quality
inspection, and robots for
performing surgery
Intelligent robot A robot that can perform tasks by Robots for explorations in
sensing its environment and/or remote places such as space
interacting with external sources and deep sea; gesture and
and adapting its behavior motion recognition; object
detection; and
environmental change
detection
Source ISO (2012), “ISO 8373:2012—Robots and robotic devices—Vocabulary,” Inter-
national Organization for Standardization, March, [accessed from https://www.iso.
org/obp/ui/#iso:std:iso:8373:ed-2:v1:en:term:2.6]

In terms of applications, the above-mentioned types of robots can be

broadly applied in industrial and service settings. While industrial robots
have demonstrated significant value over the decades in developing offer-
ings through their critical roles in manufacturing and industrial operations,
service robots are relatively newcomers. Popular service robots to date include
robots in the retail industry (e.g., Lowe’s “LoweBot”) to answer customer
queries and assist in-store navigation17 ; robots in healthcare such as surgical
robots, medical transportation, and telepresence18 ; robots in the media and
216 V. Kumar and P. Kotler

publishing industry19 ; and robots in the restaurant industry,20 among others.

The advent of service robots has removed the requirement of the mechanical
component from the definition of a robot. The information revolution has
substantially changed the scope of work. Much of today’s work is knowledge-
based, which can be completed with little or no physical labor. Therefore,
robots continue to serve us in varied ways, with their repertoire only expected
to increase in the future.
Overall, robotics is rapidly gaining momentum among the academic and
practitioner communities because of various real-world application possibil-
ities. In this regard, robotics is largely oriented towards executing tasks and
activities as determined by managers. Any internal intelligence possessed by
robotics is also powered by other new-age technologies (NATs) like artificial
intelligence (AI) and the Internet of Things (IoT).21 As a result, robotics is
considered a function-oriented technology that serves to integrate with other
existing technologies by performing last-mile tasks or activities as required.
Kumar and Ramachandran22 identify function-oriented technologies to allow
firms to gain increased accessibility to areas and situations that humans
cannot access safely. Further, the firm can achieve increased efficiency and
accuracy in tasks requiring precision and attention to detail. Especially in
the case of repetitive tasks, function-oriented technology can deliver consis-
tently good results, quickly and without fatigue.23 To conclude the overview
of robotics, the following three vignettes present the possibilities of robotics
in delivering valuable offerings.

Industrial and Business Applications

The robotics industry has experienced rapid growth since the first case of
the adoption of robots in a Swedish metalworks plant in 1959.24 The
robotic process automation (RPA) market also saw a similar trend.25 Such
a trend indicates the dominance of robots in the industrial setting and their
importance in developing products.
As listed in the definition mentioned earlier, industrial robots possess
certain key distinguishing characteristics valued in production and opera-
tions settings (see Image 8.1). First, industrial robots are autonomous in that
they can perform intended tasks based on information from sensors, without
human intervention. Related to this is the robots’ ability to be manipu-
lated (i.e., controlled) by an operator or a programmable controller/device.
For instance, Nguyen et al.26 have developed a proximity sensor that can
detect a human presence nearby and use that data to inform the robot of
the person’s distance and angle of approach. Developments such as these
 8 Transformative Marketing with Robotics 217

set up the stage for human–machine collaboration in a seamless manner.

Second, industrial robots can be redesigned to accommodate changes in oper-
ations without physically altering the robot. For instance, industrial robots are
being developed that can be reprogrammed within one minute using a touch-
screen interface to perform other functions.27 Third, industrial robots are also
conducive to physical alterations to suit different applications. For instance,
modifications in product lines or custom creations in manufacturing can be
easily handled by industrial robots as they would be favorable to changes in
their physical structure to handle different tasks.
In addition to their place in factories, robots hold a critical place in
routine business applications. Popularly referred to as professional service
robots, these robots are primarily used outside of factories, and in an assistive
capacity to humans rather than replace them. In the marketing literature,
service robots are defined as “…system-based autonomous and adaptable
interfaces that interact, communicate and deliver service to an organiza-
tion’s customers”.28 Often fitted with some form of mobility (fully mobile
or partly mobile), professional service robots can be found in many business
settings such as retail, hospitality, healthcare, transportation and warehousing,
construction, agriculture, space exploration, and many more. Business robots
have been implemented in several commercial settings that drive value to
corporations and users alike. The following uses provide a flavor of the various
business applications of robots:

Image 8.1 Robots in manufacturing. Robots in an automobile manufacturing plant

(Source Photo by Lenny Kuhne on Unsplash)
218 V. Kumar and P. Kotler

• Robots in Education—Personalization is a key ingredient in imparting

quality education. By factoring in students’ requirements and prefer-
ences, robots can provide individual care and attention to the student’s
learning needs. In this regard, robots are used in many education settings
such as STEM classes (e.g., Root, Cubelets) and STEAM classes (e.g.,
Nao, Pepper), PreK-5 education (e.g., Dash & Dot, LEGO WeDo), and
special-needs education (e.g., QTrobot, Leka).
• Robots in General Hygiene—Hospitals and public institutions regularly
use robots for their hygiene needs via actions such as disinfecting places,
dispensing sanitizers, trash removal, cleaning public spaces, and steril-
ization, among others. For instance, Danish company UVD Robotics
has developed a UV light system-based robot that can disinfect and kill
diseases, viruses, bacteria, and other types of harmful organic microorgan-
isms in the environment by breaking down their DNA structure, thereby
preventing and reducing the spread of infectious diseases, viruses, and
bacteria. For hospital applications, this robot can clean and disinfect public
spaces by moving autonomously from room to room, riding elevators, and
opening doors automatically. Additionally, the robot pays special attention
to infection-prone areas such as washbasins, patient beds, door handles,
and so on.29
• Robots in Healthcare: Robots in healthcare have become more advanced
in recent years, bringing in benefits for healthcare workers and patients
alike. Reflecting the recent advancements, robots involved in healthcare
fall into five broad types—(a) surgical robots (those working with the
surgeons to perform minimally invasive procedures), (b) service robots
(those performing non-patient-facing tasks to smoothen hospital opera-
tions), (c) exoskeleton robots (those that can be attached to humans that
can facilitate specific actions), (d) rehabilitation robots (those that assist
patient motion or perform actions for the patient), and (e) social robots
(those that interact with patients and are capable of complex communica-
tion involving emotional responses).30 Overall, robots have enhanced the
quality of patient care, and efficiency of the clinical processes, while also
bringing in a safe environment for the entities involved.
• Robots in Agriculture—Agriculture plays a critical role in the economic
vibrancy of nations. As a result, agricultural productivity is an area that
attracts attention from all members of the agricultural community such as
farmers, agri-marketing companies, researchers, and policymakers. In this
regard, research has established the vital role played by robots in improving
agricultural output and productivity.31 The key areas of agriculture where
robots have been implemented include seeding, application of fertilizers/
 8 Transformative Marketing with Robotics 219

pesticides, weeding, harvesting, autonomous farm vehicles, field mapping,

environmental monitoring, and many more.
• Robots for Customer Service—An area where the use of robots is perhaps
most felt is customer service, with retail and hospitality industries leading
the way. Chui et al.32 observed that the service sector is the most readily
automatable in the US economy, with almost half of the existing service-
related tasks being easily replaceable by robotics. In the restaurant industry,
for instance, robots are increasingly being used for tasks such as food
preparation, cooking, and serving food; cleaning food-preparation areas;
preparing hot and cold beverages; and collecting dirty dishes (Image
8.2). Other robotic implementations include Aloft hotels’ robot butlers
to deliver toothbrushes, razors, and room service33 ; retail service robots in
Lowe’s34 ; and Walmart’s Bossa Nova robots are used as floor cleaners, truck
unloaders, in-store pickup towers, and shelf scanners,35 among others.
• Robots for Physical Therapy—Robots are successfully used in physical
therapy and rehabilitation for people with spinal cord injuries, neurolog-
ical disorders, and strokes.36 As mentioned earlier, wearable robots, also
known as exoskeletons, support, replicate, or enhance the body’s move-
ments, thereby providing essential support for human motion.37 Popular
offerings in this category include ReWalk’s Exo-Suit, Ekso Bionic’s Ekso
NR, and Cybderyne’s Hybrid Assisted Limbs, among others.

Domestic-Oriented Technology

Domestic robots are those that are used to perform routine household tasks
and assist in everyday living.38 The tasks performed by these robots include
vacuum cleaning (e.g., Roomba, Eufy), floor washing (e.g., iLife, iRobot),
laundry and ironing (e.g., Effie, FoldiMate), cooking aids (e.g., Moley,
Julia), home security systems (e.g., Xrana, JAMOR), swimming pool cleaning
(e.g., Dolphin, Aquabot), window washing (e.g., HOBOT, Gladwell Gecko),
lawncare (e.g., Husqvarna, Robomow), butlers (e.g., Ugo, Moro), social
companionship (e.g., Pepper, Buddy), and more. Further, advancements in
robotics are gradually making domestic robots more than just expensive
gadgets.
The rapid growth in domestic applications of robotics can be attributed
to improvements in performance speed, data storing, and processing capa-
bilities.39 Robotic assistants, like Google Home, Amazon Echo, and Apple’s
Siri, can help with information search, setting the calendar, timely reminders,
connecting and controlling other home electronic devices, online shopping,
220 V. Kumar and P. Kotler

Image 8.2 Service robots. Robots serving drinks at a bar

(Source Photo by David Levêque on Unsplash)

scheduling car rides, ordering food, and many more jobs. In this regard, the
category of social robots emerged.
Social robots were developed primarily to create humanlike interactions
with robots.40 Despite this simplistic purpose, conceptualizations of social
robots are varied. Table 8.4 presents a flavor of the conceptualizations of social
robots. Further, research has uncovered that the mere presence of social robots
in the same room can have a motivating effect and lead to social facilita-
tion effects compared to human counterparts.41 Essentially, going beyond the
typical functional uses, recent home robotic creations focus on the emotional
side of the robots. For instance, Kiki is a home companion robot that
develops a unique set of traits based on how the owner interacts with her.
Further, the robot can understand emotions and feelings, learn over time, can
be affectionate, learn from other Kikis, and create meaningful experiences as a
 8 Transformative Marketing with Robotics 221

Table 8.4 Select conceptualization of social robots

Study Conceptualization
Bartneck and “…an autonomous or semi-autonomous robot that interacts
Forlizzi43 and communicates with humans by following the
behavioral norms expected by the people with whom the
robot is intended to interact.”
Breazeal44 “…those that people apply a social model to interact with
and to understand.”
Fong et al.45 “… recognizing each other and engaging in social
interactions, possessing histories, and explicitly
communicating with and learning from each other.”
Hegel et al.46 those robots that have a social interface, wherein a social
interface encloses all the designed features by which a user
judges the robot as having social qualities

companion.42 Therefore, domestic robotic applications are expected to grow

with more understanding of human relationships, robotic capabilities, and
the nature of social interactions.

Humanoid Robots

As established thus far, robots are being used to perform boring, repeti-
tive, or dangerous tasks for humans. A recent and high-profile example of
a humanoid robot is Tesla’s Optimus. On Tesla’s AI Day in 2021, CEO
Elon Musk unveiled the idea of a Tesla Bot that is friendly and can navi-
gate through the human world. While this announcement was supported by
a human walking around in a robot suit, Musk said that they would have a
prototype released by the following year. On Tesla’s AI Day 2022, Musk and
engineers on the team introduced the humanoid robot: Optimus.47 Tesla’s
vision with Optimus is to create a general-purpose, bi-pedal, autonomous
humanoid robot that can perform unsafe, repetitive, and boring tasks. To
achieve this end goal, software stacks that enable balance, navigation, percep-
tion, and interaction with the physical world need to be built. As of this
writing, Tesla is involved in rolling out Optimus at high volumes, low costs,
and high reliability.
Optimus has been designed to resemble the human body—with arms,
hands, legs, and a head. The robot also has a brain which is the central
computer located in the torso. The central computer possesses vision data
from multiple sensors so it can perceive its surroundings. It also has a visual
navigation system, managed by neural networks. The brain is also loaded
with natural motion references. For this, engineers record human motions
222 V. Kumar and P. Kotler

such as picking up boxes off a shelf, and map that motion data, which has
been optimized to adapt to real-world motion to Optimus.
Optimus is also equipped with skills such as motor torque control (i.e., the
ability to perform tasks like picking up delicate objects, following a specific
trajectory, or exerting a precise force), and the ability to discover and memo-
rize new environments. Tesla has long believed that they were in a strong
position to develop a human bot by leveraging the hardware and software
that was being used to create electric cars—which come with a degree of auto-
mated functionality. CEO Elon Musk stated “As full self-driving gets closer
and closer to generalized real-world AI, that same software is transferable to
a humanoid robot. My prediction is that the majority of Tesla’s long-term
value will be Optimus. And I am very confident in that prediction.” Tesla
predicts that the demand for Optimus could ultimately reach as many as 20
billion units soon, owing to Optimus’ abilities to facilitate the fundamental
transformation of civilization.48
Tesla’s ambitious venture into humanoid robotics with Optimus is an
example of the convergence of advanced technology and artificial intel-
ligence. As Optimus slowly steps into the world, we are witnessing the
potential for AI-driven robots to address mundane and risky tasks, alongside
creating a path towards discussion about the transformative power of robotics
in various industries. One such industry is marketing, where automation,
personalization, and AI-driven insights are already reshaping how businesses
connect with their audiences and streamline their operations. The integration
of robotics into marketing strategies enhances customer engagement, opti-
mizes product placement, and delivers innovative brand experiences. As we
look ahead, the synergy between AI-powered robots and marketing presents
exciting possibilities that could redefine how businesses interact with their
customers and how products and services are promoted and delivered.

Robotics in the Marketing 5.0 World

The rate at which the modern world is progressing exceeds all expectations.
Such progress has immensely benefitted from the confluence of NATs such as
AI, ML, and others. One particularly intriguing combination of technologies
that is gaining traction in business decision-making is intelligent automa-
tion, also referred to as cognitive automation.49 By leveraging automation
technologies such as AI, business process management, and robotic process
automation, intelligent automation streamlines operations, allocates resources
more effectively, and enhances overall efficiency. Expanding on the Marketing
 8 Transformative Marketing with Robotics 223

5.0 concept discussed in Chapter 2, this section presents how robotics and
intelligent automation operate in the Marketing 5.0 world. Particularly, this
section discusses five examples of where robotic applications are applied
through the lens of Marketing 5.0 and establishes how such actions can also
bode well for humanity.

Data-Driven Marketing Using Robotics

The integration of robotics in data-driven marketing offers numerous bene-

fits for businesses. Firstly, it allows for more efficient and accurate data
analysis, eliminating the potential for human error and bias. Secondly, it
enables marketers to personalize their marketing efforts by delivering targeted
messages and offers to individual customers based on their preferences and
behavior. Lastly, data-driven marketing robotics can help businesses opti-
mize their marketing budgets by identifying the most effective channels and
strategies for reaching their target audience.
For instance, AMP Robotics, a company based in the United States,
utilizes artificial intelligence and robotics to create recycling infrastructure
for the global supply chain. Through a data-driven approach, their AMP
Cortex high-speed robotics system automates the sorting and identification of
recyclables from mixed material streams.50 Their unique technology employs
computer vision and deep learning to guide high-speed robotics systems
in recognizing, differentiating, and recovering recyclables based on various
attributes such as color, size, shape, opacity, and more. The system also stores
data about each item it detects, providing valuable insights. According to
AMP Robotics, their sorting technology can pick up more than 80 items
per minute, which is twice the speed of a human sorter. The company has
achieved up to 150 picks per minute with their tandem units.
In addition to their sorting system, AMP Robotics offers another solution
called AMP Clarity. This solution provides data and material characteriza-
tion, allowing businesses and producers to optimize their recycling processes
by identifying which recyclables are captured and missed. With their tech-
nology deployed worldwide, AMP Robotics recovers recyclables from various
sources including municipal collection, electronic scrap, construction and
demolition debris, and organic material, thereby contributing to the efficient
utilization of valuable resources.
224 V. Kumar and P. Kotler

Predictive Marketing Using Robotics

The concept of predictive marketing using robotics combines the power of

predictive analytics with the efficiency of robotic automation. This tech-
nology can help businesses identify the most promising leads, personalize
marketing messages, and optimize marketing budgets for maximum ROI.
By leveraging predictive marketing using robotics, businesses can also deliver
personalized experiences to their customers, increase customer satisfaction,
and drive revenue growth. Particularly, predictive analytics using robotics
involves the use of sophisticated algorithms and artificial intelligence to
analyze vast amounts of data and make accurate predictions about user needs.
For instance, the Advocate Aurora Research Institute, based in Milwaukee,
USA, is utilizing predictive analytics to enhance the outcomes of surgical
care throughout its operations.51 Through a collaboration with KelaHealth,
a predictive analytics company, the institute inputs clinical and robotics data
into an intelligence platform, which employs AI to forecast patient risk based
on historical data. The resultant risk scores, which are regularly updated, will
be integrated with the electronic health record, enabling doctors to assess
a patient’s risk for a specific surgery and their recovery after the proce-
dure. Additionally, the institute leverages robotics data obtained from robotic
surgical systems to generate valuable insights that will enable surgeons to
refine their surgical techniques, achieve better outcomes, and promote fiscal
responsibility.

Contextual Marketing Using Robotics

Contextual marketing using robotics enables businesses to automate certain

marketing processes, saving time and resources. Robots can analyze vast
amounts of data quickly and accurately, allowing marketers to make data-
driven decisions and optimize their campaigns in real-time. This automation
also enables businesses to deliver personalized messages at scale, ensuring
that each customer receives content that is relevant to their specific needs
and interests. Contextual marketing using robotics revolutionizes the way
businesses connect with their customers, providing a more personalized and
efficient marketing approach.
Robots are becoming increasingly advanced, with the ability to perceive
their surroundings and respond accordingly. Recent research has led to the
development of an AI-based human–robot collaboration system that is suit-
able for use in factories.52 This system provides robots with contextual
information about their work environment and the people around them,
 8 Transformative Marketing with Robotics 225

allowing them to predict human behavior and work alongside humans on

assembly lines more effectively than ever before.
Unlike traditional human–robot systems, which can only measure the
distance between the robot and its human co-workers, the new system can
identify individual workers and even their skeletal structure. This allows the
robot to recognize each worker’s posture and anticipate their next move.
By utilizing AI, the system requires less computational power and smaller
datasets than traditional machine learning methods. In experiments, the
new system has demonstrated that such robots can operate more safely
and efficiently, without slowing down production, thanks to their ability to
understand context. As a result, context-aware robot systems are expected to
improve efficiency and safety in the workplace.

Augmented Marketing Using Robotics

Augmented marketing using robotics opens new possibilities for interac-

tive and immersive marketing experiences. Increasingly, robotics are being
integrated with virtual reality or augmented reality technologies to create
virtual shopping experiences or showcase products more engagingly and inter-
actively. Moreover, robots can be designed to meet customer needs and
preferences while working within the constraints of physical spaces, real-
time performance, and personalized assistance. This creates a unique and
memorable brand experience, leaving a lasting impression on customers.
Slice Factory, a pizza restaurant chain based in Chicago, has introduced
a revolutionary addition to its kitchen—the Pizzaiola.53 Developed by Nala
Robotics, this robotic chef can prepare and serve a variety of pizzeria-style
dishes, including pizzas, pasta, salads, burgers, and wings. The Pizzaiola is
essentially a self-contained kitchen, equipped with food storage and prepara-
tion areas, ovens, and a 7-axis robotic arm that moves seamlessly throughout
the cooking space.
When it comes to making pizzas, Pizzaiola offers an impressive range of
options. It can choose from four types of dough, four sauces, 35 cheeses, and
other toppings. The robot then proceeds to press the dough, add the sauce
and toppings, and finally cook, slice, and box the pizza. With the ability to
prepare up to 50 pizzas per hour, in various sizes ranging from 8 to 18 inches,
the Pizzaiola is a game changer for Slice Factory. Thanks to ML technology,
this robotic chef can replicate an infinite number of recipes across various
cuisines with precise accuracy, making it a versatile and efficient addition to
the kitchen.
226 V. Kumar and P. Kotler

Furthermore, Slice Factory has also embraced technology in its ordering

process, allowing customers to place orders through multi-modal kiosks,
virtual storefronts, or online platforms.54 With plans to expand nationwide
(beyond their current 12 outlets in Chicago), Slice Factory believes that the
technology provided by Nala Robotics will play a crucial role in augmenting
their growth and expanding their service.

Agile Marketing Using Robotics

Agile marketing is a modern approach that emphasizes flexibility, adapt-

ability, and quick response to changing market dynamics. When combined
with robotics, it opens a whole new realm of possibilities. Robotics can
automate various marketing tasks, enabling businesses to streamline their
processes, improve efficiency, and enhance customer experiences. Further-
more, agile marketing using robotics enhances personalization and customer
engagement. To implement agile marketing with robotics successfully, organi-
zations should start with a clear strategy and roadmap. They need to identify
the marketing tasks that can be automated and prioritize their implementa-
tion. It is crucial to select the right robotics technology that aligns with the
organization’s goals and integrates seamlessly with existing marketing systems.
For instance, Volkswagen is strategically navigating the competitive
Chinese market by focusing on intelligent driving technologies. Unlike the
slower pace of transformation in Europe, the Chinese market demands
constant innovation, pushing automotive companies and suppliers to stay
ahead. Unable to meet consumer expectations satisfactorily, Volkswagen
recently experienced a significant decline in market share in China. To address
this setback, the Volkswagen Group has committed a substantial invest-
ment of USD 2.4 billion to accelerate innovation, promote technological
localization, and enhance customer focus in China.55
To achieve these goals, Volkswagen has formed a new partnership between
its software company CARIAD and Horizon Robotics, a leading provider
of computing solutions for smart vehicles in China. This collaboration
aims to improve the development of advanced driver assistance systems and
autonomous driving systems specifically tailored for the Chinese market.
Additionally, Volkswagen has increased its investments in e-mobility research
and development, as well as design and production, to cater to the preferences
of Chinese consumers.
One area of focus for Volkswagen in China is the production of new
energy vehicles (NEVs), or battery-powered electric vehicles. In 2009, China
launched the NEV program to promote the development and introduction
 8 Transformative Marketing with Robotics 227

of new energy vehicles.56 Volkswagen plans to introduce more NEV models

in the coming years while strengthening collaboration with Chinese part-
ners in research and development, production, and supply chains. By doing
so, Volkswagen aims to better respond to consumer demands and effectively
implement its “In China, for China” strategy.57

Current Robotics Applications in Marketing

Robotic applications in marketing are increasing at a vigorous pace. With
academic research58 identifying robotics as a promising technology that not
only presents value-creating opportunities in marketing but also holds impor-
tant implications for the development of marketing strategies, the growth
in marketing applications of robots is only obvious. This section presents
five specific application areas where robotics continues to help companies in
developing marketing initiatives.

Understanding Customer Needs to Deploy Robotics

Deploying robotics is a significant call that organizations need to make. With

several business elements such as productivity, market share, technological
expertise, and a steady customer base at stake, the decision to deploy robotics
often places organizations at the crossroads of business transformation. A key
decision variable in deploying robotics pertains to how well the organiza-
tion understands its customers’ needs. This applies to business-to-business
(B2B) and business-to-customer (B2C) relationships. Since technology has
the potential to deliver answers and solutions for firm expectations, a good
understanding of a customer’s needs can prepare firms well in terms of
robotics deployment.
Often, marketers must contend with changes and trends in customer
expectations. This is largely a result of changes in various factors that include
demographic changes, prominence of NATs, changes in disposable income,
need for authenticity, environmental consciousness, social connectedness,
preference for experiences rather than products, technology-savvy, person-
alized content, and an openness to change, among others. This varied set
of factors is very different from the traditional marketing approach. Such
changes have materialized in changing customer needs that are exhibited to
marketers at the consumers’ point of usage. For instance, consider customer
needs concerning fulfillment and delivery. With companies spending more
resources to move offerings faster through the system, fulfillment and delivery
228 V. Kumar and P. Kotler

systems are now more advanced to save time and costs. In a B2B setting,
companies such as DHL are using autonomous mobile robots that can navi-
gate semi-structured warehouse spaces and delivery processes.59 Similarly, in
a B2C setting, Amazon uses more than 100,000 wheeled, flat-topped robots
called “drives” that can carry entire shelves of merchandise to workers filling
orders.60 Regardless of the business setting (i.e., B2B or B2C), improving
speed and efficiency are the goals of deploying robotics. These goals reflect
the consumer needs for immediate delivery of products and convenience of
use. Here, evaluating customer readiness for robotic deployments is critical,
and academic research continues to investigate this area.61

Revisiting Firm Capabilities to Integrate Robotics

From a resource management standpoint, Barney62 argues that a firm’s

competitive advantage is derived from its unique bundle of resources that
are difficult for competitors to duplicate. The resource-based view (RBV)
classifies resources as (1) managerial resources, (2) input-based resources, (3)
transformational resources, and (4) output resources.63 The RBV was further
extended to form dynamic capabilities that refer to companies’ search for new
resources and/or new ways of utilizing existing resources to build, integrate,
and reconfigure internal and external competencies to achieve a competitive
edge in a knowledge-based economy. The dynamic capabilities thus reflect a
firm’s processes to achieve new and innovative forms of competitive advantage
given their resources, path dependencies, and market positions.64 Further,
Eisenhardt and Martin65 emphasize the importance of dynamic capabilities
to provide quick responses to mission-critical applications in information-
intensive environments. In this regard, robotics play an important role as
information resources that involve the nature and amount of information
possessed by the firm about individual customers, competitors, and other
stakeholders. By acquiring and analyzing customer and competitor infor-
mation, robotics secures vital knowledge about key stakeholder groups in a
real-world setting that can then be used to offer customized solutions and
gain competitive advantage.
Further, the strategic flexibility of firms depends on resource identification,
acquisition, and deployment capabilities.66 While committed resources can
reduce cost outlays when demand is predictable, flexible resource configura-
tion provides the companies a buffer in meeting demand fluctuations.67 As
a result, optimal flexibility in firm resource configuration may impact firm
costs and performance.68 Successful companies such as Amazon, Walmart,
 8 Transformative Marketing with Robotics 229

Google, and Tesla reap rich dividends from the excellence of their techno-
logical competence and their integration of marketing with backend support
systems. Here, robotics can reinforce and augment these technical capabil-
ities to optimize firm resource configuration. This can be done by better
monitoring of resource usage based on an accurate assessment of changes
occurring due to supply and demand fluctuations, product customizations,
and changes in the marketing mix. As an outcome, Kumar, and Ramachan-
dran69 propose that the integration of robotics into firm functions is likely
to infuse the firm with newer capabilities such as (a) increased automation
of repetitive tasks without fatigue, (b) increased efficiency and accuracy in
tasks that require extreme precision or consistent service quality, and (c)
reduced need for human presence or intervention in unsafe, uncomfortable,
or inaccessible situations.

Designing Marketing Mix Strategies with Robotics

As mentioned earlier, robotics operates as a function-oriented technology,

offering ease of use, value, and convenience to users in an application
setting.70 Additionally, the coupling of AI and 5G network capabilities can
provide robotics with the power to learn over time and process information
more efficiently which can drive further value to users in a timely and rele-
vant manner. As a result, showcasing robotics capabilities through marketing
mix variables becomes apparent and critical to firms. Successful companies
have realized impressive wins in each of the four key marketing mix vari-
ables—product, price, place, and promotion, as seen from the following
examples.
Product. Organizations integrate robotics via three formats—(a) in
designing physical products, (b) in designing service offerings for individual
or commercial uses, and (c) meant for public consumption. In physical prod-
ucts, the focus is on delivering value as envisioned through the physical form,
actions, and abilities of the robot. Examples of robotic products include Ugo
butler, Google Home, Amazon’s Echo, iRobot, Roomba, and Aibo robotic
dog, among others. In designing service offerings for individual or commer-
cial uses, the value is delivered through a blend of a tangible physical form
and intangible functionality. The prominence of form over functionality (or
vice versa) is often determined by the usage scenario. Examples of robotic
services that can be used for individual or commercial uses include ElliQ the
elder care assistant robot, and chef robots, among others. Examples of robotic
services that are used in commercial settings include NPR’s sportswriter
230 V. Kumar and P. Kotler

robot, the autonomous medical robot Tug, Walmart’s autonomous shop-

ping cart Dash, and Wendy’s chatbot, among others. Finally, robots are also
used for delivering public services such as utility services, construction, and
information kiosks. Examples of such robots include Volvo’s robotic refuse
collector ROAR, Volvo’s autonomous load carrier HX2, and the FURO kiosk
robot.
Price. Robots have been used to facilitate price comparison among shop-
pers. Popularly known as shopping robots, or simply shopbots, they have
been used to lower search costs for users.71 Further, Chen and Sudhir72 and
Diehl et al. 73 examined how shopbots affect price competition and sensitivity
in an e-commerce setting. These robots are automated internet-based tools
that let shoppers compare prices, offerings, deals/promotions, and availability
across competing firms. Early examples of shopbots include BizRate, NexTag,
and so on. More recently, the Nao humanoid robot has been developed as a
social companion robot that can also be used for shopping trips. Specifically,
the robot can compare the prices of each item and provide customers with
the best advice.74
Research shows that though shopbots generally push prices downward,
carefully applied robots can provide many opportunities to target micro-
consumer segments based on their willingness to pay, maintain relationships,
and leverage brand names.75 According to Smith,76 robots can help retailers
find ways to maintain their price differentiation while improving the targeting
of consumers with micro-segmentation. Retailers thus have greater opportu-
nities to differentiate their products because of their careful understanding
of their target market’s preferences. The use of notification and recommen-
dation agents also helps retailers up and cross-sell products, which results in
higher sales volumes and market shares, as well as more satisfied and fulfilled
customers. Furthermore, intelligent agents such as robots protect market
share through careful competitor analysis and defense. They can increase ROI
by reducing marketing costs because they support far more customers than a
human salesperson or technical representative.77
Place. Robotics can significantly impact the final form of delivering firm
offerings to the consumer, especially when their location-based preferences
are satisfied. In this regard, robots deliver a high degree of value through their
ability to move about (in the case of mobile robots), and through their ability
to perform in the same manner and functionalities and the same level of
performance, regardless of their installed/usage location. Further, robots are
highly customizable to the usage environment and needs, and they almost
seem to fit in perfectly in all instances. These features indicate that robots
transcend place/geography restrictions and can deliver their full potential as
 8 Transformative Marketing with Robotics 231

designed by the developers. This implies that a companion robot for seniors
can serve its full potential regardless of its use in Asia or the United States,
with the right level of customized elements. As a result, robots serve a utili-
tarian purpose in serving the needs of the user/usage condition to their full
potential. This aspect of robots has enabled its rapid growth and its almost
contemporaneous use in various industries across the world.
Promotion. In addition to performing laborious and repetitive tasks, robots
have also been implemented in creative promotional activities such as sales
force assistance, advertising support, and online shopping. In the retail
setting, robots have been used to free up sales associates’ time by performing
routine and tedious tasks such as physical inspection of stores, product
placement locations, shelf stockouts, checking for special promotion tags,
cleaning and maintenance, security/surveillance, and so on. Grocery retailers
in the United States such as Giant Eagle, Schnucks Markets, Broad Branch
Market, and Walmart have implemented robots and are beginning to see
positive results.78 Firms are also using robots in automated advertising/
marketing communications efforts. Some of the current robotic applica-
tions include machines that can communicate/negotiate with other machines
without human intervention, evaluate various types of audiences, generate,
and distribute creative content, and so on.79 Finally, robots are also helping
consumers get the most out of online shopping by scouring for the best deals
online. For instance, Honey is a coupon robot that exists as a web plug-in that
works on web browsers. When users reach the checkout stage while shopping
online, Honey meanwhile works in the background looking for the cheapest
price and alerts the user to the location of the cheaper deal; thereby securing
users valuable savings. Other such robots include eBay’s ShopBot and Kelkoo
and Pricerunner in the UK.
Robotics as a Service (RaaS). We are also witnessing the emergence of
robotics as a service (RaaS), which is a pay-as-you-go, or subscription-based
service model that allows users to benefit from robotic process automation (by
leasing robotic devices and accessing a cloud-based subscription). Additional
benefits from such a model include reduced hassles of purchasing expen-
sive equipment and maintenance that comes along with it.80 In recent years,
RaaS has become popular due to its flexibility, scalability, and lower costs of
entry (compared to traditional robotics programs) it poses. Many companies,
ranging from warehouses, and security providers to healthcare facilities are
integrating RaaS into their operations.
Typically, robots were seen as instruments to replace low-paying jobs done
by humans at companies that come with expenses and take time to be realized
as returns. But RaaS allows companies to scale up and down depending on
232 V. Kumar and P. Kotler

the market conditions and client needs, while also offering predictable costs
and less upfront capital to get started. As a result of this, and the familiarity
with SaaS, many companies are warming up to the idea of implementing
RaaS, regardless of the size of the firm. Big Tech companies like Amazon,
Google, and Microsoft have developed tools to enable RaaS on a large scale
and are used in many ways. Some prominent examples of RaaS use include:

• AWS Robomaker runs large-scale and parallel simulations, and cost-

effectively scales and automates simulation workloads. It allows users to
easily create refined, randomized 3D virtual environments.
• Google is developing the Google Cloud Robotics Platform, which
combines AI, the cloud, and robotics into an open ecosystem of automa-
tion solutions that use cloud-connected collaborative robots.
• SavorEat, an Israel-based tech company, has developed a robotic system
that cooks customizable plant-based burgers. These meatless products are
created and cooked by a robot chef according to customer preferences and
at the touch of a button.

While all of this sounds very encouraging, there are things to overcome
to make the adoption of RaaS quicker. There is a lot of customization of the
hardware that goes into the process of making the robots useful for individual
organizations’ specific needs. Once the companies find a way to reduce the
time for customization, the popularity and adaptability of RaaS are expected
to increase tremendously.

Driving Customer Engagement Through Robotics

Robotics plays a critical role in providing memorable customer experiences

that in turn work towards enhancing customer engagement.81 For instance,
Elisa, a Finnish telecom company, deployed Pepper, the world’s first personal
robot that recognizes main emotions, to interact with and engage customers
in a personalized way. The personalized actions include greeting customers,
directing them to the right service member, and supporting the click-and-
collect process of customers buying online and picking up the order in-store,
all in a seamless manner to ensure meaningful engagement instances.82
Further, robots being equipped with AI and 5G capabilities implies that
programming the robots and the delivery of actions becomes instantaneous,
thereby enhancing customer engagement. For instance, by integrating AI and
5G capabilities, companies can develop robots that are autonomous or be
controlled remotely in real-time with the ability to make instant decisions
 8 Transformative Marketing with Robotics 233

that can be updated over time. Such features in robots in customer-facing

roles such as in retail, hospitality, healthcare, and aviation can significantly
enhance customer engagement.
In this regard, research has advanced the concept of Tactile Internet (TI),
which refers to a communication infrastructure combining low latency, very
short transit time, high availability, and high reliability with a high level of
security.83 Essentially, the TI will enhance human–machine interactions by
reducing the time between initiating a data transfer and the beginning of data
transfer (i.e., latency) such that real-time interactive systems can be developed
that are instantaneous and impactful.84 Such developments present impor-
tant implications for industries such as education, telesurgery, construction,
and so on that, in turn, can enhance customer engagement.
Research has also investigated the role of robotics in reducing varia-
tion in service experience delivered by firms. Specifically, Kumar et al.85
propose that the perceived variation in service experience moderates the influ-
ence of service experience on satisfaction and emotional attachment, which
ultimately impacts customer engagement. Since robots are controlled by
computer programs, they can provide standardized service without variations
and with a high degree of accuracy and precision, which is beyond human
capabilities.86 Given the same input, the output will always remain the same
across robots, time, and context, thereby enhancing customer engagement.

Designing Digital Strategies with Robotics

Robotics adds to the technological capabilities of organizations. Technological

capabilities refer to a firm’s capacity to build and employ internal technolog-
ical resources in sync with other internal resources of the firm to improvise
the existing offerings or develop a new one responding to the shifting market
conditions and consumer preferences.87 The emergence of NATs (such as
robotics) and consumer preferences to go digital compels firms to audit and
develop their technological capabilities in the form of updated technolog-
ical infrastructure such as hardware, software, and service integration. This
compulsion on firms is expected to the development of competitive advan-
tage, since the firm can respond to altered consumers’ needs and demands
more swiftly (Gupta et al. forthcoming).88 In this regard, Saboo et al.89
suggest that a firm’s capability to absorb a new set of knowledge is mainly
dependent on its existing processes and knowledge base. To become more
open to new ideas, encourage customer feedback, and involve consumers in
co-developing products, firms need to enhance customer-firm interactions via
the use of appropriate technologies. A robust technological infrastructure will
234 V. Kumar and P. Kotler

enrich the firm with comprehensive macro-level customer data in real-time,

and robotics will play a crucial role in allowing firms to generate enhanced
firm and customer value.
Firms primarily focus on personalization elements that are valued by
consumers when developing their digital strategies. The use of robotics, such
as NATs, allows for a high level of personalization, making them attractive
for customer-firm interactions. These robotics solutions can be seamlessly
integrated into various tasks, often without users even realizing they are
interacting with technology. Examples of such interactions include robotic
process automation software, robotics for senior care and assisted living, and
robots used in physical rehabilitation and therapy. When technology can
connect with users on a personal level, it fosters a strong bond. Marketers
can leverage this bond to create significant customer value. However, the
success of personalization initiatives is dependent on the availability and
quality of customer information, the ability to derive insights from this
data, and the effective implementation of these insights.90 To overcome these
constraints and enhance personalized offerings, companies are turning to
robotics-powered solutions in a digital format. The scalability of robotic solu-
tions, which can be achieved in a relatively short period with or without
human intervention, makes them a favorable choice for companies.

Future of Robotics in Marketing

An era in which robots will feature in almost all aspects of human lives is
fast approaching, the signs of which already exist. Rapidly developing robotic
technologies that become smarter and cheaper will virtually transform all
service sectors and bring opportunities for a wide range of industrial and
service innovations that have the potential to dramatically improve customer
experience, service quality, and productivity all at the same time.91 Firms
should refrain from apprehension of this trend and utilize the opportuni-
ties of this technological revolution. While firms would do well by paying
careful attention to the oncoming robotic revolution, rushing into adopting
robotics without thoughtful consideration of the implications would lead
to significant losses. The role of NATs, and specifically robotics, in driving
and facilitating technological advancements and their business uses requires
nuanced examination, as they can automate vital business processes, accen-
tuate insights and real-time decision-making, and enhance firms’ abilities to
engage with customers.92 In this regard, Xiao and Kumar93 offer a compre-
hensive view of when and how to adopt and integrate robotics into customer
 8 Transformative Marketing with Robotics 235

service operations, factors that would affect the degree of robotics adoption,
and the likely consequences of such an adoption.
Further, the ever-expanding amounts of information (relating to
customers, businesses, and markets) involved in everyday commercial oper-
ations, and the increasingly dynamic online business environment present a
huge challenge for markets to extract value. Robotics occupies a vital place in
such a transformed marketplace. In this regard, robotics will present impor-
tant opportunities in two key areas that marketers will have to pay attention
to.94 First, robotics will present increased opportunities for increased learning
and insights for companies. With further advancements in robotics, robots
will acquire the capabilities to perform ever more complex tasks by collabo-
rating, which in turn, will make marketing even more efficient and effective.
They also may increase the intensity of competition and consumer power
due to lower search costs. Further, the consumer adoption of robots may
exert downward pressure on prices for undifferentiated products, but strong
price/quality perceptions and branded variants ensure price variation in
markets. Second, robotic implementations are likely to improve the decision-
making capabilities of firms. As the plethora of robots for commercial and
personal uses increases, robots’ abilities and performance are expected to
increase further. This will provide increased efficiencies in the areas of infor-
mation handling and retrieval, inventory, and customer engagement, and
offer consumer value in the form of more convenience, better informa-
tion, and better selection. Therefore, the future of robotics for marketing
purposes appears to be promising and varied. While we can expect progress
in robotic capabilities in many organizational areas, three areas that stand out
are discussed here.

Robotics and the Interactive Service Industry

Implementing robotics is a trend that companies cannot afford to ignore.

This is especially so for customer service firms, due to the rising costs of
human labor, enhanced robotic capabilities, and declining costs of robotics.95
Technology-wise, robotics has the potential to replace human workers in
many service functions, but when it comes to customer service that involves
intensive interactions with customers, it is never a purely technical issue.96
Instead, robots will act as a useful complement to the service force, and
customers can expect to be served by a combination of a robotic and human
workforce in most service encounters over the coming years.97 So far, robots
are superior only at simple, routine, repetitive, and algorithm-based tasks
236 V. Kumar and P. Kotler

that require little creativity, expertise, and social skills, but are not appro-
priate for innovative and creative tasks that require high-order human mental
processes, which are beyond algorithmic enunciation.98 For instance, Chui
et al.99 found that less than 5% of jobs could be completely fulfilled by
robots, which holds for both manufacturing and customer service.
With regards to the service industry, Xiao and Kumar100 propose that
employee acceptance of robots, customer acceptance of robots, and the level
of human–robot interaction determine the degree of robotics adoption in
a firm. Further, they contend that in addition to these factors, firms should
consider the technical feasibility of firms, a cost-benefit analysis of robotic
deployments, and legal/ethical considerations in determining when, where,
and the extent to which robotics should be adopted in their customer service
strategy.
In terms of industry applications, interactive robots are being increas-
ingly implemented in industries such as education, healthcare, telepres-
ence, construction, defense, and transportation, among others. Technological
advancements, such as autonomous navigation, environmental sensors to
detect obstacles in the vicinity, 5G network connectivity, and AI capabilities,
have made robots more interactive, user-friendly, and endowed with oper-
ational features (see Image 8.3). Currently, a large part of the interactivity
in robots is seen in concierge-type services developed for specific applica-
tions such as in airports (e.g., robots at Heathrow Airport can communicate
with passengers in multiple languages) (see Image 8.4), retail outlets (e.g.,
Lowebots), online education (e.g., educational robots used in K-12 educa-
tion for classroom instruction), and telepresence (e.g., robots fitted with
audio/video features can place the viewer in a remote location via virtual
presence). Looking ahead, technology companies are developing more task-
agnostic robots that are not designed with a specific use-case, but instead
with a set of specific capabilities that can be used in a wide range of real-
world applications.101 If this trend were to continue, we could see a boom
in robotic deployments whereby many facets of everyday life could be filled
with robots.

Interactive Marketing

As discussed earlier, robots are being successfully used in social settings (e.g.,
personal use, homes, etc.) in an interactive service format.102, 103 Although
service tasks are generally difficult to automate, it is theorized that with
further advancements in AI towards higher intelligence tasks (i.e., from
mechanical, analytical, intuitive, to empathetic), robots can gain the ability
 8 Transformative Marketing with Robotics 237

Image 8.3 Interactive robots. Robots can be used in interactive settings in social
spaces
(Source Photo by Andy Kelly on Unsplash)

to perform several service tasks typically performed by humans.104 Inter-

estingly, some types of chatbots and robots already exhibit empathy—the
highest-order type of intelligence.
The collaborative nature of robots is most evident in interactive robots
designed to work alongside humans in a specific workspace. These robots can
integrate into various aspects of marketing. Not only can they drive essential
processes that require integration, but they can also align marketing func-
tions with company systems and objectives. These robots can synchronize and
update information across different management and marketing functions,
as well as across multiple companies. In terms of marketing applications,
these robots can provide transparency in customer relationships and sales
initiatives, incorporating reward systems into the process. Additionally, they
can gather and synthesize information for proactive marketing and future
planning. This information can be utilized to design future strategies and
enhance existing models to improve decision-making. Collaborative robots
are currently being utilized in pick and place operations, packaging processes,
quality inspections, and industrial cleaning (see Image 8.5). However, there
are also potential novel applications for collaborative robots in areas such as
farming, healthcare, aviation, and restaurants. The future holds the promise
of further innovations and improvements in collaborative robots, allowing
them to work in harmony with humans and bring value creation, efficiency,
and convenience to both business and personal uses.
238 V. Kumar and P. Kotler

Image 8.4 Robots in airports. A robot assisting passengers at Incheon airport, South
Korea
(Source Photo by Author)

Creative Content Curation

Curation as a strategy, has been conceptualized towards future-oriented activ-

ities, more specifically the set of practices that select, maintain, and manage
information in ways that are intended to promote future consumption of that
information.105 Curation106 of product, price, place, and promotion to indi-
vidual customers assume more significance for companies in this digital age
where customers are exposed to information explosion.107
Within the robotics environment, the process of curation would still
involve selecting, maintaining, and managing information. However, such
efforts may or may not involve human interference. In this regard, we are
beginning to see early applications where robots are used to curate and
deliver personalized content. Here are three cases of robots aiding in curating
content.
 8 Transformative Marketing with Robotics 239

Image 8.5 Collaborative robots in manufacturing. Collaborative robots are used

alongside humans in an industrial setting
(Source Photo by Amin Khorsand on Unsplash)

• Ria 2.0, a bot developed by Healthifyme, a health and fitness app from
India, is capable of tracking and managing daily calorie needs and workout
regimens, as well as providing suggestions on healthy lifestyle habits.108
The bot can analyze user-uploaded photos of food plates and menu card
options to identify healthy and unhealthy foods and can also consider
medical conditions to offer personalized food suggestions, diet plans, and
general information on healthy lifestyles. With the bot handling a signif-
icant portion of messages (about 20%), it demonstrates the potential of
bots in efficiently handling large volumes of data to deliver personalized
content to users with minimal human interaction.
• Mystore-E, a Tel Aviv-based clothing store, has designed its stores to
mimic the experience of a website within a store109 . Using extensive digital
displays and augmented reality, the store has enabled customers to virtually
try on products. Further, the addition of AI capabilities allowed employees
to receive notifications that match customers’ choices to provide highly
personalized and curated offerings.
• McCormick Foods is using IBM Watson to help their research and devel-
opment teams in developing new spice combinations based on insights
about customer consumption and social listening.110
240 V. Kumar and P. Kotler

Such curative actions by firms reduce consumer cognitive load and take the
responsibility of finding the best options for a consumer’s choice context to
the search platform or the brand.111 These are but only early cases of robotic
implementations. We can expect future developments in this area to develop
more value-creating offerings and services.

Key Terms and Related Conceptualizations

Collaborative robot A robot designed for direct interaction with a

human
Curation strategy The set of practices that select, maintain, and
manage information in ways that are intended
to promote future consumption of that
information
Domestic robot A robot that is used to perform routine household
tasks and assist in everyday living
Dynamic capabilities A firm’s processes to achieve new and innovative
forms of competitive advantage given their
resources, path dependencies, and market
positions
Industrial robot An automatically controlled, reprogrammable,
multipurpose manipulator, programmable in
three or more axes, which can be either fixed in
place or mobile for use in industrial automation
applications
Intelligent robot A robot that can perform tasks by sensing its
environment and/or interacting with external
sources and adapting its behavior
Mobile robot Is a robot that can travel under its control
Personal service robot A service robot is used for a non-commercial task,
usually by laypersons
Professional service robot A service robot used for a commercial task is
usually operated by a properly trained operator
Robotics The science of studying the intelligent connection
of perception to action
Robotics as a service (RaaS) A subscription-based service model that allows
users to benefit from robotic process automation
(by leasing robotic devices and accessing a
cloud-based subscription)
Robots Actuated mechanisms programmable in two or
more axes with a degree of autonomy, moving
within its environment, to perform intended
tasks
Service robot A robot that performs useful tasks for humans or
equipment excluding industrial automation
applications
(continued)
 8 Transformative Marketing with Robotics 241

(continued)
Tactile Internet (TI) A communication infrastructure combining low
latency, very short transit time, high availability,
and high reliability with a high level of security
Technological capabilities A firm’s capacity to build and employ internal
technological resources in sync with other
internal resources of the firm to improvise the
existing offerings or develop a new one
responding to the shifting market conditions
and consumer preferences

Notes and References

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3. In 2021, the global market for industrial robots was estimated
at USD 81 billion. This market is expected to grow to around
USD 129 billion by 2025 and reach around USD 165 billion by
2028 (Inkwood Research. (October 25, 2021). Size of the market
for industrial robots worldwide from 2018 to 2020, with a fore-
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2022, the sales value of the industrial robotics market world-
wide was estimated at USD 15 billion, with China, the United
States, Japan, South Korea, and Germany representing the top
five regions (Statista. (2021). Sales value of the industrial robotics
market worldwide from 2018 to 2022, by main country (in million
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mated at USD 3.4 billion and is expected to reach USD 6.8 billion
by 2025 (Loup Ventures. [2019a]. Value of the domestic consumer
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otics-market-value/.). In the same period, 13.2 million domestic
robots were shipped worldwide in 2020 and are expected to reach
nearly 30 million units by 2025 (Loup Ventures. (2019b). Unit ship-
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44. Breazeal, C. (2003), “Toward sociable robots,” Robotics and
Autonomous Systems, 42(3–4), 167–175.
45. Fong, T., I. Nourbakhsh, & K. Dautenhahn (2002), “A survey
of socially interactive robots: Concepts, design and applications,”
Robotics and Autonomous Systems, 42(3–4), 142–166.
46. Hegel, F., C. Muhl, B. Wrede, M. Hielscher-Fastabend, & G. Sagerer
(2009), “Understanding social robots,” In 2009 second international
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IEEE.
47. Biba, J. (2023), “The Tesla robot: Here’s what we know,” BuiltIn,
May 31, accessed from https://builtin.com/robotics/tesla-robot.
48. McCallum, S. (2022), “Tesla boss Elon Musk presents humanoid
robot Optimus,” BBC.com, October 1, accessed from https://www.
bbc.com/news/technology-63100636.
49. IBM (2023), “What is intelligent automation?” IBM , accessed from
https://www.ibm.com/topics/intelligent-automation.
50. Kenyon, T. (2022), “How AMP Robotics is applying AI and robotics
to recycling,” Technology, May 30, accessed from https://technolog
ymagazine.com/ai-and-machine-learning/how-amp-robotics-is-app
lying-ai-and-robotics-to-recycling.
51. Gliadkovskaya, A. (2023), “Advocate health’s research arm pilots
KelaHealth’s predictive software to assess surgical risk, improve
outcomes,” Fierce Healthcare, April 10, accessed from https://www.
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ahealths-predictive-software-improve-or-outcomes.
52. Liu, H., & Wang, L. (2021). “Collision-free human-robot collabo-
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53. Coxworth, B. (2022), “Pizzaiola aims to robotize the humble
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54. Verdict Food Service (2022), “Slice Factory to install Nala Robotics’
automated chef,” Verdict Food Service, June 30, accessed from https://
www.verdictfoodservice.com/news/slice-factory-nala-robotics/?cf-
view&cf-closed.
 8 Transformative Marketing with Robotics 247

55. Volkswagen, (2022), “Volkswagen to strengthen regional develop-

ment competence for autonomous driving in China through joint
venture between CARIAD and Horizon Robotics,” Volkswagen.com,
October 13, accessed from https://www.volkswagen-newsroom.com/
en/press-releases/volkswagen-to-strengthen-regional-development-
competence-for-autonomous-driving-in-china-through-joint-ven
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Challenges and opportunities,” World Bank, April, accessed from
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market,” ChinaDaily.com, August 28, accessed from https://www.chi
nadaily.com.cn/a/202308/28/WS64ebfc2ea31035260b81e8a4.html.
58. For more information, please see studies on robotics related to
the service sector (e.g., Achrol, R. S., & P. Kotler (2012), “Fron-
tiers of the marketing paradigm in the third millennium,” Journal
of the Academy of Marketing Science, 40(1), 35–52; Bitner, M. J.
(2017), “Service research: Rigor, relevance, and community,” Journal
of Service Research, 20(2), 103–104; Huang and Rust 2017; Wirtz
and Zeithaml 2018); customer–robot interactions (e.g., Holzwarth,
M., C. Janiszewski, & M. M. Neumann (2006), “The influence of
avatars on online consumer shopping behavior,” Journal of Marketing,
70(4), 19–36; Toure-Tillery, M., & A. L. McGill (2015), “Who or
what to believe: Trust and the differential persuasiveness of human
and anthropomorphized messengers,” Journal of Marketing, 79(4),
94–110; Kim, S., R. P. Chen, & K. Zhang (2016), “Anthropomor-
phized helpers undermine autonomy and enjoyment in computer
games,” Journal of Consumer Research, 43(2), 282–302); performance
(e.g., Herrmann, P. N., D. O. Kundisch, & M. S. Rahman (2015),
“Beating irrationality: Does delegating to IT alleviate the sunk cost
effect?” Management Science, 61(4), 831–850); impact of robots (e.g.,
Smith 2002; Huang and Rust 2018; Shankar, V. (2018), “How Arti-
ficial Intelligence (AI) is reshaping retailing,” Journal of Retailing, 94
(4), vi–xi); impact of robot laws (e.g., Olazabal, A. M., A. Cava, & R.
Sacasas (2001), “Marketing and the Law,” Journal of the Academy of
Marketing Science, 33(4), 116–118); and the antecedents and conse-
quences of robotics in customer service (e.g., Xiao, L., & V. Kumar
(2021). “Robotics for customer service: A useful complement or an
248 V. Kumar and P. Kotler

ultimate substitute?” Journal of Service Research, https://doi.org/10.

1177/1094670519878881). This is only a representative list and not
an exhaustive list.
59. Nichols, G. (2020a), “DHL expands robotic footprint with 1000
autonomous robots,” ZD Net, March 12, [accessed from https://
www.zdnet.com/article/dhl-expands-robotic-footprint-with-1000-
autonomous-robots/]; Nichols, G. (2020b), “CES 2020: Is this
robot concierge the future of service robots?,” ZD Net, January
10, [accessed from https://www.zdnet.com/article/ces-2020-is-this-
robot-concierge-the-future-of-service-robots/].
60. Rolfsen, B. (2019), “Amazon’s growing robot army keeps warehouses
humming,” Bloomberg Law, May 1, [accessed from https://news.
bloombergenvironment.com/safety/amazons-growing-robot-army-
keeps-warehouses-humming].
61. Evaluating customer readiness for robotic deployments continues
to be studied (Mims, Christopher (2010), “Why Japanese love
robots (And Americans fear them),” MIT Technology Review,
October 12, [accessed from https://www.technologyreview.com/
s/421187/why-japanese-love-robots-and-americans-fear-them]; Forl-
izzi, Jodi (2014), “How robots will work with us isn’t only
a technological question,” Harvard Business Review, March 20,
[accessed from https://hbr.org/2014/03/how-robots-will-work-with-
us-isnt-only-a-technological-question]). Meuter et al. (Meuter, M. L.,
M. J. Bitner, A. L. Ostrom, & S. W. Brown (2005), “Choosing
among alternative service delivery modes: An investigation of
customer trial of self-service technologies,” Journal of Marketing,
69(2), 61–83) refer to the consumer readiness concept as a condition
or state in which a consumer is prepared and likely to use an innova-
tion for the first time. Customer readiness is conceptualized to consist
of role clarity, motivation, and self-efficacy, and to have a substan-
tial influence on customers’ decision to adopt, attitude towards, and
the actual usage of the technology (Venkatesh, V., M. G. Morris, G.
B. Davis, & F. D. Davis (2003), “User acceptance of information
technology: Toward a unified view”, MIS Quarterly, 27(3), 425–478.;
Meuter et al., 2005; Venkatesh, V., & H. Bala (2008), “Technology
acceptance model 3 and a research agenda on interventions,” Deci-
sion Sciences, 39(2), 273–315; Kohler, C. F., A. J. Rohm, K. de
Ruyter, & M. Wetzels (2011), “Return on interactivity: The impact of
online agents on newcomer adjustment,” Journal of Marketing, 75(2),
93–108; Xiao and Kumar 2021).
 8 Transformative Marketing with Robotics 249

62. Barney, J. B. (2001), “Is the resource-based view a useful perspec-

tive for strategic management research? Yes,” Academy of Management
Review, 26(1), 41–56.
63. Menguc, B., & S. Auh (2006), “Creating a firm-level dynamic capa-
bility through capitalizing on market orientation and innovativeness,”
Journal of the Academy of Marketing Science, 34(1), 63–73.
64. Teece, D. J., G. Pisano, & A. Shuen (1997), “Dynamic capabili-
ties and strategic management,” Strategic Management Journal , 18(7),
509–533.
65. Eisenhardt, K. M. and J. A. Martin (2000), “Dynamic capabil-
ities: What are they?” Strategic Management Journal , 21(10–11),
1105–1121.
66. Johnson, J. L., R. P. Lee, A. Saini, & B. Grohmann (2003), “Market-
focused strategic flexibility: Conceptual advances and an integrative
model,” Journal of the Academy of Marketing Science, 31(1), 74–89.
67. Hansen, D. R., & M. M. Mowen (2011), Cornerstones of cost
accounting, South-Western Cengage Learning, Mason, OH.
68. Kumar, V., A. Dixit, R. R. G. Javalgi, & M. Dass (2016), “Research
framework, strategies, and applications of intelligent agent technolo-
gies (IATs) in marketing,” Journal of the Academy of Marketing Science,
44(1), 24–45.
69. Kumar, V., & D. Ramachandran (2020), “Developing a firm’s growth
approaches in a new-age technology environment to enhance stake-
holder wellbeing,” working paper, Georgia State University, GA.
70. Kumar, V., & D. Ramachandran (2020), “Developing a firm’s growth
approaches in a new-age technology environment to enhance stake-
holder wellbeing,” working paper, Georgia State University, GA.
71. Smith, M. D. (2002), “The impact of shopbots on electronic
markets,” Journal of the Academy of Marketing Science, 30(4), 446–
454.
72. Chen, Y., & Sudhir, K. (2004). When shopbots meet emails: Impli-
cations for price competition on the Internet. Quantitative Marketing
and Economics, 2, 233–255.
73. Diehl, K., Kornish, L. J., & Lynch Jr, J. G. (2003). Smart agents:
When lower search costs for quality information increase price sensi-
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74. Bertacchini, F., E. Bilotta, & P. Pantano (2017). “Shopping with a
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75. Iyer, G. and A. Pazgal (2003), “Internet shopping agents: Virtual co-
location and competition,” Marketing Science, 22(1), 85–106.
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76. Smith, M. D. (2002), “The impact of shopbots on electronic

markets,” Journal of the Academy of Marketing Science, 30(4), 446–
454.
74. Kumar, V., A. Dixit, R. R. G. Javalgi, & M. Dass (2016), “Research
framework, strategies, and applications of intelligent agent technolo-
gies (IATs) in marketing,” Journal of the Academy of Marketing Science,
44(1), 24–45.
78. Bandoim, L. (2020), “How robots are helping grocery stores during
the coronavirus outbreak,” Forbes, March 30, [accessed from https://
www.forbes.com/sites/lanabandoim/2020/03/30/how-robots-are-
helping-grocery-stores-during-the-coronavirus-outbreak/#2436a7
4b242a]; Meyersohn, N. (2020), “Grocery stores turn to robots
during the coronavirus,” CNN , April 7, [accessed from https://www.
cnn.com/2020/04/07/business/grocery-stores-robots-automation/
index.html].
79. Schultz, D. (2016), “The future of advertising or whatever we’re
going to call it,” Journal of Advertising, 45(3), 276–285.
80. Biba, J. (2022), “What is robotics as a service (RaaS)?,” BuiltIn,
October 25, accessed from https://builtin.com/robotics/robotics-as-
a-service-raas.
81. Kumar, V. (2021). Intelligent marketing: Employing new age technolo-
gies, Sage Publications.
82. Qmatic (2016), “Qmatic’s customer journey platform integrates
humanoid robot to serve customers and improve the customer
experience in New Elisa Flagship Store,” Qmatic, June 15, [accessed
from https://www.qmatic.com/meet-qmatic/news/2016/june/qma
tics-customer-journey-platform-integrates-humanoid-robot-to-serve-
customers-and-improve-the-customer-experience-in-new-elisa-fla
gship-store/?zd_source=mta&zd_campaign=13760&zd_term=vandit
agrover].
83. ITU (2014), “The tactile internet—ITU-T technology watch
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from https://www.itu.int/dms_pub/itu-t/oth/23/01/T23010000230
001PDFE.pdf].
84. Simsek, M., A. Aijaz, M. Dohler, J. Sachs, & G. Fettweis (2016),
“5G-enabled tactile internet,” IEEE Journal on Selected Areas in
Communications, 34(3), 460–473.
85. Kumar, V., B. Rajan, S. Gupta, & I. Dalla Pozza (2019b), “Customer
engagement in service,” Journal of the Academy of Marketing Science,
47(1), 138–160.
 8 Transformative Marketing with Robotics 251

86. Aron, R., S. Dutta, R. Janakiraman, & P. A. Pathak (2011), “The

impact of automation of systems on medical errors: Evidence from
field research,” Information System Research, 22(3), 429–446.
87. Moorman, C., & R. J. Slotegraaf (1999), “The contingency value
of complementary capabilities in product development,” Journal of
Marketing Research, 36(2), 239–257.
88. Gupta, S., A. Leszkiewicz, V. Kumar, T. Bijmolt, D. Potapov, “Dig-
ital analytics: Modeling for insights and new methods,” forthcoming,
Journal of Interactive Marketing.
89. Saboo, A. R., A. Sharma, A. Chakravarty, & V. Kumar (2017),
“Influencing acquisition performance in high-technology industries:
The role of innovation and relational overlap,” Journal of Marketing
Research, 54(2), 219–238.
90. Arora, N., X. Dreze, A. Ghose, J. D. Hess, R. Iyengar, B. Jing, Y.
Joshi, V. Kumar, N. Lurie, S. Neslin, S. Sajeesh, M. Su, N. Syam, J.
Thomas, & Z. J. Zhang (2008), “Putting one-to-one marketing to
work: Personalization, customization, and choice,” Marketing Letters,
19(3), 305–321.
91. Wirtz, J., & V. Zeithaml (2018), “Cost-effective service excellence,”
Journal of the Academy of Marketing Science, 46(1), 59–80.
92. Kumar, V. (2021). Intelligent marketing: Employing new age technolo-
gies. Sage Publications.
93. Xiao, L., & V. Kumar (2021). “Robotics for customer service: A
useful complement or an ultimate substitute?” Journal of Service
Research, https://doi.org/10.1177/1094670519878881.
94. Kumar, V., A. Dixit, R. R. G. Javalgi, & M. Dass (2016), “Research
framework, strategies, and applications of intelligent agent technolo-
gies (IATs) in marketing,” Journal of the Academy of Marketing Science,
44(1), 24–45.
95. Frick, W. (2014), “Experts have no idea if robots will steal your
job,” Harvard Business Review, August 8, [accessed from https://
hbr.org/2014/08/experts-have-no-idea-if-robots-will-steal-your-job];
Miremadi, M., S. Narayanan, R. Sellschop, & J. Tilley (2015), “The
age of smart, safe, cheap robots is already here,” Harvard Business
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96. Xiao, L., & V. Kumar (2019). “Robotics for customer service: A
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97. Miremadi, M., S. Narayanan, R. Sellschop, & J. Tilley (2015), “The

age of smart, safe, cheap robots is already here,” Harvard Business
Review, June 15, [accessed from https://hbr.org/2015/06/the-age-of-
smart-safe-cheap-robots-is-already-here]; Shah, J. (2016), “Robots are
learning complex tasks just by watching humans do them”, Harvard
Business Review, June 21, [accessed from https://hbr.org/2016/06/rob
ots-are-learning-complex-tasks-just-by-watching-humans-do-them].
98. Miremadi, M., S. Narayanan, R. Sellschop, & J. Tilley (2015), “The
age of smart, safe, cheap robots is already here,” Harvard Business
Review, June 15, [accessed from https://hbr.org/2015/06/the-age-of-
smart-safe-cheap-robots-is-already-here]; Nedelescu, L. (2015), “We
should want robots to take some jobs,” Harvard Business Review,
June 5, [available at https://hbr.org/2015/06/we-should-want-robots-
to-take-some-jobs]; Torres, N. (2015), “Research: Technology is only
making social skills more important,” Harvard Business Review,
August 26, [accessed from https://hbr.org/2015/08/research-techno
logy-is-only-making-social-skills-more-important].
99. Chui, M., J. Manyika, & M. Miremadi (2016), “Where machines
could replace humans—And where they can’t (yet),” McKinsey Quar-
terly, July, [accessed from https://www.mckinsey.com/business-fun
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100. Xiao, L., & V. Kumar (2021). “Robotics for customer service: A
useful complement or an ultimate substitute?” Journal of Service
Research, 24(1), 9–29.
101. Nichols, G. (2020b), “CES 2020: Is this robot concierge the future
of service robots?,” ZD Net, January 10, [accessed from https://www.
zdnet.com/article/ces-2020-is-this-robot-concierge-the-future-of-ser
vice-robots/]
102. Various studies have been conducted on the impact of robotics
in human-centric settings. For example, Čaić, M., Mahr, D., &
Oderkerken-Schröder, G. (2019). Value of social robots in services:
social cognition perspective. Journal of Services Marketing, 33(4),
463–478, examine if social robots can evoke a similar social response
as human agents and find evidence that the elderly humanize the
robots, exhibit warmth and competence judgements in their inter-
actions with them.
103. A study by Mende, M., Scott, M. L., Van Doorn, J., Grewal, D., &
Shanks, I. (2019). Service robots rising: How humanoid robots influ-
ence service experiences and elicit compensatory consumer responses.
 8 Transformative Marketing with Robotics 253

Journal of Marketing Research, 56(4), 535–556, investigate customers’

response to humanoid service robots versus human service providers,
giving empirical evidence of the uncanny valley—a phenomenon
that that interacting with humanoid robots makes people uncomfort-
able. The insights from a series of experiments shows that customer
interacting with humanoid robots engage in compensatory behavior
(for example, status signaling, social belonging, or increased food
consumption) to reduce the threat to self-identity.
104. Huang, M. H., & R. T. Rust (2017), “Technology-driven service
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because the offerings were poorly curated. It is established that
customer engagement improves with better curation (Karp, P. D.
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ware?” Database, December, [accessed from https://doi.org/10.1093/
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standing the role of artificial intelligence in personalized engagement
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 9
Transformative Marketing Using Drones

Overview
Drones have been receiving increasing attention among companies, largely
due to their varied applications in real-world uses. Formally known as
unmanned aerial vehicles (UAVs), enterprise drones (i.e., drones used by
commercial enterprises in their regular operations) have captivated businesses
and users alike for their multipurpose civilian uses. However, drones were
first developed for use in specialized military operations. Since their initial
development, the commercial applications of drones have been muted, until
recently.1
From a business standpoint, the developer community continues to serve
as a major source of growth drivers by developing various commercial uses
and applications for drones. Some of the popular uses of drones currently
include asset tracking and management, preventive maintenance, environ-
mental management, security and surveillance, media, and photography, and
so on. Further, drones have emerged as a valuable NAT in several industries
such as agriculture, construction, transportation and warehousing, mining,
insurance, and civil services such as law and order, emergency operations,
and disaster management, in addition to becoming a popular hobby.2
Further, many companies have expressed optimism about the growth and
adoption of drones in the coming years. On the consumer side, nearly
65% of Americans expect that in the next 20 years, most deliveries in
major cities will be made by robots or drones rather than humans.3 As
seen in the case of other NATs, drone applications are also expected to
increase even further as they develop advanced capabilities, receive regulatory

© The Author(s), under exclusive license to Springer Nature 255

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_9
256 V. Kumar and P. Kotler

support, enjoy consumer acceptance, and witness advancements in public

infrastructure.4 In this regard, the marketing applications of drones appear
to be particularly appealing as businesses strive to demonstrate and deliver
value-enriching offerings.
This chapter is organized as follows: A brief history of the origin of drones
is presented, followed by a definition of drones (from a marketing stand-
point). Then, a discussion on the various classifications of drones is presented
spanning military, consumer, and business applications, with a special focus
on disaster response applications. Next, marketing applications of drones
focusing on understanding customer needs, revisiting firm capabilities to
integrate drones, designing drone-focused marketing mix strategies, driving
customer engagement (CE) through drones, and designing digital strategies
with drones are discussed. Finally, the future of drones for the marketing
industry is discussed through specific business and customer-facing tasks
such as businesses’ enhanced ability to establish CE, and ways of advancing
customer contact solutions.

Origin, Definition, and Classification of Drones

Origin

The UAVs have their origins in military actions with the earliest instance
being unmanned balloons loaded with explosives used when Austria attacked
Venice in 1849. While these balloons did not involve technology, the first
technological creation of UAVs occurred in 1916 during World War I. The
United States developed the Kettering Bug, an aerial torpedo that was capable
of striking ground targets. However, the war ended before the Bug could be
deployed. Subsequent advancements of the Bug led to the development of
the first remote-controlled aircraft called the Radioplane OQ-2 in 1941.5
Drones borrow their name from the male bees that have limited and
focused use in the bee community—i.e., to mate with a fertile queen bee.
They were first introduced to the public as remotely controlled aircraft
for a battleship weapon’s target practice. Examples of such drones include
the Fairy Queen and the De Havilland Queen Bee seaplane introduced
during World War I.6 The following decades witnessed the development of
drones for various military purposes such as battlefield operations, surveil-
lance and reconnaissance, communications, delivery, and relief measures,
among others. More recent sophistication in drones relates to capabilities on
performance, flying at higher altitudes, better fuel efficiency, covering longer
 9 Transformative Marketing Using Drones 257

distances, solar-based models, and so on. Now, drones are not restricted only
for military purposes but are being successfully used in commercial applica-
tions such as environmental assessment, goods transportation, security, media
and photography, agriculture, rescue operations, and many more.

Definition

While the concept of a drone may seem straightforward, the definition of a

drone is far from it. The definition of a drone varies based on terminologies
used, applications/markets served, and physical/technical characteristics. A
drone can, therefore, be “defined” based on these three aspects. The following
discussion provides a brief overview of these three aspects that can be illustra-
tive in demonstrating the difficulty in identifying a widely accepted definition
of drones.
Regarding the terminologies used, several terms such as unmanned aerial
vehicle (UAV), unmanned aircraft system (UAS), remotely piloted vehicle
(RPV), remotely piloted aircraft (RPA), remotely piloted aircraft systems
(RPAS), and drones have appeared in the literature. Table 9.1 explains these
terms. While all these terms refer to the basic concept of driverless flight
onboard, the level of overlap between these terms indicates the complex
nature of drones. Going forward, in this chapter, we will use the term “drone”
to refer to unmanned aircraft that fly as per human-assisted commands and
are capable of flying autonomously.
Regarding the applications/markets served, drones continue to be used in a
wide range of settings. The Association for Unmanned Vehicle Systems Inter-
national (AUVSI) identifies the following five markets for drones—academic
market (i.e., for scientific research purposes), civil market (i.e., for govern-
ment non-military purposes such as the first responders), commercial market
(i.e., uses developed by for-profit businesses), consumer market (i.e., for
individual consumers and hobbyists), and military market (i.e., for military
purposes).14,15

Classification of Drones

Drones are also understood based on their physical/technical characteristics.

Drone characteristics such as wing systems, autonomy, size, energy source,
payload, and sensors have been identified as particularly prominent in under-
standing and classifying drones.16 These drone characteristics are discussed
briefly here.
258 V. Kumar and P. Kotler

Table 9.1 Similar terms relating to drones

Term General description Reference
Unmanned Aerial vehicles that provide wireless connectivity by Zeng et al.7
aerial transmitting data remotely, and typically without an
vehicle onboard pilot
(UAV)
Unmanned An aerial system is made up of many sub-systems that Austin8 ;
aircraft include the aircraft, its payloads, and the control Watts
system station(s). Essentially, it’s an aircraft with its crew et al.9
(UAS) removed and replaced by a computer system and a
radio link
Remotely Class of UAVs designed to have some degree of Larm10
piloted interaction with a human controller via a data link
vehicle but may possess autonomous flight control
(RPV) capability
Remotely A sub-category of an unmanned aircraft where the ICAO11
piloted flying pilot is not on board the aircraft
aircraft
(RPA)
Remotely A set of configurable elements consisting of an RPA, ICAO12
piloted its associated remote pilot station(s), the required
aircraft command and control links, and any other system
systems elements as may be required, at any point during
(RPAS) flight operation
Drone An unmanned aircraft that can fly autonomously Villasenor13

Wing systems. This relates to the wing system of the drone. Three broad
types of wing systems have been identified.

• Fixed-Wing Systems. Refers to fixed, static wings in combination with

forward airspeed to generate lift. Therefore, these drones are built to
cover long distances. Such drones can be seen in military operations and
delivering relief measures (see Image 9.1).
• Multirotor Drones. Such drones are equipped with multiple small rotors,
at least four. Known for their ability to hover in the air, be noiseless, and
be lightweight, these drones are ideally suited for aerial photography and
carrying small loads. However, they can remain airborne only for a short
duration (see Image 9.2).
• Hybrid Systems. Possess characteristics of fixed-wing systems and multi-
rotor drones. Ongoing research on these drones has developed models that
can stay airborne for a longer duration, be powered by batteries and elec-
tric motors, and fly longer without having to refuel. Such drones can be
useful in conducting research and performing search and rescue operations,
especially in hazardous conditions.
 9 Transformative Marketing Using Drones 259

Image 9.1 Fixed-wing drone

(Source Image by US Air Force Photo / Lt. Col. Leslie Pratt)

Image 9.2 Multirotor drone

(Source Image by Inmortal Producciones from StockSnap)

Autonomy. Drones have some degree of autonomy, owing to the absence

of an in-flight operator. Here, the distinction between autonomous systems
and automatic systems provided by the US Department of Defense (US
DoD) is critical.17

• Automatic Systems. Fully preprogrammed systems that act repeatedly and

independently of an external influence or control. While automatic systems
can be self-steering or self-regulating and can follow an externally given
260 V. Kumar and P. Kotler

path while compensating for small deviations caused by external distur-

bances; they are unable to define the path according to some given goal or
to choose the goal dictating its path.
• Autonomous Systems. Self-directed systems perform towards a goal in that
they do not require outside control, but rather are governed by laws and
strategies that direct their behavior. In this sense, an autonomous system is
self-directed by choosing the behavior it follows to reach a human-directed
goal. Most notably, they cannot exercise a “freedom of choice”.
• The US DoD identifies the following four levels of autonomy—(a) human-
operated (a human operator makes all decisions), (b) human-delegated (the
vehicle can perform many functions independently of human control when
delegated to do so), (c) human supervised (the system can perform a wide
variety of activities when given top-level permissions or direction by a
human), and (d) fully autonomous (the system receives goals from humans
and translates them into tasks to be performed without human interaction)

Size. The size of drones is a key character to understand and classify

drones. Clarke18 contends the size of drones is the most important factor
in recognizing the distinct categories of drones, and classifies drones as (a)
large drones (100 kg–150 kg), (b) mini-drones (20–30 kg), (c) micro-drones
(0.1kg–7 kg), and (d) nano-drones (“smart dust” or “smart particles”). As a
result of the varying sizes, these drones would likely serve different markets
and applications. For instance, while large drones could be used in commer-
cial applications such as transportation and rescue operations; micro-drones
could be used in applications such as reconnaissance and environmental
monitoring.
Energy Source. Drones are typically powered by one of the following
energy sources such as (a) traditional airplane fuel (e.g., kerosene) that is
primarily used in fixed-wing drones, (b) battery cells (e.g., rechargeable
battery cells) that are used in multirotor drones, (c) fuel cells meant for use
in fixed-wing drones, and (d) solar cells meant for use in fixed-wing drones.
Payload. This refers to the weight a drone can carry. While it does not
include the weight of the drone itself, it does include anything placed or
fitted in the drone such as sensors, task-related equipment (e.g., camera,
weapon, etc.), and items for delivery/transportation. Therefore, smaller-sized
drones typically used for hobby purposes are expected to have a lower payload
(less than 2 kg (i.e., 4.4 lbs)), while drones used for military or professional
purposes are expected to have a higher payload (even up to 200 kg). Further,
the payload handling range is jointly determined by the flying time and flying
range of the drone. Therefore, while hobby drones are designed to maximize
 9 Transformative Marketing Using Drones 261

flight time and flight range, the payload capacity is often not too high. Simi-
larly, for drones involved in rescue and relief missions, payload capacity could
be prioritized over flight time and flight range.
Sensors. Sensors are an important category of payload included in drones.
Examples of sensors include cameras, microphones, and scientific sensors
used for various purposes such as testing, measurement, security, and many
more. Drones being developed now often include cameras and microphones.
The popular audio/video uses of sensors include security monitoring, surveil-
lance, access control, intelligence gathering, cartography, geo-mapping, land
surveys, archeological surveys, wildlife photography, and media and enter-
tainment, among others. The popular types of scientific sensors include
biological/chemical/meteorological sensors for various measurement and
testing purposes, sensors for testing environmental emissions, surveying
landfills, estimating environmental degradation and pollution, scientific
studies involving data collection, agricultural crop spraying, and moni-
toring, combating natural disasters, assessing the impact of natural disasters,
estimating populations, conducting atmospheric studies, and wildlife conser-
vation and management, among others.
As seen from the above discussion and Table 9.1, the closeness of the
related concepts involving drones indicates the evolving nature of this tech-
nology, and therefore the absence of a precise definition. Broadly, drones have
been referred to as any type of vehicle, including aircraft, characterized by
the absence of an onboard pilot and either autonomous or piloted from the
ground.19 It is important to note that many military forces do not prefer
the term “drone”, instead preferring the use of terms such as UAV (e.g., in
the United States and Australia) and RPA (e.g., in Europe and Australia).20
However, the popular usage of the term drones now refers to any unmanned
aircraft that is flown by an operator on the ground or is capable of fully
autonomous flight with no direct human intervention.21
Overall, whereas drones present important strategic implications to
governments and militaries worldwide, they represent a fast-growing area
that is of keen interest to corporations and application developers. The
ever-expanding capabilities of drones provide corporations with more access
to users, more opportunities for customer interaction touchpoints, more
avenues for operational efficiencies, and richer sources of information, among
others. In this regard, Kumar and Ramachandran22 propose that drones
qualify as a function-oriented technology that can allow companies to develop
capabilities to gain increased accessibility to areas and situations that humans
cannot access safely. Additionally, the firm can achieve increased efficiency
262 V. Kumar and P. Kotler

and accuracy in tasks requiring precision and attention to detail, in addi-

tion to consistently obtaining positive results.23 To conclude the overview of
drones, the following vignettes present the possibilities of drones and how
companies and users are deriving value from such offerings.

Military-Oriented Technology

Drone applications are perhaps the most visible in military operations.24 In

addition to birthing this technology, the military remains the most advanced
user of this technology that hinges on significant goals and outcomes. Specifi-
cally, the ability to make offensive strikes on adversaries away from immediate
danger presents critical strategic advantages to the user. Further, the oper-
ational efficiencies provided by drone usage have not only prevented loss
of lives but also continued to aid in vital military rescue missions, thereby
significantly impacting countries’ foreign policies.25 The vitality of drones
in the military can be seen in the development of drone electronics (i.e., the
sensors).26 In this regard, world military organizations (e.g., the UK Ministry
of Defence) have also recognized the importance of civilian drone popularity
and commercial expertise in advancing drone technology that can help the
military in significantly driving drone adoption and use.27
While the validity of drones in a military setting is increasingly justi-
fied by their continued usage around the world, the critical strengths, and
weaknesses of drones from tactical and strategic perspectives warrant atten-
tion. Specifically, drones strengthen militaries from various aspects such as (a)
doing the dull, dirty, and dangerous work deemed for humans, (b) ensuring
vital presence where manned forces are not feasible, (c) are economical to
use and operate, (d) safeguarding human military personnel, (e) facilitating
limited physical presence in dangerous territories, (f ) securing more intel-
ligence to gain a good understanding of the local situation, especially in
hostile areas, (g) allowing to be used clandestinely, (h) effectively coun-
tering time-sensitive targets, and (i) augmenting military capabilities through
ongoing technological improvements (e.g., satellite capabilities, advanced
sensors, etc.).
In contrast, drones also present critical weaknesses for the military such
as (a) exposure to information and communications hacking, (b) perfor-
mance subjective to inclement weather (e.g., snow, wind, etc.), especially in
lower-end drone models, (c) lower drone speeds could increase risk expo-
sure, (d) high development costs, especially in updating with advanced drone
electronics, (e) inability to distinguish between friendly and hostile human
populations, (f ) lesser than ideal load carrying capacities, especially weaponry,
 9 Transformative Marketing Using Drones 263

(g) easy availability to adversaries, (h) challenges in securing radio frequency

spectrum, and (i) lack of clarity in proportion and suitability of manned vs.
unmanned drone operations.
In addition to combat-related functions, drones also render vital support
in non-combat military projects.28 Such projects are often in the areas of
nation-building, peacekeeping missions, infrastructure support, and sensitive
civilian-focused projects. Military organizations around the world use drones
for vital functions such as mapping, identifying geohazards, construction, and
maintenance of critical country infrastructure (e.g., highways, bridges, mili-
tary bases, etc.), assistance in civil engineering projects (e.g., dams, refineries,
energy projects, etc.).29 Further, through its research and development initia-
tives, the military often develops applications using NATs that subsequently
became available for civilian use.30 Popular historical examples include the
development of duct tape, the microwave oven, GPS, the Internet, and virtual
reality which were first created by the US military for their internal opera-
tions.31 Therefore, drones are a fast-emerging technology that continues to
power the military in war and non-war projects.

Consumer Applications

Consumer use of drones has increased due to the inclusion of exciting drone
features.32 While military drones are equipped with highly functional and
essential features that are used in strategic and tactical operations, consumer
drones focus on hobbyists expecting fun and recreation-related features. In
the United States, the Federal Aviation Administration (FAA) considers recre-
ational or hobby UAS or drones as those used for enjoyment and not for
work, business purposes, or compensation or hire. The FAA deems such
aircraft as “model aircrafts” and defines them as “an unmanned aircraft that
is (1) capable of sustained flight in the atmosphere; (2) flown within visual
line of sight of the person operating the aircraft; and (3) flown for hobby
or recreational purposes”.33 In this regard, popular consumer drone applica-
tions largely focus on recreation aspects such as photography and sporting
activities, among others.
Perhaps the biggest attraction of drones for personal use lies in the features
of photography. While using drones for commercial photography may be
classified as a business application, individuals and photography enthusiasts
increasingly use drones for taking visually stunning photographs. With high-
quality cameras and recording devices becoming a standard feature in newer
drone models, aerial photography has become a fun and creative pastime (see
Image 9.3). Further, wildlife enthusiasts also use drones to capture dramatic
264 V. Kumar and P. Kotler

images. When handled well, drone photography can be useful in educational

pastimes such as bird watching, identification of flora/fauna, and indepen-
dent scientific research explorations.34 However, experts caution how using
drones for capturing images of birds, for example, can be disruptive for the
birds when not sensitively conducted.35 This can especially be so in the case
of beginner or amateur drone photographers. Another interesting area of
aerial photography for personal use is event photography (e.g., weddings,
social gatherings, graduation parties) and social media participation (e.g.,
photos by social media influencers, high-quality images for sharing).
Drone racing is another area of personal drone use that is making rapid
progress. This sport requires the drone operator to wear a first-person view
(FPV) headset device that is connected to a camera mounted on the drone.
This allows only the racer to see the path of the drone, and the goal of the
race is to complete the set course as quickly as possible (see Image 9.4). Such
drones typically carry features such as agility to make sharp turns, lightweight,
and the ability to make acrobatic turns. This sport, which originally began in

Image 9.3 Drones used in Aerial Photography

(Source Image by Bobby Stevenson from Unsplash)
 9 Transformative Marketing Using Drones 265

Image 9.4 Drone Racing. First-person view drone racing

(Source Image by Siggy Nowak from Pixabay)

Australia in 2014, has now attracted worldwide participation and viewership

involving several professional organizations.36

Business Applications

The extent and impact of drones on business applications are expanding at

a vigorous pace. Advancements in various commercial operations are being
developed to create more value for businesses and customers.37 Research from
the Boston Consulting Group estimates that by 2050, the industrial drone
fleet in Europe and the United States will comprise more than 1 million
units and generate $50 billion per year in product and service revenues,38
and analysts at Barclays contend that the use of drones will result in cost
savings of some $100bn.39 Overall, companies are identifying opportunities
to infuse more value into their offerings with the expectation of deriving more
value from customers. The following uses provide a flavor of such business
applications using drones:
266 V. Kumar and P. Kotler

• Drones in Agriculture. Many developing countries’ economies are heavily

dependent on agricultural produce for sustenance and exports. Despite
its importance, the sector is prone to crop failure due to adverse weather
conditions, uncontrolled pests, etc. In India, the farmers are dependent on
monsoon rains for irrigation and implement age-old farming methods. The
quality and quantity of the produce are compromised despite the efforts
of the farmers. Through the integration of technological advancements in
farming practices, the sector could mitigate failure and disasters. Drone-
based agricultural practices are picking up momentum in India, with key
roles to play in precision agriculture, improvement in crop yield, and locust
control. For instance, farmers in India using drones for spraying herbi-
cides and pesticides have realized significant time and labor savings. Instead
of around three to four hours to spray over an acre, a drone can finish
the work in just 10–12 minutes. This translates to significant cost savings
incurred due to hiring farm labor.40
The use of drone technology in agriculture aids in reducing time and
increasing the efficiencies of the farmers. With infrared mapping, drones
can gather information about the health of the soil and the crop—thereby
ensuring crop health. They detect minute signs of pest attacks and provide
accurate data about the degree and range of the attack. Since agricul-
ture is prone to be impacted by extreme weather conditions, drones can
be useful in detecting upcoming weather conditions and can prepare
farmers for adversities in advance. Agri drones are sturdy, low-cost, and
require minimum maintenance. However, these drones are heavily reliant
on internet connectivity, weather-dependent, and require the right sets of
skills and knowledge to operate them.
In 2019 survey by the California Farm Bureau Federation (CFBF) found
that 56% of participating farmers were unable to hire all the employees
they needed at some point during the past five years.41 A similar situation
can be seen across the United States. For example, between 2002 and 2014,
the number of field and crop workers in America fell by 146,000, and the
wages of field and crop workers during this period increased by 12%.42
The above two facts indicate that rising wages and a decline in the number
of farm laborers have accentuated the challenges faced by the agriculture
industry.
In this regard, drones are viewed as a labor-saving technology with
many farmers actively using drones for a range of farm-related activities.43
Drones are used in farming activities such as crop estimation, yield assess-
ment, irrigation leak detection and management, pest control, seeding,
spraying of fertilizers/pesticides, crop/livestock health assessment, soil, and
 9 Transformative Marketing Using Drones 267

Image 9.5 Drones used in spraying farms

(Source Image by DJI-Agras from Pixabay)

field analysis, and so on (see Image 9.5). However, the adoption has not
been as widespread as expected due to operational challenges such as drone
safety, privacy issues, and insurance coverage.44
• Drones in Construction. Drones have been demonstrating significant value
in the construction industry, primarily with their varied applications in
construction sites. Some of their key implementations include (a) aerial
surveys of work sites, (b) progress tracking, (c) construction planning and
management (especially at the preconstruction stage), (d) quality control,
(e) work site safety, (f ) risk mitigation and management, (g) work site
security and surveillance, (h) stockpile management, (i) marketing commu-
nications of real estate, (j) equipment storage and installation, and so
on.45 Further drone advancements such as thermal sensors, GPS units,
and high-quality cameras, in addition to augmenting drones with artifi-
cial intelligence (AI) and machine learning (ML),46 are expected to make
the drone a valued capability for the construction industry (see Image 9.6).
• Drones in Transportation. Drones are expected to provide critical first-mile
and last-mile delivery solutions for companies and consumers. Companies
such as DHL, UPS, Amazon, and Google have already started devel-
oping and testing drone deliveries and are seeing impressive results. For
instance, UPS Flight Forward, a dedicated drone delivery unit, is the first
organization to be certified by the US FAA to be operated as a drone
airline.47 Further Flight Forward is working with the WakeMed hospital
system in North Carolina to transport medical samples to speed up diag-
nosis and is exploring drone delivery options for prescriptions and retail
268 V. Kumar and P. Kotler

Image 9.6 Drones used in construction

(Source Image by Shane McLendon from Unsplash)

products for CVS.48 As with other industries, the ability to capture data
efficiently is serving businesses well in terms of customer management.
Further, when coupled with real-time communications and information-
sharing capabilities, drones improve operational efficiencies and accentuate
value creation.

Disaster Response

Mass disaster events always attract widespread public interest and require
immediate attention from first responders and disaster management teams.
While the timely mobilization of rescue and relief efforts is critical, the
method of execution and operational details are vital in ensuring the success
of the mission. In this regard, the Emergency Events Database (EM-DAT)
containing global mass disasters that are compiled by The Center for Research
on the Epidemiology of Disasters (CRED) can be used to improve decision-
making for disaster preparedness.49 While mega-disasters are not a common
occurrence, it does bring to light the importance of timely and coordi-
nated recovery/rescue efforts that can potentially minimize loss of lives and
economic damages. Here, technological advancements such as drones are
proving to be highly beneficial in assisting with disaster management efforts.
 9 Transformative Marketing Using Drones 269

In the event of a major disaster, research has identified that drones can
help secure better situational information for relief workers, locate and
rescue survivors, perform inspection and analysis of critical infrastructure,
and deliver vital supplies.50 Further, drones can be used to install temporary
communications infrastructure, generate maps of affected areas, and identify
specific spots where rescue teams must prioritize efforts.51,52
Companies and relief organizations have also been actively using drones
to coordinate relief efforts and develop better drone systems that can deliver
the maximum results. This has been implemented in dealing with chemical
spills, infrastructure damages (e.g., bridges, tunnels), fighting wildfires, and
distributing relief items. For instance, in the fight to contain the COVID-
19 pandemic, US companies such as UPS Flight Forward, DroneUp, and
Workhorse Group are testing to see how drones can be used in the coron-
avirus response by speeding up testing and increasing social distancing.53,54

Drones in the Marketing 5.0 World

In the era of marketing 5.0, drones have emerged as a game changer, trans-
forming the way businesses approach their promotional strategies. These
cutting-edge aerial devices have paved the way for innovative marketing tech-
niques that were previously unimaginable. By harnessing the power of drones,
marketers can now capture data (through images and videos) and deliver
personalized messages to their target audience. The versatility of drones allows
marketers to showcase their products and services in a way that is both
visually appealing and engaging, leaving a lasting impression on consumers.

Data-Driven Marketing Using Drones

Data-driven marketing using drones involves the use of UAVs to collect

and analyze data for marketing purposes. Drones can capture various types
of data, including imagery, video, and sensor-based information, to provide
marketers with valuable insights. Some ways through which drones collect
data that can be used for marketing campaigns include (a) delivering
targeted advertisements to individuals in populated spaces (e.g., beaches,
crowded parks), (b) displaying real-time data, product demos, or interac-
tive content, engaging audiences in a dynamic and personalized way, (c)
collecting user-response information (e.g., foot traffic patterns, crowd density,
and even individual reactions to advertisements), and (d) gathering visual data
270 V. Kumar and P. Kotler

on competitors’ activities (e.g., store layouts, promotional events, product

displays).
Aerodyne, a Malaysian drone solutions company, has partnered with
Amazon Web Services (AWS) to use its DRONOS software to help drone
operators around the world.55 DRONOS is a cutting-edge platform that
provides a broad variety of drone services, allowing users to quickly manage
and analyze drone data to improve operations, increase productivity, and
conduct aerial inspections while protecting the safety of ground workers.
Aerodyne’s expertise has found a significant application in agriculture,
where it helps to address global food security issues by using precision farming
techniques using drones. The company has successfully developed solutions
such as the Agrimor platform, which is powered by DRONOS and enables
farmers and agriculture service providers to use drones for various tasks
including planting, spraying, plant analysis, and mapping. This platform has
been developed in collaboration with AWS and has resulted in a significant
increase in crop yields, with some cases reporting up to a 67% rise. Inde-
pendent farmers and large palm oil plantation corporations in Malaysia and
Indonesia have adopted the Agrimor platform, using it to quickly identify
crop issues such as under-irrigation or disease and then deploy fertilizers or
pesticides more effectively. This not only optimizes resource allocation but
also contributes to the overall food security and profitability of farmland.

Predictive Marketing Using Drones

Predictive marketing using drones involves leveraging data collected by

drones to make informed predictions about consumer behavior, market
trends, and other factors that can influence marketing strategies. This is
an exciting new frontier, offering businesses unprecedented opportunities to
reach the right audience at the right time with the right message. Drones
equipped with sensors and cameras can gather a wealth of information,
including demographics, location, behavior, and environmental data, among
others, that can be used to predict individual behaviors and interests and
suggest appropriate marketing actions.
For instance, Sustainable Skylines, an American drone aerial advertising
company, has obtained official approval from the Federal Aviation Admin-
istration (FAA) to operate in Miami Beach.56 This achievement signifies a
significant milestone as it is the first time a drone banner-towing opera-
tion has been granted FAA approval for commercial purposes in the United
States. Unlike conventional crewed aircraft, these drones have the advantage
of vertical takeoff and landing, eliminating the need for a runway or airport
 9 Transformative Marketing Using Drones 271

and reducing fuel consumption. Once in the air, the company plans to utilize
camera footage from the drones as well as third-party mobile data to eval-
uate the effectiveness of their advertising campaigns. By employing predictive
analytics, Sustainable Skylines aims to offer dynamic pricing, adjusting their
rates based on the anticipated visibility of the aerial ads. This pricing strategy
mirrors the approach taken by Facebook and Google ads, which rely on actual
data to support their pricing decisions.

Contextual Marketing Using Drones

Contextual marketing using drones involves decision-making, structuring

activities, and delivering content based on the specific context or environ-
ment of a user. In addition to several business and marketing uses, drones can
be used for coordinating emergency response and public safety messaging.
In the case of emergencies or public safety announcements, drones can
be deployed to deliver important messages to specific areas, ensuring that
relevant information reaches the right audience promptly.
For instance, Belgium-based Citymesh is revolutionizing emergency
response with its latest innovation, SENSE.57 This groundbreaking system
consists of a network of 70 Safety Drones that are strategically deployed
to support police and fire services. What sets SENSE apart is its use of
Drone-in-a-Box (DiaB) solutions, which are automated docking stations for
drones. Within just 15 minutes of an emergency call, these DiaB stations
are deployed, providing essential support to emergency centers. Not only do
they serve as hubs for drone deployment, recharging, and data transmission,
but they also house the drones when not in use. Designed specifically for
combating fires, these drones capture high-definition 4K and thermal images,
enhanced with AI technology. This valuable information greatly enhances the
speed and effectiveness of emergency interventions.
To ensure comprehensive coverage, SENSE will be deployed across all 35
emergency zones in Belgium. Each zone will have two DiaB units, resulting
in a total of 70 Safety Drones. This extensive network of drones aims to create
a drone grid that enables emergency services to respond in a more targeted
and efficient manner. Remote Operations Centres (ROCs) play a crucial role
in this system, as they are equipped with skilled pilots who are available 24/7
to conduct flights and coordinate the activities of the drones. Additionally, a
UTM platform ensures the safety of the flights and logs all activity. UTM, or
Urchin Tracking Module, is a code that generates Google Analytics data for
digital campaigns. In the context of SENSE, UTM helps track the progress
272 V. Kumar and P. Kotler

of the drones’ activities on various online platforms, further enhancing their

effectiveness.
The capabilities of the Safety Drones are truly impressive. They capture
live HD video feeds and high-resolution images, which are transmitted in
real-time to ROCs, police forces, fire brigades, and other emergency services.
This real-time information allows these entities to anticipate risks and select
the most suitable equipment for successful rescue missions. Moreover, the
remote operators of the drones can fulfill specific requests from dispatch
and local first-response teams. By focusing the drone’s cameras on specific
areas of interest, they provide valuable insights and support to on-ground
personnel. To ensure flight safety and coordination with other aircraft, the
drone operators work closely with air traffic services. This collaborative
approach guarantees the safe and efficient operation of the Safety Drones in
emergencies.

Augmented Marketing Using Drones

Augmented marketing using drones involves combining drone technology

with existing technologies and practices to enhance marketing experiences.
Additionally, the fusion of drones with related new-age technologies creates
interactive and immersive campaigns that can engage consumers in novel
ways. Drones can capture 360-degree views of products or environments
that can be used to enhance existing capabilities and functionalities by
providing additional information, features, or interactive elements. This is
particularly useful for showcasing real estate, travel destinations, or complex
products. Increasingly, drones are also used in niche work environments such
as equipment maintenance and defense purposes.
For instance, Boeing is currently assessing how routine maintenance on
its aircraft can be expedited and improved through the assistance of drones.
The company has introduced the Autonomous Aircraft Inspection (AAI)
program, which utilizes drones to aid in maintenance tasks and has presented
its potential benefits to the US Air Force.58 With the AAI program, an airman
selects the specific area of the aircraft that requires inspection, and the drone
captures photographs that are then transmitted back to the airman on the
ground. These images, obtained by Air Force-owned drones, are stored in a
cloud-based environment, and analyzed, allowing for data accessibility from
any location. This proves advantageous in the event of identifying a defect, as
technicians in different locations can collaborate and devise a plan to address
the issue.
 9 Transformative Marketing Using Drones 273

While Boeing acknowledges that the AAI program is not flawless, it

asserts that it has demonstrated greater accuracy compared to relying solely
on human operators, with an estimated precision level of approximately
78%. Additionally, the utilization of drones significantly reduces the time
required for inspections, reducing pre-flight checks from four hours to a mere
30 minutes. The company emphasizes that the technician ultimately deter-
mines which data is stored in the cloud, highlighting that the system is not
intended to entirely replace human operators. Rather, Boeing aims to enhance
the expertise of human inspectors, ensuring that they possess the necessary
knowledge when commencing a maintenance task, rather than relying on
guesswork. By implementing this system, maintenance workers are expected
to speed up getting the aircraft out of the hangar, back to the crews, and
swiftly back into operation.

Agile Marketing Using Drones

Agile marketing using drones involves applying agile methodologies to

existing firm practices that leverage drone technology. The agile approach
emphasizes adaptability, collaboration, and the ability to respond quickly
to changing circumstances. Moreover, the ability of drones to provide rapid
data and insights allows marketers to respond quickly to market changes.
Agile marketing principles support the flexibility needed to adjust strategies
in response to emerging trends or shifts in consumer behavior.
Consider Tevel, an Israeli startup, that has developed groundbreaking
robots that are specifically tailored for fruit picking (see Image 9.7). These
autonomous flying drones utilize advanced AI and computer algorithms
to harvest fruit efficiently and optimize the entire harvesting process.59
Although the idea of using drones for apple picking is not entirely new, more
and more companies are recognizing the potential benefits of agricultural
drones and exploring how automation can contribute to efficient harvesting
solutions. For instance, these agile drones can operate continuously, providing
cost-effective solutions for farmers and real-time monitoring of the orchard’s
harvesting progress. The information collected by these drones provides valu-
able insights into the unique characteristics and contents of each bin before
it is transported to the packing house. This data empowers growers to elim-
inate uncertainties related to market value, quality, and output while also
enhancing on-site efficiencies.
Farmers can benefit from the use of drones, as they provide access to a
plethora of information about the harvested fruit, such as its quantity, weight,
274 V. Kumar and P. Kotler

Image 9.7 Drones used in apple-picking

(Source Tevel technology, https://www.tevel-tech.com/)

color grading, ripeness, diameter, timestamp, geolocation, and other essen-

tial data. These drones are equipped with sensors and 3D cameras, which
enable them to accurately identify ripe fruit, measure sugar content, and
detect diseases. The drones are autonomous and have decision-making capa-
bilities, some even utilizing electrostatic charges that mimic bee movements
for pollination. Technology companies are leading the way in designing fruit-
picking drones and tree-pollinating “paddles,” to improve farm efficiency and
agility in the face of labor shortages and climate change challenges.

Current Drone Applications in Marketing

Drones are quickly assuming an important role in the marketing function
through their varied roles. They enable firms to integrate the power of scalable
computing resources with enduring, affordable sensors that can function in
most work environments.60 When paired with other technological advance-
ments such as virtual reality, AI, and ML, they also help in the creation of an
environment in which businesses can make quick, accurate decisions based
on rich information directly from the source. Since drones can substitute for
conventional fuel-powered vehicles, they not only provide valuable assistance
in transportation but also work in reducing congestion from the roads and
containing harmful emissions. As a result, drones are becoming a valuable
 9 Transformative Marketing Using Drones 275

addition to organizations in many industries that not only present value-

creating opportunities in marketing but also hold important implications for
the development of marketing strategies. This section presents five specific
application areas where drones continue to help companies in developing
marketing initiatives.

Understanding Customer Needs to Deploy Drones

Companies often look to automation to infuse operational efficiencies, estab-

lish competitive advantage, and provide exceptional service to customers.
Consumers now demand innovative and technology-enabled devices and
solutions to meet their needs. With the emergence of NATs, technology and
consumer-level data have become inseparable. Companies can now gather
rich and varied information from customer interactions that can be used to
drive more value through the exchange. In this regard, drones can capture a
wide range of information depending on the task it was designed for.
While a significant portion of drone data may be in the form of images of
geospatial information, it provides an enormous scope for companies to do
a lot more with such images. For instance, such images can be (a) processed
into a sequentially/logically organized dataset to convey a visual message, (b)
appended with other forms of data (e.g., thermal, chemical, physical, etc.)
to learn more about a specific location, (c) illustrative in informing about
the local conditions, (d) tracked over time to better understand a partic-
ular occurrence, (e) compared against similar or diverse forms of data to
reveal further insights, and (f ) easily delivered and consumed through smart-
phone apps. This vivid information can be indicative of customer needs and
expectations that companies can focus on. As a result, drone data can subse-
quently aid companies in the development and implementation of marketing
strategies.61
In consumer applications of drones, the deployment of drones is perhaps
most impactful in delivery solutions. Especially in e-commerce, delivery
options and perceived quality of delivery service are critical for consumers
to shop online.62 In a survey conducted by the European Union Aviation
Safety Agency, respondents were asked how likely they were to try out delivery
drones, assuming that drone delivery would cost about double today’s stan-
dard shipping fees and would be guaranteed within 2 hours of placing the
order. The results showed that 72% of respondents from Milan were receptive
to trying out delivery drones, followed by residents of Barcelona (68%) and
Budapest (67%). The more northern cities of Hamburg in Germany (59%)
and the Nordics’ Öresund (57%) were slightly less open to the idea.63
276 V. Kumar and P. Kotler

While consumers are more open to trying out delivery drones, they are
also expressing more frustration in any instance of bad service. Specifically, a
survey found that 84% of customers are more likely to spend more money
to shop from a brand that provides great customer service. In contrast, 51%
of consumers indicated switching to competition after 1–2 poor customer
experiences.64 The implication of such findings indicates that companies may
not get a second chance to undo the effect of bad service experience and
that they must be vigilant in all service experiences. In this current NAT
environment, this implication is very pertinent to drone delivery and its effect
on service experience.
Such survey findings are also in line with academic research that has
highlighted the importance of minimizing service experience variance in
establishing satisfaction and emotional attachment with consumers. Specif-
ically, Kumar et al.65 conceptualize that (a) the positive relationship between
service experience and satisfaction is enhanced when the perceived varia-
tion in service experience is low and (b) the positive relationship between
service experience and emotional attachment is enhanced when the perceived
variation in service experience is low. Additionally, studies have shown that
(a) technology has a global appeal and applicability concerning its rele-
vance to real-time information,66 (b) technology can render the time and
place irrelevant for delivery of products and services (e.g., e-commerce,
online banking),67 and (c) technology can strengthen branding efforts that
can result in a competitive advantage for firms.68 Therefore, understanding
customer needs vis-à-vis drone usage will enable brands to improve customer
interactions and provide superior service experiences.

Revisiting Firm Capabilities to Integrate Drones

While drones can perform a wide range of tasks, firms can realize the full
potential of drones only when the firm’s capabilities and drone potential are
aligned.69 Given that drones have just emerged into the technology space,
their utility to businesses remains to be seen. Therefore, companies investing
in drones today will only see the results in the future. The implication is
that firms must remain committed, able, and willing to reevaluate their busi-
ness models and operations to include any new technological advancement to
realize valuable gains. This is a crucial aspect of all NATs, especially drones.
This is because, drone technology has significant commercial benefits as seen
by (a) its conduciveness towards miniaturization, (b) lower costs of electronic
components, and (c) a good testing ground for integrating other NATs such
as AI, ML, and virtual reality.70 Research has identified that firms that are
 9 Transformative Marketing Using Drones 277

future-focused have been recognized as being more focused on adopting tech-

nologies that build their capabilities to manage future needs.71 Regarding
drones, firms must develop/update technological capabilities that can bring
out the best results from a drone implementation. In this regard, academic
research has studied the development of technological capabilities of drones
extensively.72
With the emergence of drone technology, the development of techno-
logical capabilities may involve firms to be (a) open to newer technologies,
changing dynamics, and business practices, (b) perceptive in managing
risks, (c) led by strong and decisive senior management, (d) agile and in
keen anticipation of market-related changes, and (e) innovative with newer
technologies.73 This involves firms having a deep understanding of their
immediate and long-term firm requirements, goals, and challenges that make
a real impact on the bottom line. Further, firms will also have to gain a clear
assessment of the implications of adopting drones. In this regard, Kumar and
Banda74 propose that a firm’s technological capabilities influence its propen-
sity to adopt drones, in addition to other factors such as the readiness of its
managers and customers, drone suitability for the business, and a regulatory
framework.

Designing Marketing Mix Strategies With Drones

Like robotics, drones operate as a function-oriented technology, offering ease

of use, value, and convenience to users in an application setting.75 Given the
newness of drone technology in business, a concerted effort at integrating
drones into marketing strategy is noticeably absent. Current drone imple-
mentations in businesses appear to be ad-hoc in nature where drones as used
in specific marketing tasks and not featured as part of a broader marketing
mix strategy. However, this is likely to change in the future with drones
demonstrating their impact on customer experience, operating costs, and
bottom lines.
The evolving customer preferences and needs become apparent in a
technology-focused environment. As customers and firms interact closely,
learning occurs continuously. Specifically, the increased access to informa-
tion about firms and offerings allows customers to evaluate the alignment of
the proposed offerings with that of their values. Likewise, customers share
their data with firms in the course of using products and services in a
NAT environment. This creates a space for firms to know and observe more
about their customers. Further, with the compiled customer data, firms can
278 V. Kumar and P. Kotler

provide customers with personalized experiences and offerings, thereby vali-

dating/updating their knowledge of the customers. In this cycle of firms and
customers constantly evaluating and informing each other, information and
knowledge are exchanged. This exchange powers the creation of value from
and to firms and customers. Additionally, over time, such an exchange allows
for the evolution and refinement of marketing strategies from firms that are
aimed at creating value for both firms and customers.
A hallmark of the NAT environment is the presence of a business
atmosphere that focuses on personalization, delivering positive experiences,
productivity enhancements, and value growth (for firms and customers). This
implies that firms direct their attention to understanding individual customer
preferences to determine marketing mix variables. Further, this calls for firms
to ascertain the various offering combinations of marketing mix variables
that deliver the expected level of personalization, which is typically delivered
through newer technologies.
With the increasing emphasis of firms on NATs such as drones to deliver
positive experiences, firms also focus on monitoring and maintaining their
devices/platforms, to increase productivity, improve efficiency, and reduce
operating costs. For instance, drones are increasingly used to survey damage
from natural disasters such as hurricanes, wildfires, and earthquakes. In such
times of loss, consumers often depend on insurance to help them rebuild their
lives. With drones being used in surveying damages, consumers can expect
faster processing of insurance claims, thereby making a meaningful differ-
ence to consumers. Another area where drones can make a positive service
experience is in delivery, as witnessed by the developments made by major
companies such as Amazon, Google, DHL, and UPS.
Similarly, in-store navigation assistance is a key area that can result in posi-
tive experiences, as seen in the case of Walmart’s proposed in-store drones for
customer assistance76 and in-store package pickup.77 Given the assistance of
drones with generating data-driven insights and delivering positive customer
experiences, firms can potentially not only change the way they communi-
cate with consumers in real time but also accurately measure the effectiveness
of their marketing efforts, thereby increasing the opportunities for firm and
customer value growth.

Driving Customer Engagement Through Drones

The topic of customer engagement has attracted significant practitioner

and academic attention.78 Practitioners worldwide continue to focus on
developing valuable offerings while engaging with customers. Some of the
 9 Transformative Marketing Using Drones 279

marketing functions in which customer engagement continues to be most

visible include marketing communications, customer co-creation, loyalty
programs, and social media marketing, among others. As with other NATs,
drone technology continues to demonstrate its utility and value in many busi-
ness settings (industrial and consumer), thereby steadily entrenching itself
as a valuable tool in firms’ customer engagement efforts. In doing so, two
key drone capabilities are emerging as well-primed for more drone-related
customer engagement efforts.
Interactivity. Drones were originally developed to perform automated tasks
that were either difficult, dangerous, or dirty for humans. This implies that
interactivity was not an intended feature of drones. While this automation
may be well-suited for many industrial situations, consumer applications
may require drones to have interactivity as a capability. This is because the
customer-focused market structure dictates that it is vital for firms to establish
a long-term value-driven relationship with their customers to enjoy continued
patronage and financial robustness. With the increasing popularity of drones
and the high number of consumer applications, interactivity is now a feature
that drone developers are focusing on. An example of drone interactivity can
be seen in the case of the Hyderabad, India-based Biryani By Kilo. The fast-
food seller specializing in biryanis decided to launch an initiative to deliver
biryanis by drone. Along with the initiative, the company paired it with a
social media campaign by engaging with social media influencers based in
Hyderabad. The initiative and the social media campaign were a success with
nearly 815 thousand views, around 85 thousand engagements, and a 44%
increase in sales after the campaign.79 This shows that drones can be made
interactive when integrated within a company’s marketing campaigns.
With advances made in speech recognition technologies, it is possible to
equip drones with audio response capabilities (e.g., such as Alexa) that can
interact with consumers in an exchange setting.80 Such a feature will be most
useful in situations like customer deliveries, in-store assistance, and naviga-
tion, customer assistance in public attractions (e.g., malls, museums, and
amusement parks), and event management venues (e.g., queue management),
among others. These applications are likely to enhance customer engagement
as the drones will have the ability to instantly respond to customer queries.
Delivery. Drones are poised well to disrupt the delivery business, especially
in fulfilling orders in highly populated areas. Many companies across coun-
tries have initiated delivery programs using drones. Some of the prominent
ones include DoorDash launching a drone pilot program in the South-
east Queensland region in Australia, Walmart partnering with four drone
delivery companies to establish drone delivery hubs in seven US states, Tesco
280 V. Kumar and P. Kotler

launching its drone delivery service in Galway, Ireland, and Chinese food
delivery platform, Meituan, starting drone delivery operations in 2021.81
Consider Amazon, for instance. Most products sold by Amazon weigh five
pounds or less.82 Many drones are equipped to handle this weight. There-
fore, this is an area that online retailers are looking at with great interest and
one that can enhance customer engagement in a significant way.
However, given the limited air space, it is likely that firms will face chal-
lenges in drone delivery, with several instances of collision and property
damage. Here, a traffic management system (TMS would help firms and users
to have efficient usage of air space and serve as a way to enhance customer
engagement. For instance, NASA is working on creating a platform known
as the UAS Traffic Management (UTM) to create a system that can integrate
drones safely and efficiently into air traffic that is already flying in low-altitude
airspace.83 Such a system is expected to monitor and regulate package delivery
and hobby drones from intruding into the air space of regular air transport
(e.g., airplanes, helicopters) and first responder drones.

Designing Digital Strategies With Drones

In the fast-evolving NAT environment, media and consumers are increasingly

going digital. For marketers, this change presents important implications in
two key areas—solutions-focused offerings and changing user demographics.
Solutions-focused offerings refer to those types of offerings that directly
relate to customer requirements by leading them to the solution they seek
rather than going through a long search process. When faced with choices,
consumers typically look for more information to help them make decisions.
While new information (e.g., competing offerings, alternative solutions)
may be acquired through traditional and/or digital means, it also assists
in avoiding decision regret,84 and thereby helps consumers feel confident
about their choices. Further, when consumers face a non-routine (or less
frequent) decision, they would likely seek more information to assuage their
concerns. Seeking and processing large amounts of information may lead
to “information fatigue” and potentially an unsatisfactory decision-making
process. In this regard, digital strategies can facilitate faster decision-making
by shortening customers’ purchase journeys and making them more efficient
and convenient. When companies use drones in their marketing programs,
the level and depth of information that is communicated is very rich and
informative to the viewers. For instance, using drone footage/images in
commercials provides dramatic aerial views that convey much more than
traditional ground-based footage/images. Often captivating, drone images
 9 Transformative Marketing Using Drones 281

Table 9.2 Changing nature of user demographics in the United States

User age group Percentage of adults who
Own a Use social media Own a tablet
smartphone in… in… computer in…
2012 2018 2021 2012 2018 2021 2012 2018 2021
18–29 66 94 96 81 88 84 20 63 61
30–49 59 89 95 64 78 81 12 56 53
50–64 34 73 83 39 64 73 10 50 46
65 and above 13 46 61 16 37 45 6 38 44
Source Faverio, M. (2022), “Share of those 65 and older who are tech
users has grown in the past decade,” Pew Research Center, January 13,
accessed from https://www.pewresearch.org/short-reads/2022/01/13/share-of-those-65-
and-older-who-are-tech-users-has-grown-in-the-past-decade/

add dimension and movement to the marketing content, thereby nudging

them towards a decision.
The changing nature of user demographics has moved towards digital
avenues. While younger users are known to be early adopters of technology
compared to older users, the rate of adoption of newer technologies by the
oldest age group has increased significantly in recent years. Particularly, a
recent survey has found the gap between the oldest and youngest adults has
narrowed. The results of the survey are presented in Table 9.2.
As shown in Table 9.2, among Americans 65 and older between 2012
and 2021, there was a nearly five-fold increase in the ownership of smart-
phones, a three-fold increase in the usage of social media, and a seven-fold
increase in the ownership of a tablet computer. While other age groups also
showed increases, it was not as significant as the 65 and older group.85 The
implication of such generational shifts is, that firms that can take advan-
tage of ongoing developments in drone capabilities, drone electronics, and
sensors; creatively use drone data and insights; plan drone deployment in a
precise manner; and implement digital strategies that involve drones in the
right measure can reap impressive rewards while delivering the most value to
consumers.

Future of Drones in Marketing

With the rapid progress made in technological innovations, the future
looks loaded with gadgets, algorithms, and platforms. As with all NATs,
drones too will become a regular feature in our daily lives. As we move
towards a data-rich and innovation-focused environment, the presence and
282 V. Kumar and P. Kotler

usage of consumer data by firms, the quality of insights generated, and

the way technology is used to implement solutions based on the insights
will inform the usefulness and relevance of marketing strategies.86 While
a technology-intensive future is inevitable, firms must adopt a customer-
focused approach while designing marketing strategies that create value for
firms and consumers. Drones will undoubtedly continue to impact marketing
strategies and marketing practices. In doing so, the lessons learned from drone
implementations and the marketplace changes will continue to drive future
drone implementations. While we can expect progress in drone capabilities
in many organizational areas, three areas that stand out are discussed here.

The “Good,” “Bad,” and “Ugly” of Drones

It is apparent that personalization has increased tremendously, and data is

being generated in more ways than one can expect. While there have been
a few concerns over the role of these technologies, drones require specific
attention. Here, three perspectives about drones are presented—the “good”
(why we must embrace drone use), the “bad” (that which must be worked
on), and the “ugly” (that which must be re-evaluated) to facilitate decision-
making for customers and organizations.
The “Good.” As discussed earlier, drones have many uses that benefit
society such as for inspection in law enforcement, construction, and safety
and disaster management, among others. Drones are also being used in
ecosystem management for identifying poaching or illegal deforestation—
they were used in Kenya in fighting poachers. Drone photography and
videography also have a transformative effect on humans. In business
contexts, drones are used by firms to offer better customer experiences. In
2016, Domino’s Pizza flew the peri-peri chicken, chicken, and cranberry
pizzas to a couple in Whangaparaoa, New Zealand—the first people in the
world to get pizzas delivered by drones.87 Around the same time, Amazon
delivered their goods using drones, following the Amazon Prime Air business
model.
The “Bad.” It is to nobody’s surprise that drones have infiltrated our daily
lives with ease, but the long-term consequences of this action are relatively
underexplored. Drones are a safety threat. When operated by inexperienced
fliers, when poorly made, or when flying in unfavorable conditions—they
may fall out of the sky unexpectedly (susceptible to engine malfunctions).
Additionally, there are rising concerns over drones’ invasion of privacy. The
idea of a drone flying above people’s homes and capturing images to store as
 9 Transformative Marketing Using Drones 283

data is very unsettling to many. These are being mitigated by drone manufac-
turers and developers—they are developing new technologies; cameras that
automatically blur or pixelate faces. Customers are using privacy screens to
block the view of their homes, some apps detect drone presence around set
premises.
The “Ugly.” Flying drones over crowds is becoming common nowadays—
this is a serious hazard as drones could collide with other people or objects
in the crowd. They are also very noisy, contributing significantly to noise
pollution. Drones are being equipped with weapons and are being used to
carry out other criminal offenses. Drones flying in restricted airspaces are
also picking pace—in 2014, a helicopter-style drone nearly collided with an
Airbus 320 taking off from Heathrow Airport in London. Such acts pose a
serious threat to humanity, only regulations and awareness can reduce the
possibilities.

Enhanced Customer Experience

Drones are continuing to prove their worth in improving customer expe-

rience. As evidenced by the above discussion, while drone technology is a
game changer in improving customer experience in end-user-focused interac-
tions, drones also work just as effectively “behind the scenes” in delivering a
superlative experience. In the future, this ability of drones is only expected to
increase as more firms see value in such implementations. A few such drone
implementations are discussed here.
Consider the insurance industry. This industry was one of the first to
begin using drones for claims inspections. Companies such as Allstate, Trav-
elers, USAA, and Liberty Mutual are using drones for damage inspection
and processing claims, with more companies planning to adopt drones.88
Whereas claims inspection is but one function for insurers, drone deployment
is being evaluated or used in many more functions. Specifically, drones are
being considered for assessing the loss before and after a negative event occurs.
Regarding the determination of loss before a negative event occurs, drone
data and inputs are used in calculating premiums, including risk mitigation
clauses in the insured property, and collecting information relating to poten-
tial threats from natural disasters. Once a loss-creating event has occurred,
drones can be considered for assisting in several tasks such as inspecting
damages to property and lives, assessing risks to avoid future losses, processing
claims, and validating damages to prevent insurance fraud, among others.
While all these actions may not occur in direct interaction with customers,
284 V. Kumar and P. Kotler

their involvement in the background ultimately impacts how insurers manage

customer expectations and provide superior experience.
Consider the public utilities industry. Drones serve a vital use in assisting
with aerial surveys for maintenance purposes. For instance, critical infras-
tructure such as power lines, communications towers, roads, rivers, bridges,
etc., needs routine maintenance and monitoring, to avoid any service failures.
While trucks, helicopters, and boats are typically used for such maintenance
purposes, it is often expensive and could place members of the maintenance
team in hazardous conditions. Here are three examples of drone usage by
public utility companies.

• An early user of drones, Dominion Energy in Virginia has been using

drones for routine power line inspections since 2014.89 Recently, the
company also won approval from the FAA for expanded beyond visual line
of sight (BVLOS) drone flights. The company expects such advancements
in drone usage to serve its customers better by providing a superior service
experience.
• In 2017, the New York Power Authority (NYPA) tested the use of drones to
inspect the Niagara ice boom for any damages and preventive maintenance.
While it can cost $3,500 for a helicopter or $3,300 to send a crew of four
for a full-day inspection by boat, a drone could cost only $300 per trip,
thereby leading to valuable cost savings.90
• In 2017, Oklahoma Gas and Electric (OG&E) recently deployed inspec-
tion drones to speed up storm assessment and restoration times during
winter storm Jupiter. By continuing the use of drones to undertake advance
inspections of power lines, wind farm turbines, and plat equipment, the
company estimates the outage duration to have been reduced by 50%.91

Essentially, by reducing the number of breakdowns and/or providing

more accurate information on service restoration, such implementations are
expected to ultimately provide a better customer experience for users of public
utility companies.

Customer Contact Solutions

Drones have the potential to demonstrate improvements in product devel-

opment and enhancement, process optimization, and derive deeper insights
for decision-making when well-integrated into marketing strategies. Further,
they can help firms master the knowledge of consumer preferences, and
deliver personalized products, pricing, and advertising content through
 9 Transformative Marketing Using Drones 285

relevant channels. Several companies continue to use drones for display

advertising that can be eye-catching while being economical. For instance,
Moscow-based Wokker Noodles used drones to carry small promotional fliers
past the windows of Moscow office buildings, informing the lunch specials
just as people were getting ready for lunch. The success of this innovative
campaign was immediately observed with lunch deliveries in the campaign
areas increasing by 40%.92 Other major brands such as Red Bull, Coca-Cola,
GE, and Intel have used drones for advertising and promotional marketing
campaigns.93 Such initiatives have significantly helped the brands stay closer
to their consumers.
Another area where drones can serve as effective customer contact vehi-
cles is event marketing. Visitors to an event serve as a committed audience to
which firms can pitch their offerings. Given that the attention of the audi-
ence is at a high level, an innovative way of communicating the marketing
message will likely have a high impact. For instance, when events are covered
via a live stream using drones, in addition to the regular mode of coverage,
consumers get an immersive experience of the event. Examples of such expe-
riences include recreational adventure sports (e.g., hang gliding, paragliding,
parasailing, etc.), indoor sporting events (e.g., drone cameras for capturing
close-ups and replays), drone racing, behind-the-scene footage of live events,
and so on. When brands make their presence felt during such events,
consumers may associate those brands with positive experiences thereby
boosting the brand image and recall. The Intel Drone Show at the Pepsi Super
Bowl LIII Halftime Show is an example of how brands can elevate the memo-
rability of an event while making its presence felt .94 Further, the company
has performed more than 600 light shows in over 20 countries, signifying
the value of drones as a prized, innovative event management tool that can
benefit brands and consumers.
Drones can also make a significant positive impact on customer satisfac-
tion by enhancing the quality of customer interactions during a purchase
event. Drone delivery is a good example of this. With many companies like
Amazon, Google, DHL, Flirtey, and UPS rapidly increasing the technolog-
ical capabilities of drones, regulatory bodies are now beginning to facilitate
and simplify the regulatory policies governing the use of drones in business.95
Such actions are further expected to lower the barriers to entry for other drone
adopters, drone developers, and drone service providers, thereby creating a
vibrant drone ecosystem.
286 V. Kumar and P. Kotler

Key Terms and Related Conceptualizations

Drone An unmanned aircraft that can fly

autonomously
Drone racing A sport that requires the drone
operator to wear a first-person view
(FPV) headset device that is
connected to a camera mounted on
the drone
Fixed-wing systems Fixed, static wings in a drone that can
aid with forward airspeed to
generate lift
Hybrid systems Drones that possess characteristics of
fixed-wing systems and multirotor
drones
Multirotor drones Drones that are equipped with
multiple small rotors, at least four,
to allow them to hover in the air, be
noiseless, and be lightweight
Payload The weight a drone can carry
Remotely piloted aircraft (RPA) A sub-category of an unmanned
aircraft where the flying pilot is not
on board the aircraft
Remotely piloted aircraft systems (RPAS) A set of configurable elements
consisting of an RPA, its associated
remote pilot station(s), the required
command and control links, and any
other system elements as may be
required, at any point during flight
operation
Remotely piloted vehicle (RPV) Class of UAVs designed to have some
degree of interaction with a human
controller via a data link but may
possess autonomous flight control
capability
Unmanned aerial vehicle (UAV) Aerial vehicles that provide wireless
connectivity by transmitting data
remotely, and typically without an
onboard pilot
Unmanned aircraft system (UAS) An aerial system is made up of many
sub-systems that include the aircraft,
its payloads, and the control
station(s). Essentially, it’s an aircraft
with its crew removed and replaced
by a computer system and a radio
link
 9 Transformative Marketing Using Drones 287

Notes and References

1. The global drone services market has expanded significantly and is
expected to grow from USD 4.4 billion in 2018 to USD 63.6 billion
by 2025 (Markets Insider (2019), “Global Drone Service Market
Report 2019: Market is Expected to Grow from USD 4.4 Billion in
2018 to USD 63.6 Billion by 2025, at a CAGR of 55.9%,” Markets
Insider, April 29, [accessed from https://markets.businessinsider.com/
news/stocks/global-drone-service-market-report-2019-market-is-exp
ected-to-grow-from-usd-4-4-billion-in-2018-to-usd-63-6-billion-by-
2025-at-a-cagr-of-55-9-1028147695]).
2. Research by Verizon has found that more than 90% of surveyed
businesses reported increased efficiencies, time-saving, and better
information capture as a result of drone adoption with nearly
50% reporting potential losses in the bottom line if they had not
adopted drones (Skyward (2018), “State of Drones in Big Business,”
Skyward , [accessed from http://go.skyward.io/rs/902-SIU-382/images/
2018%20State%20of%20Drones.pdf]).
3. Smith, A., & M. Anderson (2017), “Automation in everyday life”
Pew Research Center, October 4, [accessed from https://www.pewres
earch.org/internet/2017/10/04/americans-attitudes-toward-a-future-
in-which-robots-and-computers-can-do-many-human-jobs/].
4. Cohn, P., A. Green, M. Langstaff, and M. Roller (2017), “Commercial
drones are here: The future of unmanned aerial systems,” McKinsey &
Company, December, [accessed from https://www.mckinsey.com/ind
ustries/capital-projects-and-infrastructure/our-insights/commercial-
drones-are-here-the-future-of-unmanned-aerial-systems].
5. Keane, J. F., & S. S. Carr (2013), “A brief history of early
unmanned aircraft,” Johns Hopkins APL Technical Digest, 32(3), 558–
571; O’Donnell, S. (2019), “A Short History of Unmanned Aerial
Vehicles,” Consortiq, June 16, [accessed from https://consortiq.com/
media-centre/blog/short-history-unmanned-aerial-vehicles-uavs].
6. Dekoulis, G. (2018), Drones: Applications, (Ed.) IntechOpen Limited.
7. Zeng, Y., R. Zhang, & T. J. Lim (2016), “Wireless communications
with unmanned aerial vehicles: Opportunities and challenges,” IEEE
Communications Magazine, 54(5), 36–42.
8. Austin, R. (2011), Unmanned aircraft systems: UAVS design, develop-
ment and deployment (Vol. 54), John Wiley & Sons.
288 V. Kumar and P. Kotler

9. Watts, A. C., V. G. Ambrosia, & E. A. Hinkley (2012), “Unmanned

aircraft systems in remote sensing and scientific research: Classification
and considerations of use,” Remote Sensing, 4(6), 1671–1692.
10. Larm, D. (1996), Expendable remotely piloted vehicles for strategic
offensive airpower roles, Air University Press, AL., USA.
11. ICAO (2011), “Unmanned Aircraft Systems (UAS) Circular,” Inter-
national Civil Aviation Organization (ICAO), CIR 328, AN/190,
Montreal, Quebec, CA.
12. ICAO (2011), “Unmanned Aircraft Systems (UAS) Circular,” Inter-
national Civil Aviation Organization (ICAO), CIR 328, AN/190,
Montreal, Quebec, CA.
13. Villasenor, J. (2012), “What is a drone, anyway?” Scientific American,
April 12, [accessed from https://blogs.scientificamerican.com/guest-
blog/what-is-a-drone-anyway/].
14. AUVSI (2019), “Global trends of unmanned aerial systems,” Asso-
ciation for Unmanned Vehicle Systems International , [accessed from
https://02f09e7.netsolhost.com/AUVSIDocs/Global%20Trends%
20for%20UAS.pdf].
15. AUVSI reports the top six common applications for drones as imaging
(86%), followed by reconnaissance, surveillance, and intelligence
(69%), patrol and security (69%), disaster response (66%), survey/
mapping (64%), and environmental monitoring (64%) (AUVSI
2019).
16. Vergouw, B., H. Nagel, G. Bondt, & B. Custers (2016), “Drone tech-
nology: Types, payloads, applications, frequency spectrum issues and
future developments,” in The future of drone use: Opportunities and
threats from ethical and legal perspectives, B. Custers (Ed.), Springer.
17. US DoD (2011), “Unmanned Systems Integrated Roadmap FY2011-
2036,” US Department of Defense, October, [accessed from http://info.
publicintelligence.net/DoD-UAS-2011-2036.pdf].
18. Clarke, R. (2014), “Understanding the drone epidemic,” Computer
Law & Security Review, 30(3), 230–246.
19. Gregory, D. (2011), “From a view to a kill: Drones and late modern
war,” Theory, culture & society, 28(7–8), 188–215; Klauser, F., &
S. Pedrozo (2015), “Power and space in the drone age: A litera-
ture review and politico-geographical research agenda,” Geographica
Helvetica, 70(4), 285.
20. Clarke, R. (2014), “Understanding the drone epidemic,” Computer
Law & Security Review, 30(3), 230–246.
 9 Transformative Marketing Using Drones 289

21. Goldberg, D., M. Corcoran, & R. G. Picard (2013), “Remotely

piloted aircraft systems and journalism: Opportunities and chal-
lenges of drones in news gathering,” Reuters Institute for the Study of
Journalism, June, [accessed from https://ora.ox.ac.uk/objects/uuid:a86
8f952-814d-4bf3-8cfa-9d58da904ee3]; Floreano, D., & R. J. Wood
(2015), “Science, technology and the future of small autonomous
drones,” Nature, 521(7553), 460–466.
22. Kumar, V., and D. Ramachandran (2020), “Developing a firm’s growth
approaches in a new-age technology environment to enhance stake-
holder wellbeing,” working paper, Indian School of Business, India.
23. Huang, M. H., & R. T. Rust (2018), “Artificial intelligence in service,”
Journal of Service Research, 21(2), 155–172.
24. Boucher, P. (2015), “Domesticating the drone: the demilitarisation of
unmanned aircraft for civil markets,” Science and Engineering Ethics,
21(6), 1393–1412.
25. Sparrow, R. (2009), “Predators or plowshares? Arms control of robotic
weapons,” IEEE Technology and Society Magazine, 28(1), 25–29.
26. Clouet, L. M. (2012), “Drones as future air power assets: The dawn of
aviation 2.0?” In Power in the 21st Century, pp. 177–192.
27. Ministry of Defence (2017), “Joint Concept Note 1/17: future force
concept,” UK Ministry of Defence, September 7, [accessed from https://
www.gov.uk/government/publications/future-force-concept-jcn-117].
28. Apgar, M., & J. M. Keane (2004), “New business with the new
military,” Harvard Business Review, 82(9), 45–56.
29. The U.S. Army Corps of Engineers is constantly involved in nation-
building efforts, responding to natural disasters, and setting up
large-scale civilian infrastructure that typically involves the use of
current technological advancements (Gilsinan, K. (2020), “The race
to build new hospitals,” The Atlantic, April 18, [accessed from https://
www.theatlantic.com/politics/archive/2020/04/army-corp-engineers-
hospitals-coronavirus/610195/]; Kramnik, I. (2020), “To sequestrate,
or not to sequestrate: The impact of Covid-19 on military budgets,”
Modern Diplomacy, April 12, [accessed from https://moderndiplom
acy.eu/2020/04/12/to-sequestrate-or-not-to-sequestrate-the-impact-
of-covid-19-on-military-budgets/]).
30. Matthews, K. (2020), “Military robotics market shows strength for
new applications,” Robotics Business Review, January 31, [accessed
from https://www.roboticsbusinessreview.com/news/military-robotics-
market-shows-strength-new-applications/].
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31. Frolich, T., E. Comen, & G. Suneson (2019), “15 commercial prod-
ucts invented by the military include GPS, duct tape and Silly Putty,”
USA Today, May 16, [accessed from https://www.usatoday.com/story/
money/2019/05/16/15-commercial-products-invented-by-the-mil
itary/39465501/].
32. The global consumer drone market size was expected to grow
from USD 4.85 billion in 2022 to USD 8.74 billion by
2027 (Statista, & BRC. (January 15, 2023). Consumer drone
market size worldwide in selected years from 2020 to 2027 (in
billion U.S. dollars) [Graph]. In Statista. Retrieved October 08,
2023, from https://www.statista.com/statistics/1234655/worldwide-
consumer-drone-market-size/). Also, the consumer drone market was
the first to develop outside the military (Goldman Sachs (2016),
“Drones: Reporting for Work,” Goldman Sachs, October 24, [accessed
from https://www.goldmansachs.com/insights/technology-driving-inn
ovation/drones/index.html]).
33. FAA (2012), “FAA modernization and reform Act of 2012,” Pub. L.
No. 112-95, [accessed from https://www.congress.gov/112/plaws/pub
l95/PLAW-112publ95.pdf].
34. Mayntz, M. (2019), “The impact of drones on birds,” The Spruce,
June 9, [accessed from https://www.thespruce.com/birds-and-drones-
3571688].
35. Verhagen, J. (2019), “Drones and bird photography: Why it’s just
not worth it,” National Audubon Society, October 1, [accessed from
https://www.audubon.org/news/drones-and-bird-photography-why-
its-just-not-worth-it].
36. Organizations such as Fédération Aéronautique Internationale (FAI),
Canadian Federation for Drone Racing, and Drone Racing Chile serve
as governing bodies of such sporting events. Racing leagues such as
MultiGP, Drone Racing League, RotorMatch League, and X Class
Drone Racing host and coordinate drone racing events regularly.
37. In 2020, 5.1 million units of drones were sold globally garnering USD
2.9 billion in revenue. The revenue is estimated to increase to USD 4.3
billion (in 8.2 million units sold) by 2024, and USD 4.7 billion (in
9.3 million units sold) by 2028. The top five geographic markets for
drones are China, the United States, France, Germany, and the United
Kingdom (Statista (2023). Drones - Worldwide. (n.d.). In Statista.
Retrieved October 08, 2023, from https://www.statista.com/outlook/
cmo/consumer-electronics/drones/worldwide*).
 9 Transformative Marketing Using Drones 291

38. Amoukteh, A., J. Janda, & J. Vincent (2017), “Drones go to work,”

Boston Consulting Group, April 10, [accessed from https://www.bcg.
com/en-us/publications/2017/engineered-products-infrastructure-mac
hinery-components-drones-go-work.aspx].
39. McGee, P. (2019), “How the commercial drone market became big
business,” Financial Times, November 26, [accessed from https://www.
ft.com/content/cbd0d81a-0d40-11ea-bb52-34c8d9dc6d84].
40. Biswas, P. (2023), “Maharashtra’s agri-entrepreneurs take to the skies:
How drone are being used tackle farm labour shortage,” The Indian
Express, September 3, accessed from https://indianexpress.com/art
icle/cities/pune/drones-the-new-tool-for-farmers-in-maharashtra-892
1730/.
41. CFBF (2019), “Still searching for solutions: Adapting to farm
worker scarcity survey 2019,” California Farm Bureau Federation,
April 30, [accessed from https://www.cfbf.com/news/survey-california-
farms-face-continuing-employee-shortages/].
42. New American Economy (2020), “Agriculture,” New American
Economy, [accessed from https://www.newamericaneconomy.org/iss
ues/agriculture/].
43. The 2019, CFBF survey found that 74% of the respondents adopted
technology because of rising workforce costs, and 56% said because of
a labor shortage (CFBF 2019).
44. Mazur, M. (2016), “Six ways drones are revolutionizing agriculture,”
July 20, MIT Technology Review, [accessed from https://www.techno
logyreview.com/2016/07/20/158748/six-ways-drones-are-revolutioniz
ing-agriculture/].
45. Burger, R. (2019), “6 Ways drones are affecting the construction
industry,” The Balance, August 15, [accessed from https://www.the
balancesmb.com/drones-affecting-construction-industry-845293];
Goodman, J. (2020), “Tech 101: Construction drones,” Construction
Dive, January 8, [accessed from https://www.constructiondive.com/
news/tech-101-construction-drones/569796/].
46. Winick, E. (2018), “AI and drones are being used to control
construction projects,” MIT Technology Review, March 15, [accessed
from https://www.technologyreview.com/2018/03/15/144645/ai-and-
drones-are-being-used-to-control-construction-projects/].*
47. UPS (2019a), “UPS flight forward attains FAA’s first full approval for
drone airline,” UPS, October 1, [accessed from https://pressroom.ups.
com/pressroom/ContentDetailsViewer.page?ConceptType=PressRele
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48. UPS (2019b), “UPS flight forward, CVS pharmacy to develop drone
delivery applications,” UPS, October 21, [accessed from https://pressr
oom.ups.com/pressroom/ContentDetailsViewer.page?ConceptType=
PressReleases&id=1571676331520-698].
49. CRED reports that in the decade of 2008–2017, an annual average
of 348 global disaster events occurred that resulted in an annual
average of 67,572 deaths, affected an annual average of 198.8 million
people and caused economic losses of an annual average of USD 166.7
billion. In comparison, 2018 saw 315 global natural disaster events
that resulted in 11,804 deaths, affected over 68 million people, and
caused economic losses of around USD 131.7 billion (CRED 2018).
The reason for the higher annual averages for the decade of 2008–2017
could be attributed to the occurrence of mega-disasters such as the
2010 Haiti earthquake, the 2011 Japan earthquake and tsunami, and
the 2015–16 drought in India that claimed several thousands of lives,
affected millions of people, and created several billions in economic
losses.
50. Measure-Red Cross (2015), “Drones for disaster response and relief
operations,” Measure and American Red Cross, April, [accessed from
http://www.issuelab.org/resources/21683/21683.pdf].
51. Al-Tahir, R., M. Arthur, & D. Davis (2011), “Low cost aerial mapping
alternatives for natural disasters in the Caribbean,” International Feder-
ation of Surveyors, May, [accessed from https://www.fig.net/resources/
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rthur_et_al_5153.pdf].
52. Research has investigated the use of drones in logistics operations
(Gupta, L., R. Jain, & G. Vaszkun (2015), “Survey of important issues
in UAV communication networks,” IEEE Communications Surveys &
Tutorials, 18(2), 1123–1152; Erdelj, M., & E. Natalizio (2016),
“UAV-assisted disaster management: Applications and open issues,” In
2016 international conference on computing, networking and communi-
cations (ICNC), IEEE, February, pp. 1–5), to deliver supplies (Hayat,
S., E. Yanmaz, & R. Muzaffar (2016), “Survey on unmanned aerial
vehicle networks for civil applications: A communications viewpoint,”
IEEE Communications Surveys & Tutorials, 18(4), 2624–2661), and
to recover hazardous materials (Pauner, C., I. Kamara, & J. Viguri
(2015)., “Drones. Current challenges and standardisation solutions in
the field of privacy and data protection,” In 2015 ITU Kaleidoscope:
Trust in the Information Society (K-2015), IEEE, December, pp. 1–
7), among others, and developed frameworks to economically deploy
 9 Transformative Marketing Using Drones 293

drones to serve a disaster-affected region (Chowdhury, S., A. Emelogu,

M. Marufuzzaman, S. G. Nurre, & L. Bian (2017), “Drones for
disaster response and relief operations: A continuous approximation
model,” International Journal of Production Economics, 188, 167–184).
53. Fisher, J. (2020), “UPS and workhorse test drones to help COVID-19
response,” FleetOwner, April 21, [accessed from https://www.fleeto
wner.com/covid-19-coverage/article/21129382/ups-and-workhorse-
test-drones-to-help-covid19-response].
54. Zipline assisted the Ghanaian government in containing the spread
of the coronavirus by delivering test samples in rural areas to medical
laboratories in two major cities in long-distance drones (Muller, J.
(2020), “A coronavirus first: Zipline drones deliver test samples in
Africa,” Axios, April 20, [accessed from https://www.axios.com/cor
onavirus-zipline-drone-delivery-africa-1d4d2680-ce4f-4efe-b3b4-b91
714c4a254.html]). Similarly, India deployed drones for surveillance
purposes in the fight against COVID-19 to track large gatherings,
minimize physical contact, monitor narrow lanes that cannot be
easily accessed by police vehicles, and spray disinfectants (Srivastava,
A. (2020), “Coronavirus lockdown: Drones deployed for surveillance
across Bihar,” India Today, April 20, [accessed from https://www.indiat
oday.in/coronavirus-outbreak/story/coronavirus-lockdown-drones-dep
loyed-for-surveillance-across-bihar-1669110-2020-04-20]; Shekhar,
G. C. (2020), “Chennai’s drone army joins city’s fight against coro-
navirus; plays crucial role in red zones,” Outlook, April 22, [accessed
from https://www.outlookindia.com/website/story/india-news-che
nnais-drone-army-joins-citys-fight-against-coronavirus-plays-crucial-
role-in-red-zones/351249]).
55. Economic Times (2023), “Aerodyne teams up With AWS to solve
complex industrial issues with drone data,” Economic Times—CIO
Southeast Asia, December 4, accessed from https://ciosea.economict
imes.indiatimes.com/news/corporate/aerodyne-teams-up-with-aws-to-
solve-complex-industrial-issues-with-drone-data/105712904.
56. Sheena, J. (2023), “Drone aerial advertising startup gets green light
from aviation authorities,” Marketing Brew, August 29, accessed
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ial-advertising-startup-gets-green-light-from-aviation-authorities.
57. Ghosh, B. (2023), “World’s first: Citymesh to deploy 70 drone-in-a-
box systems across Belgium for emergency response,” flytbase, March
16, accessed from https://www.flytbase.com/blog/citymesh-to-deploy-
70-drone-in-a-box-systems-across-belgium-for-emergency-response.
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58. Gill, J. (2023), “Boeing sees 5G, drone inspectors and augmented
reality training key to future aircraft maintenance,” Breaking Defense,
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sees-5g-drone-inspectors-and-augmented-reality-training-key-to-fut
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59. Jackson, A. (2023), “Agribots: The possible future development of
food harvesting,” Food Digital , July 17, accessed from https://fooddi
gital.com/articles/agribots-the-possible-future-development-of-food-
harvesting.
60. Kumar, V. (2021). Intelligent Marketing: Employing New Age Technolo-
gies. Sage Publications.
61. Companies are considering delivery through drones to improve their
last-mile connectivity performance. Between 2021 and 2022, trends
indicate that the number of packages delivered by drone increased
by more than 80%, reaching almost 875,000 deliveries worldwide.
Further, by 2023, commercial drone deliveries are projected to exceed
1 million (Cornell et al. 2023).
62. By 2025, it is likely that same-day and instant delivery will reach a
combined share of 20 to 25% of the market, thereby highlighting
the importance of drones in fulfilling last-mile delivery needs; and
that 60% of consumers are in favor of, or at least indifferent to,
drone delivery (Joerss, M., F. Neuhaus, & J. Schröder (2016),
“How customer demands are reshaping last-mile delivery,” McKinsey,
October, [accessed from https://www.mckinsey.com/industries/travel-
transport-and-logistics/our-insights/how-customer-demands-are-res
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63. Fleck, A. (2023). European city dwellers would try delivery drones. In
Statista. January 13, Retrieved October 08, 2023, from https://www.
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nes/.
64. Islam, Z. (2020), “Great service drives revenue in Gladly’s 2020
customer expectations report,” Gladly, [accessed from https://www.gla
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65. Kumar, V., B. Rajan, S. Gupta, & I. D. Pozza (2019), “Customer
engagement in service,” Journal of the Academy of Marketing Science,
47(1), 138–160.
66. McLaughlin, C. P., and J. A. Fitzsimmons (1996), “Strategies for
globalizing service operations,” International Journal of Service Industry
Management, 7(4), 43–57.
 9 Transformative Marketing Using Drones 295

67. Jayawardhena, C., and P. Foley (2000), “Changes in the banking

sector–the case of Internet banking in the UK,” Internet Research,
10(1), 19–31.
68. Wright, A. (2002), “Technology as an enabler of the global branding
of retail financial services,” Journal of International Marketing, 10(2),
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69. Kumar, V. (2021). Intelligent marketing: Employing new age technologies.
Sage Publications.
70. Gupta, S., Leszkiewicz, A., Kumar, V., Bijmolt, T., & Potapov, D.
(2020). Digital analytics: Modeling for insights and new methods.
Journal of Interactive Marketing, 51(1), 26–43.
71. Srinivasan, R., G. L. Lilien, & A. Rangaswamy (2002), “Technological
opportunism and radical technology adoption: An application to e-
business,” Journal of Marketing, 66(3), 47–60.
72. Technological capabilities have been identified as those abilities that
competitively distinguish the firm and allow it to create a sustained
competitive advantage based on the technology in a changing context
(Leonard-Barton, D. (1992), “Core capabilities and core rigidities: A
paradox in managing new product development,” Strategic Manage-
ment Journal , 13(S1), 111–125; Prahalad, C. K., & G. Hamel (1990),
“The Core Competence of the Corporation,” Harvard Business Review,
68(3), 79–91). This becomes even more relevant in the NAT envi-
ronment where firms have to contend with emerging technologies,
competitive pressures, and evolving regulatory policy environment.
Lall (Lall, S. (1992), “Technological capabilities and industrialization,”
World Development, 20(2), 165–186) refers to the development of a
firm’s technological capabilities as the outcome of investments under-
taken by the firm in response to external and internal stimuli, and
interaction with other economic agents, both private and public, local,
and foreign. The implication is that several micro-level and macro-level
factors jointly determine the level of technological capabilities of firms.
73. Kumar, V., and D. Ramachandran (2020), “Developing a firm’s growth
approaches in a new-age technology environment to enhance stake-
holder wellbeing,” working paper, Indian School of Business, India.
74. Kumar, V., & S. Banda (2020), “CX in a drone world,” working paper,
Indian School of Business, India.
75. Kumar, V., and D. Ramachandran (2020), “Developing a firm’s growth
approaches in a new-age technology environment to enhance stake-
holder wellbeing,” working paper, Indian School of Business, India.
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76. Martin, C. (2018), “Walmart Files Patent For Drone Customer Service
In Stores,” MediaPost, March 26, [accessed from https://www.mediap
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customer-service-in.html].
77. Leonard, M. (2019), “Patent pending: Walmart plans for drone
delivery, others tackle faster picking and the end of lost inventory,”
Supply Chain Dive, October 4, [accessed from https://www.supplycha
indive.com/news/patent-pending-walmarts-plans-for-drone-delivery/
564359/].
78. Academic research has covered several engagement concepts such
as customer engagement (Kumar, V., L. Aksoy, B. Donkers, R.
Venkatesan, T. Wiesel, & S. Tillmanns (2010), “Undervalued or
overvalued customers: Capturing total customer engagement value,”
Journal of Service Research, 13(3), 297–310; Pansari, A., and V.
Kumar (2017), “Customer engagement: The construct, antecedents,
and consequences,” Journal of the Academy of Marketing Science, 1–
18; Verhoef, P. C., W. J. Reinartz, & M. Krafft (2010), “Customer
engagement as a new perspective in customer management,” Journal
of Service Research, 13 (3), 247–252), customer engagement behav-
iors (Van Doorn, J., K. N. Lemon, V. Mittal, S. Nass, D. Pick, P.
Pirner, & P. C. Verhoef (2010), “Customer engagement behavior:
Theoretical foundations and research directions,” Journal of Service
Research, 13(3), 253–266), consumer brand engagement (Hollebeek,
L. D., M. S. Glynn, & R. J. Brodie (2014), “Consumer brand
engagement in social media: Conceptualization, scale development and
validation,” Journal of Interactive Marketing, 28(2), 149–165), and
customer engagement marketing (Harmeling, C. M., J. W. Moffett,
M. J. Arnold, & B. D. Carlson (2017), “Toward a theory of customer
engagement marketing,” Journal of the Academy of Marketing Science,
45(3), 312–335), among others. Kumar et al. (2019) investigate
customer engagement in a service setting wherein, service experience
is defined as “…the overall customer experience that is borne out of
all forms of customer interactions, communications, and transactions
regarding the service offerings, over time” (p. 139).
79. Social Samosa (2022), “Case study: How biryani by kilo created
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80. Fuhrman, T., D. Schneider, F. Altenberg, T. Nguyen, S. Blasen, S.

Constantin, & A. Waibel (2019), “An interactive indoor drone assis-
tant,” arXiv preprint, arXiv:1912.04235; Padhy, R. P., S. Verma, S.
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for autonomous UAV navigation in indoor corridor environments,”
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82. Guglielmo, C. (2013), “Turns out Amazon, touting drone delivery,
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87. Reid, D. (2016), “Domino’s delivers world’s first ever pizza by drone,”
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to small UAV coalition,” Unmanned Aerial , August 1, [accessed
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90. NYPA (2017), “First ever drone inspection of Niagara Ice Boom,” NY
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storm recovery,” Oklahoma Gas and Electric, March 15, [accessed
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92. Feloni, R., & A. Taube (2014), “These drone-based advertisements
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ising-2014-9].
93. Walgrove, A. (2016), “How 3 major brands are using drone marketing
to reach new heights,” Sprinklr, June 2, [accessed from https://blog.
sprinklr.com/brands-using-drones-marketing/]; Agrawal, A. J. (2017),
“5 Ways marketers can take advantage of drone technology,” Forbes,
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95. Nearly 88% of respondents cited a change in the regulatory envi-
ronment as a key growth driver for the subsequent use of drones
(Comptia (2019), “The drone market: Insights from customers and
providers,” Comptia, June, [accessed from https://www.comptia.org/
content/research/drone-industry-trends-analysis]).
 10
Transformative Marketing Using Blockchain

Overview
In the NAT environment, blockchain technology is rapidly gaining atten-
tion among firms and users. Blockchain operates on a peer-to-peer (P2P)
network and is characterized as a distributed ledger technology wherein data
can be stored on servers anywhere in the world. Such a system allows for the
creation of a permanent record of actions while providing the participants
of the system the ability to verify each action ever performed. Essentially,
this technology works based on creating a distributed consensus in the digital
online world, thereby firmly establishing trust in actions even when operating
in the online world.
The promise of this technology can be seen in its global growth. According
to the IDC, the market for blockchain solutions is expected to reach $6.6
billion by 2024, growing at a five-year compound annual growth rate
(CAGR) of 48% between 2019 and 2024.1 Additionally, the IDC study
makes 3 bold predictions for the future of blockchain into the year 2028.
First, the market for crypto loans will grow to $5 trillion by 2026 as more
people use them as a standard platform for both lenders and borrowers.
Second, as a technology channel for private and public stocks, debt, and
derivatives, by 2027, 50% of new securities issued globally will be NFTs (or
Blockchain-based tokens). Finally, assuming trade ecosystems become inter-
operable, standardized, technology-neutral, and widely available to clients by
2028, digital trade finance transactions will account for 30% of all trade
finance transactions. Key factors like cybersecurity and risk, digital business,
economic instability, ecosystem-based innovation, embracing the metaverse,

© The Author(s), under exclusive license to Springer Nature 299

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_10
300 V. Kumar and P. Kotler

global supply shock, and storms of disruption are what are driving these
forecasts.
Bolstered by several salient features such as economic considerations, being
Internet-savvy, and enhanced privacy settings, this technology is gaining
acceptance and usage in various commercial and industrial settings. For
instance, a global Deloitte survey found that in the next 24 months, digital
assets will be “very/somewhat important” to their respective businesses,
according to roughly 80% of all respondents.2
This chapter is organized as follows. First, a brief history of the origin
of blockchain is presented, followed by a definition of blockchain (from
a marketing standpoint). Then, a discussion on the various classifications
of blockchain is presented spanning individual to commercial uses such as
security applications, interfacing technology between other NATs, and end-
user applications. Next, some marketing applications of blockchain focusing
on understanding customer needs, revisiting firm capabilities to integrate
blockchain, designing blockchain-focused marketing mix strategies, driving
CE through blockchain, and designing digital strategies with blockchain are
discussed. Finally, the future of blockchain for the marketing industry is envi-
sioned through specific business- and customer-facing tasks such as the role
of blockchain in shaping data and transaction security, ensuring advertising
transparency, and powering online marketing campaigns.

Origin, Definition, and Classification

of Blockchain
Origin

The development of blockchain technology is the most recent among the

NATs considered in this book. Its origins can be traced back to 2008
when Satoshi Nakamoto first proposed the introduction of the first cryp-
tocurrency—Bitcoin, a blockchain-based digital currency application.3 The
Bitcoin application is based on cryptographic proof instead of the tradi-
tional third-party mediation for two willing parties to execute an online
transaction over the Internet.4 For instance, when two parties (say A and
B) want to transact over the Internet using blockchain, the general opera-
tional procedure of the transaction would be as follows. When A wishes to
send money to B, a “block” denoting the transaction is created online. Then,
the network participants are notified of the transaction’s intent and initia-
tion. The network participants then approve the transaction as legitimate.
 10 Transformative Marketing Using Blockchain 301

The block can then be appended to the chain indicating its authenticity and
permanence in history. Following this, the money gets transferred to B. The
two critical aspects that are verified before recording any transaction are (a)
A maintains and owns the cryptocurrency that they would like to send and
(b) A holds enough cryptocurrency balance in their account for the proposed
transaction, after checking their transaction details with other members in the
network. The entire transaction is protected with the presence of public keys
and private keys (see Image 10.1). Studies such as Crosby et al.,5 de Kruijff
and Weigand,6 Lin and Liao,7 Zheng et al.,8 and Zı̄le and Strazdiņa9 offer a
detailed exposition of the working details and structure of blockchain.
As the origins of blockchain started with Bitcoin, the two have been
mistaken for each other, with many instances of interchangeable usage.10
Whereas Bitcoin is the first successful cryptocurrency created to address
the need for a secure online digital currency, prior attempts at creating a
cryptocurrency faced several challenges. These attempts include the creation

Image 10.1 Bitcoin. Bitcoins are used widely as a reliable means of digital currency
(Source Photo by David Shares on Unsplash)
302 V. Kumar and P. Kotler

of ecash, HashCash, Digicash, and e-gold, among others.11 After Bitcoin’s

success, several cryptocurrencies have been developed such as Ethereum,
Ripple, Litecoin, Cardano, and Solana to name a few. While Bitcoin ushered
in a new way of transacting online safely and securely, the underlying
blockchain technology has found subsequent uses in several real-world appli-
cations such as distribution, finance, healthcare, and supply chain, among
others.

Definition

Blockchain refers to a distributed ledger and immutable database for securely

transferring data. The name is a combination of two words—the “ block”
that contains batched transactions and a “chain” that represents cryptograph-
ically linked blocks.12,13,14 It is important to note that there is no consensus
on a globally accepted definition of blockchain, and there are several concep-
tualizations of blockchain.15 Table 10.1 provides a flavor of the various
conceptualizations of blockchain.
Blockchain technology is better understood by considering the underlying
elements driving it. A brief discussion of the main elements is provided here.
Decentralized . Traditional online transaction systems require the involve-
ment of a central agency (such as a central bank) that is trusted with
monitoring and regulating the smooth functioning of the system. Such a
setup invariably adds procedures and protocols to the operational aspects of
the transactions thereby imposing monetary and non-monetary costs on the
transacting parties. In a blockchain network, no centralized authority moni-
tors, oversees, or approves the transactions. Instead, many validating network
participants (known as nodes) confirm the transactions’ authenticity. In this
regard, Nakamoto16 offers the proof-of-work consensus as an approach that

Table 10.1 Select conceptualizations of Blockchain

Study Conceptualization of blockchain
Hileman and “…type of distributed ledger that is composed of a chain of
Rauchs130 cryptographically linked ‘blocks’ containing batched transactions;
generally, broadcasts all data to all participants in the network.”
Tama et al.131 “…a part of the implementation layer of a distributed software
system.”
Zheng “…is distributed and can avoid the single point of failure
et al.132 situation.”
Yli-Huumo “…to create a decentralized environment where no third party is
et al.133 in control of the transactions and data.”
 10 Transformative Marketing Using Blockchain 303

can replace the central agency, while providing incentives that would keep the
network participants honest.
Secure and Immutable. Blockchain is a replicated ledger format where
records may not be altered or removed. Such a setup creates a unique record
of the transaction history that is immutable unless most of the nodes decide
to do so. This feature establishes trust in the system and creates confidence
among users.
Instantaneous. Given that blockchains do not involve intermediaries, are
final, and are irreversible, the speed at which transactions can materialize is
enormous. Additionally, the instantaneous nature of transactions makes the
exchange cheaper as no intervening procedures or oversight are necessary.
Transparent . Each node in a blockchain has access to all the data, and all
records can be reviewed and checked publicly. This feature of the blockchain
makes it secure and trustworthy to use. Additionally, blockchain allows the
creation of third-party applications, as permitted by its open-source archi-
tecture. This provides several value offerings to users and creates numerous
commercial opportunities for developers.
Hash Functions. A mathematical process known as a cryptographic hash
function accepts an input (or “message”) and outputs a fixed-length string,
which is often a series of digits and letters. The result, also known as the
hash value or digest, should be distinct for each input or at the very least
exceedingly unlikely to be duplicated. This implies that even the slightest
alteration in the input will result in a significantly altered hash.17
Tokens and Tokenization. On many blockchains, especially those that
support smart contracts, tokens act as a representation of resources or utility.
They can serve as a mechanism of commerce inside the blockchain ecosystem
or reflect ownership or value supported by an asset. Tokens have the fungi-
bility property, which can categorize them as either fungible or non-fungible.
In contrast to traditional currencies, which are interchangeable and of equal
value, non-fungible tokens are valued independently and are frequently
used to represent digital assets like artwork or collectibles. Utility Tokens
give users access to platform services or features. Security tokens represent
ownership and are linked to physical assets, much like stock shares in a
firm. Asset-backed Tokens are tied to tangible or intangible assets, such as
gold. Governance tokens allow token holders to vote on decisions regarding
their host blockchain. Tokens are essentially flexible tools in the blockchain,
enabling everything from straightforward transactions to intricate platform
interactions.18
Autonomous. Blockchain ensures that parties around the world can conduct
activities online automatically without the need for any human intervention.
304 V. Kumar and P. Kotler

Using private/public key algorithms, ensuring trust, verifying transactions or

reconciliation efforts can be performed automatically through the software.
Essentially, the software ensures that conflicting or double records cannot
be permanently written in the ledger. In this regard, algorithms can self-
execute, self-enforce, self-verify, and self-constrain the performance of the
transactions.19

Classification of Blockchain

Research has identified that blockchains can be classified based on the level
of access and openness into public, private, and hybrid (see Table 10.2).
As mentioned earlier, while blockchain was developed primarily to develop
a secure way of transaction online, later applications of blockchain have iden-
tified process economies for firms by expediting and securing the processes
and data records underlying interactions and transactions.20 Such applica-
tions of blockchains can be seen in a wide range of industries worldwide.
Commercial applications of blockchain usage include data management (e.g.,
managing contracts, planning network infrastructure, and organizational
data management), data authentication (e.g., document verification, quality
inspection, and notary services), financial services (e.g., online payments,
insurance services and currency exchange), and business processes (e.g.,
supply chain management, content management services, and media manage-
ment).
To improve operations, promote transparency, and provide new services,
many businesses across numerous industries have implemented blockchain
technology. Here are a few noteworthy instances:

• BMW: Traces and verifies the provenance of the minerals used in the
construction of their cars using blockchain to ensure ethical sourcing.21
• JPMorgan Chase: Launched the “JPM Coin,” a digital token used to
instantly settle transactions between institutional accounts.22
• MediLedger: Blockchain technology is being used by a group of pharma-
ceutical businesses to track and validate prescription drugs. Its members
include the major U.S. wholesalers and top manufacturers including
Genentech, Pfizer, Bayer, Gilead, and Amgen.23
• Microsoft: Offers blockchain as a service (BaaS) via its Azure cloud
computing platform.
• Propy: A global real estate marketplace that uses blockchain to record
property deeds and conduct international transactions.24
 10 Transformative Marketing Using Blockchain 305

Table 10.2 Classification of Blockchain

Type of Select
blockchain Meaning Key features/benefits examples
Public • Also known as • Secured by the Bitcoin,
blockchain permissionless combination of Ethereum
blockchain, all economic incentives
participants in the and cryptographic
network have access verification using
to all the ledgers mechanisms such as
• No central agency/ proof of work or
body manages the proof of stake
network, including • Adhere to a general
approving or banning principle that the
transactions degree to which
someone can
influence the
consensus process is
proportional to the
number of economic
resources that they
can bring in134
Private • Also known as • In some cases, readers Hyperledger,
blockchain permission and writers could be Ripple
blockchain, authority part of blockchains
regarding read and that exist
write operations in contemporaneously
the blockchain is and are
reserved for limited interconnecteds135
members • Allows firms to adopt
• An invitation-only distributed ledger
network governed by technology without
a central authority making data public
that decides the level
and extent of read/
write access
participants get in
the operations of the
blockchain
(continued)
306 V. Kumar and P. Kotler

Table 10.2 (continued)

Type of Select
blockchain Meaning Key features/benefits examples
Hybrid • Also known as • Here, a group of 10 XinFin,
blockchain consortium legal service firms (for Kadena
blockchain, the instance) may run a
determination of blockchain, with at
what blocks get least seven members
added to the chain signing off every
and what the current block for the block to
state is, is controlled be valid
by a select group of • The rights to read
participants136 (i.e., public vs.
• Constitutes a hybrid restricted) the data
between the public may be decided by
blockchains and the the group and could
single highly trusted also vary by each
authority model (i.e., participant
private blockchains)

• Spotify: To aid in tracking credit and royalty payments, Spotify purchased

blockchain firm Mediachain.25
• Starbucks: Focuses on fair trade principles while using blockchain to track
the path of its coffee beans from farmers to shops.26
• Walmart: To secure the safety of its food supply, it uses blockchain to track
the origin of agricultural items.27

These are but a few instances of blockchain implementations. Businesses

are quickly adopting blockchain as they become aware of its potential advan-
tages, which range from efficiency and cost savings to transparency and
security.28 To conclude the overview of blockchain, the following three
vignettes present the possibilities of blockchain and how companies and users
are deriving value from such offerings.

Security-Oriented Technology

As with many NATs, blockchain is a practitioner-driven technology. While

proponents of blockchain consider it to be one of the best ways to secure
transactions, it is not without concern. Academic research has identified
concerns in the privacy and security settings of blockchain, and scripting
language design, among others.29
Recent academic research efforts have codified security features and
attributes of blockchain that can be used to assess, (re)design, and improve
 10 Transformative Marketing Using Blockchain 307

newly developed solutions. Specifically, the following six security concepts

have been proposed that have gained wide consensus.30

• Accountability. Also referred to as non-repudiation, this concept states that

undeniable proof will exist to verify the truthfulness of any claim of a
participant. In the non-profit industry, this could mean tracking the move-
ment of donations (in the form of cryptocurrency) from wallet to wallet,
thereby making auditing and accounting easier for the firm.
• Authenticity. This concept refers to the identification or verification of the
source of origin of data in the network. In the media industry, this could
mean using blockchains to verify the source of a news item and tracking
the circulation of fake news.
• Availability. This concept ensures that network services are available and
will survive possible attacks or failures that could occur. This also includes
protection against any incident that threatens the network’s availability. In
an online transaction system, this could mean ensuring the payment system
can always serve transaction requests as created by authorized users and
complete the requests when the service is active.
• Confidentiality. This concept refers to the assurance that data will be
disclosed only to authorized individuals or systems. In the case of smart
homes fitted with metering devices for measuring utility consumption,
this could mean that no entity (other than the customer and the utility
company) will have access to the appliance(s) and their usage patterns.
Such levels of confidentiality would also include customer preferences
regarding how much detail the utility can have access to and what details
cannot be accessed.
• Fairness. Whereas the concept of fairness can be best understood only in
the usage context since the application of fairness could vary accordingly,
a general understanding of this concept relates to a protocol that does not
discriminate against the honest and correctly participating members. Addi-
tionally, transparency could also be related to this concept—one that talks
about fair and just usage practices in the network. In the food industry,
this could mean companies using blockchains to allow consumers to get
detailed information about the origin of ingredients, food preparation,
food inspection reports, food recalls, and so on.
• Integrity. This concept refers to the assurance that the accuracy of the
information is always maintained. This involves not allowing tampering
(i.e., changed, modified, or altered) of information by participants not
authorized to do so. Additionally, this also involves the detection of unau-
thorized modifications and the prompt notification of such occurrences
308 V. Kumar and P. Kotler

to the network participants. In the manufacturing industry, blockchain

integrity could mean verifying 3D printers to deliver finished parts that
are in adherence to industry standards and practices. Thus, for integrity
purposes, maintaining the consistency, accuracy, and trustworthiness of
data over its entire lifecycle becomes crucial.

From the practitioner world, the security aspects of blockchain continue

to receive attention. For instance, governance agencies such as ISACA,
non-profit organizations such as Open Web Application Security Project
(OWASP), and technical associations such as the Institute of Electrical and
Electronics Engineers (IEEE) closely monitor and advance the ideal security
protocol for blockchains. These organizations regularly develop security stan-
dards, conduct ongoing industry discussions, and monitor security risk areas
that could impact commercial enterprises.

Link to AI and ML

As mentioned earlier in this book, AI and ML offer significant benefits to the

implementing firms and the end users, thereby delivering value to firms and
customers. While these two NATs’ usefulness has been adequately demon-
strated, they are not without concerns or challenges. Specifically, AI operates
in the field of automation and continuous learning, acting as the intelli-
gence that drives data-focused analytics and decision-making.31 ML, on the
contrary, deals with the process of training machines to learn over time with
the key outcome being predictions about key variables of interest wherein,
the quality of learning is dependent on the volume and quality of data.
To perform at the peak potential, both AI and ML rely on key conditions.
Specifically, while AI relies on data or information to learn, infer, and make
final decisions, ML performs better when data is reliable, secure, trusted, and
credible.32
The challenge for firms arises when the reliance on the above-mentioned
key conditions of the two NATs is not ensured. Separately, blockchain focuses
on storing data with high integrity and resiliency and cannot be tampered
with. Put simply, the key conditions for AI and ML to perform well happen
to be one of blockchain’s defining characteristics. Such a situation natu-
rally gives rise to complementarities that can well serve both AI/ML and
blockchain (for example, the supply chain industry uses blockchain to verify
food origins and AI to analyze crop patterns, growing cycles, and price
fluctuations). As a result, the consolidation of AI/ML and blockchain can
 10 Transformative Marketing Using Blockchain 309

create secure, tamper-free, decentralized systems conducive to high-quality

inference, decision-making, and learning. In this regard, both AI/ML and
blockchain can improve each technology’s efficiency and effectiveness.

AI/ML Improving Blockchain’s Effectiveness

Ensuring decentralization, autonomy, immediacy, security, and transparency

in a blockchain transaction involves various levels of parameter considerations
and nuanced coding, not to mention decision steps resulting in adjustments.
AI can ease the decision steps and automate and optimize blockchain for
higher performance and better governance.33
A key area where AI/ML can make a difference in blockchain effective-
ness is security. While blockchains per se are highly secure, the applications
developed on top of the blockchain platform are not always so. This makes
the platform and all the users vulnerable to hacking.34 In this regard, AI/
ML algorithms can help in detecting attacks on a blockchain and initiating
appropriate recourse options. Further, it is possible for AI/ML algorithms
to detect and potentially isolate the hacked component so that the rest of
the blockchain remains safe. Other areas where AI/ML continues to make
a difference in blockchain’s effectiveness include predictive analytics, smart
contracts, and privacy controls, among others.
Another crucial area where blockchain can aid AI/ML’s effectiveness is
knowledge management. From a firm standpoint, knowledge has been identi-
fied as an asset of the company to be managed,35 and a key issue of knowledge
management is observed to be the organization, distribution, and refinement
of knowledge.36 Additionally, knowledge management has been positively
linked to organizational learning,37 adaptive organizations,38 and competitive
advantage,39 among other strategic firm outcomes. Given the high level of
importance accorded to knowledge, the successful management of knowledge
depends on how knowledge is organized and managed. Research has identi-
fied the ability, the motivation, and the opportunity to act on the knowledge
as important elements in this regard.40
Further, establishing the boundary conditions under which knowledge can
be utilized is essential. For instance, the presence of an interdisciplinary team
that reflects a broad continuum of knowledge levels, the closeness of ties
between actors using the knowledge, and the newness of tasks in which the
knowledge is being used can help leverage the power of knowledge.41 Addi-
tionally, research has distinguished between information and knowledge and
the process of transferring information versus the transfer of knowledge.42
Here, carefully selecting, interpreting, and integrating knowledge is known
310 V. Kumar and P. Kotler

to add value to organizations over a mere addition of newer technology

tools. In this regard, blockchain can provide a safe and reliable environment
wherein firms can use blockchain capabilities to collect, compartmentalize,
and provide access to data and information gathered that can subsequently be
used in developing AI/ML solutions. In addition, blockchain can encourage
data sharing because it provides transparency and accountability regarding
which users’ data is accessed, when, and by whom.43 Other areas where
blockchain can improve the effectiveness of AI/ML include personalization
efforts, data security, data provenance and integrity, collective decision-
making, model transparency and traceability, enhanced security, monetiza-
tion and micropayments, management of hardware networks, crowdsourced
model training, ensuring ethical standards, automation and transparency
with smart contracts, and decentralized operations leading to firm efficiency,
among others.

Blockchain in the Marketing 5.0 World

Blockchain is displaying a lot of potential in revolutionizing marketing by
building trust and transparency, enhancing customer engagement, protecting
intellectual property, streamlining data management, and enabling new forms
of marketing. Additionally, blockchain is also indicating potential applica-
tions relating to combating fraud and counterfeiting by creating a tamper-
proof record of all transactions, improving supply chain efficiency by creating
a single, shared source of truth for supply chain data, and enabling new
forms of payment such as cryptocurrency, among others. Expanding on the
Marketing 5.0 concept discussed in Chapter 2, this section presents how
robotics and intelligent automation operate in the Marketing 5.0 world.
Particularly, this section discusses five examples of where robotic applica-
tions are applied through the lens of Marketing 5.0 and establishes how such
actions can also bode well for humanity.

Data-Driven Marketing Using Blockchain

The combination of data-driven marketing and blockchain technology has

opened new possibilities for businesses to enhance their marketing strate-
gies. With blockchain, marketers can track and verify every step of the
customer journey, from the initial interaction to the final purchase. This
level of transparency not only builds trust with customers but also allows
 10 Transformative Marketing Using Blockchain 311

marketers to optimize their operations by identifying the most effective

channels, messages, and offers.
Consider the case of ride-sharing apps. Despite their popularity, the
business model of ride-sharing companies faces serious challenges such as
labor regulations (e.g., wage levels, classification of drivers, etc.), competi-
tive threats (e.g., self-driving vehicles, increase in food delivery services, etc.),
pricing structure (e.g., surge pricing, free promotional rides, etc.), and regu-
latory compliance (e.g., federal lawsuits, city ordinances, etc.), among others.
A distinguishing feature of the current ride-sharing services business model is
the centralization of demand and supply of rides. This implies that a request
for a ride is not always satisfied immediately, and drivers often lack a steady
line of rides. The ideal scenario, however, should be different. Specifically, the
need for a ride for a rider must be met immediately with little to no wait time
and the supply of drivers must be consistent so that they have a steady stream
of rides with little to no downtime. This is where blockchain can make a
difference.
Blockchain-based apps such as Drife and Arcade City are changing the way
ridesharing is done by focusing on decentralizing operations.44 For instance,
Drife uses blockchain to offer non-commission rides and incentivize services;
instead, they charge drivers an annual fee for access to the app. Similarly,
Arcade City enables riders and drivers to connect directly with each other;
wherein, drivers determine their charges, and work hours and establish their
base of repeat customers. Another ride-sharing service, TADA, operating
in South Korea aims to bring riders, drivers, and car parts manufacturers
into one ecosystem. Apart from being a zero-commission service and insti-
tuting a rewards system for drivers, this blockchain service records the entire
vehicle history such as maintenance, repairs, previous rides, and rating of the
driver to improve services to customers.45 Therefore, blockchain can provide
significant benefits to users by way of changing the way ride-sharing works.

Predictive Marketing Using Blockchain

The incorporation of blockchain technology in predictive marketing has

presented businesses with fresh opportunities to acquire valuable knowl-
edge about their intended customer base. With blockchain, marketers can
access a vast network of data that is securely stored and verified by multiple
participants. This eliminates the need for intermediaries and ensures the
authenticity and integrity of the data. By analyzing this data, businesses can
identify patterns, trends, and correlations that can help them make informed
decisions about their marketing campaigns.
312 V. Kumar and P. Kotler

Consider the case of Volvo. The automobile company has implemented

an innovative approach to enhance its supply chain network by harnessing
real-time data and creating a digital twin. This enables the company to effec-
tively calculate and analyze the CO2 emissions associated with its supply
chain operations.46 By closely examining the sourcing procedures for nickel,
a crucial component in batteries, Volvo discovered a significant disparity in
prices depending on the location and extraction methods. It became evident
that the CO2 impact of one ton of nickel can vary considerably based on its
source.
To address this issue, Volvo has turned to blockchain technology to trace
the materials used in batteries, including nickel, cobalt, and lithium. In a
strategic move, Volvo Cars made an undisclosed investment in Circulor,
a blockchain technology provider, in 2020. This partnership has allowed
Volvo to gain transparency into its battery supply chain, utilizing Circulor’s
blockchain application throughout the process. Furthermore, Volvo has
extended the use of blockchain technology to monitor the CO2 impact of
these minerals, encompassing both mining and processing stages, as well
as their transportation to the battery cell production site. By implementing
these measures, Volvo can precisely track the shipment of parts and materials,
thereby comprehending the environmental footprint of the transportation
process.

Contextual Marketing Using Blockchain

The integration of blockchain into contextual marketing has brought signif-

icant advancements in how brands connect with their target audience. With
blockchain, marketers can now track and verify the authenticity of user data,
ensuring that the information used for targeting is reliable and up to date.
This not only enhances the effectiveness of contextual marketing but also
fosters trust between brands and consumers, as users have more control over
their transactions and can trust their engagement with brands.
Consider the act of counterfeiting. While brands cannot easily prevent
counterfeiters from creating versions of the original products, they can intro-
duce processes that evaluate the authenticity of the products. In 2021, to
tackle the problem of counterfeiting, major global luxury brands joined
together in investing in blockchain and associated technologies, which led to
the creation of the Aura Blockchain Consortium. It was founded by LVMH,
Prada Group, and Cartier (part of Richemont). Mercedes-Benz joined as a
founding member in 2022, and the group together aims to develop applica-
tions of blockchain technology and raise the standards of luxury. Accordingly,
 10 Transformative Marketing Using Blockchain 313

the products of the Aura Blockchain Consortium’s members are fitted with a
QR code as they leave the warehouse and to the store. Along with the QR
Code, any type of authentication technology (like an NFC chip) could be
used. When customers buy the product, they can scan the QR code on the
item, claim ownership, and certify its authenticity with access to the product
information. This generates a certificate of authenticity which will be made
available digitally. As the brand becomes known for authenticating its prod-
ucts on the blockchain, people will get familiar with using QR Codes, NFC,
and other AI solutions—thus creating demand in primary and secondary
markets for genuine luxury products.47
In addition to authenticating luxury goods, Blockchain also opens new
channels of engagement, builds customer loyalty, and creates the means to
build brand-centric communities. For instance, consider the Italian clothing
retailer—Diesel. The brand is exploring the possibilities of using NFTs
through its D:verse platform, which offers wearables alongside a limited-
edition physical collection. D:verse community also offers exclusive bene-
fits (invitations to real-world fashion shows, pre-sales access, etc.) to its
customers. Thus, Diesel can identify loyal customers who value being a part
of the online community and engage with such customers in innovative
ways.48
In another implementation of blockchain, establishing provenance, in
wines, for example, remained a big challenge to the industry players until
the use of blockchain. Crurated, a member- and blockchain-based member-
ship wine community, is leveraging the blockchain and NFTs with every
bottle of wine that enters their warehouse. Moreover, the company allows its
members to participate in the bidding for fractional barrel offerings wherein
members can bid for the liters that they want of the wine from the finest
wine producers.49 Additionally, members can also pick the size of the bottles
they would like and personalize the labeling. By using blockchain technology,
Crurated has not only addressed the problem of wine origin but also made
the process more democratic. In this regard, the company has been able to
attract a younger audience due to the accessible nature of blockchain. Since
the platform’s debut in 2021, 70 percent of members are younger than 45
years old, and 35 percent are under 35 years old.50 For a product that has
been largely consumed by people over 60 years, this opens a new market
segment for the company to cater to.
314 V. Kumar and P. Kotler

Augmented Marketing Using Blockchain

Augmented marketing using blockchain aims to enhance marketing expe-

riences, increase transparency, and improve user engagement. Instances of
how these manifests include tokenizing content using blockchain that allows
content creators to be rewarded with tokens when users interact with or view
their content, integrating gaming into marketing campaigns for a superla-
tive marketing experience, allowing users to unlock special experiences or
discounts as part of the loyalty programs; and validating the effectiveness of
advertising efforts, among others.
While the applications of blockchain in augmenting marketing activ-
ities are being actively documented, its use in non-business applications
is also being increasingly identified. Consider the case of voter manage-
ment. Regardless of the geographic location, voter turnout receives significant
media and research attention, given its long-lasting implications on gover-
nance and policymaking.51 Additionally, a blockchain-based system has been
identified as helpful in combating voter fraud.52 Further, start-ups such as
Voatz, Follow My Vote, and BitCongress have created secure voting systems
that aim to create secure voting options. Such voting systems ensure that
a vote is recorded only one time to a candidate of the voter’s choice that
cannot be changed. Further, such applications have additional features such
as sharing opinions on civic and citizen issues, thereby increasing the useful-
ness of such applications.53 In 2020, the state of West Virginia in the
United States discontinued its usage of the Voatz platform indefinitely, citing
industry experts’ security worries.54 Although these pilots are still in the early
stages and have difficulties, they demonstrate how blockchain technology can
completely change how we think about and trust digital voting systems.

Agile Marketing Using Blockchain

Agile marketing is a marketing approach that emphasizes flexibility, iteration,

and rapid response to change. It focuses on short sprints, continuous feed-
back, and adaptation to changing requirements. Such usage of blockchain
allows companies to deliver value to end users.
Consider the use of blockchain in food safety systems. The salmon
industry in Norway is currently encountering difficulties in implementing
effective tracking methods for its salmon. A recent study conducted in 2019
examined the supply chains and sourcing practices of various salmon prod-
ucts sold in European supermarkets such as Sainsbury’s, Aldi, and Tesco. The
study revealed that many of these products, despite having environmental
 10 Transformative Marketing Using Blockchain 315

certifications like Responsible Supply, were likely produced using fishmeal

and fish oil obtained through highly unsustainable fishing practices in coun-
tries like India, Vietnam, and the Gambia.55 In response to this issue, Atea,
a Norwegian technology firm, has partnered with IBM’s blockchain-based
platform Food Trust and the Norwegian Seafood Association to establish the
Norwegian Seafood Trust. This network, built on blockchain technology,
collaborates with major fish farming companies worldwide. By gathering
extensive data on fish welfare, water quality, genetics, feed, processing, and
distribution, the industry is experiencing unprecedented levels of trans-
parency and accessibility to valuable information.56
Moreover, by allowing firms to be transparent about tracking the food
origins, blockchain in food safety systems can benefit in a variety of ways
such as (a) improving sustainability by reducing waste, (b) lowering costs by
eliminating food system efficiencies, (c) tracking foodborne outbreaks, (d)
counterfeit foods, (e) enhanced food data resulting in efficient food flows,
among others.57 Essentially, if the entire production and supply chain system
is logged onto the blockchain, consumers can easily trace their food from
its origin to their plates (see Image 10.2). This makes it easy for regulators
to identify and control the source of any food-based illnesses. Companies
such as Alibaba, Carrefour, Greenfence, and Walmart are using blockchain
to bring efficiency to food chains such that users can be aware of the food
journey from farm to table.58

Image 10.2 Tracking food origin using blockchain. Nestlé allows users to trace the
coffee origins of their Zoégas coffee brand through blockchain-recorded data
(Source Photo by Katya Austin on Unsplash)
316 V. Kumar and P. Kotler

Current Blockchain Applications in Marketing

Aside from the critical data management capabilities for firms, blockchain
presents several marketing applications valued by firms. Particularly, what
makes blockchain appealing to firms is its ability to automate the process of
drawing and managing structured and UD from diverse sources, and provide
instant access in a discernible manner, while maintaining the integrity and
sanctity of data.59 Additionally, blockchain can help avoid data duplica-
tion and unify data entries to present an accurate and holistic perspective
on customers. This section presents five specific application areas where
blockchain continues to help companies in developing marketing actions.

Understanding Customer Needs to Deploy Blockchain

A recent development in consumer expectations is the need to know the

source of firm offerings they consume (e.g., food, medicines, donations,
etc.). For instance, in the case of the agri-food industry, research has found
that rational decision-making, utility maximization, systematic interpretation
of information, and optimal choice are hampered because information is
often imperfect, incomplete, inaccessible, asymmetrically distributed, non-
standardized, or costly to collect.60 Such a situation gives rise to information
asymmetry among consumers, which leads them to make choices that are
not in line with their preferences.61 Further, when faced with information
uncertainties, research has found that users do not behave as if they were
maximizing expected utility.62 In this regard, research has identified that if
asymmetric information is at the core of market failures and sub-optimal
choices, it can reasonably be assumed that better information and more trans-
parency will be at the core of any solution.63 Blockchain presents one such
solution that offers consumers access to information on request safely and
transparently.
Using blockchain, consumers can trace the journey of the products and
components to verify their authenticity. Additionally, under blockchain’s
transparency, users can also evaluate the alignment of a firm’s values with their
values. Specifically, they can follow the journey of firms’ offerings through
the supply chain, verify smart contracts and ownership transfers, and so on,
giving them greater insight into the firms’ offerings.64 The following list
provides a few recent applications of blockchain that focus on providing
information and transparency to consumers.
 10 Transformative Marketing Using Blockchain 317

• Alibaba is considering blockchain solutions for coordinating cross-border

supply chain activities.65
• Everledger uses NATs like IoT, AI, and blockchain to track the move-
ment of goods from raw materials source to sales, to provide greater clarity
and confidence in marketplaces.66 To ensure ethical EV battery recycling,
Everledger and Ford announced the beginning of a world-first battery
passport pilot in October 2022.67
• In Europe, Carrefour uses blockchain technology to ensure the trace-
ability of 24 products, including chicken. Using a mobile device, customers
can scan a QR code on a packet of chicken to get details regarding the
bird’s birth, daily feed, bird’s origin (farm/farmer), the type of slaughter
and processing, and its arrival in store.68 With its announcement that
it would begin using blockchain technology with its products in April
2022, Carrefour Bio is blazing new ground. The project is motivated
by customers’ increased demand for transparency regarding the origins
of organic products and the manufacturing processes utilized to create
them.69
• Volkswagen and Renault have developed telematics systems that capture a
vehicle’s data on mileage, maintenance, and repair; and the engine usage
history via the blockchain that can then be used by manufacturers, buyers,
insurance companies, and dealers to know about a vehicle.70 In July
2021, Renault Group implemented in numerous Renault plants around
Europe, a new blockchain system for the certification of vehicle compli-
ance, called XCEED. This is the first industrial-scale blockchain project in
the automotive industry.71

Revisiting Firm Capabilities to Integrate Blockchain

While firm capabilities may refer to a wide range of functional areas, with
regard to blockchain, four specific firm capabilities come to the fore—
data management, nature of exchanges, organizational excellence arising
from internal processes, and managing supply chain partners. Implementing
blockchain in an organization calls for reviewing how firms can improve
on these four firm capabilities to ensure that the firm is equipped and
well-prepared to handle the new marketplace demands.
Companies have started to make considerable progress in improving these
capabilities when introducing blockchain solutions.72 For instance, regarding
data management, LogSentinel and ReCheck in Bulgaria have developed
blockchain solutions that will allow Bulgarian businesses to expand their
318 V. Kumar and P. Kotler

activities outside of the country while ensuring the security of communi-

cation and data sharing. Additionally, services such as digitizing documents,
authenticating documents, and maintaining secure digital identities are also
possible with the new blockchain platform.73 With regard to the nature
of exchanges, De Beers and other diamond manufacturers have developed
a blockchain platform called Tracr that can successfully track a diamond
through the value chain, providing asset-traceability assurance.74, 75
Regarding managing supply chain partners, Vodafone aims to inte-
grate blockchain into its internal processes to advance its supply chain
by promoting and verifying suppliers through a digital identity platform.
Further, this platform can influence procurement decisions alongside other
standard criteria, such as safety, value, delivery, and technology when Voda-
fone invites suppliers to work with them.76 Utilizing the Internet of Things
(IoT), the Digital Asset Broker (DAB) division of Vodafone has partnered
with the Aventus blockchain network to track cargo pods. Using a special
SIM card embedded with a DAB IoT identification passport, DAB logs
data on the blockchain while cargo pods travel. To resolve the expensive
problem of missing cargo pods, also known as Unit Load Devices, Aventus
has previously worked with Heathrow Airport to track luggage, mail, and
freight.77
A successful integration of blockchain in firms would therefore imply (a)
greater traceability of assets, titles, and currencies, (b) direct firm–customer
transactions, without the involvement of intermediaries, (c) greater data
security, and (d) quicker processing of contracts, transactions, and title
transfers.78

Designing Marketing Mix Strategies with Blockchain

As mentioned earlier, blockchain offers process economies by expediting and

securing the processes and data records’ underlying interactions and transac-
tions.79 This implies that blockchain’s security and automatic execution of
transactions help hasten processes that would otherwise be dependent on the
approval of intermediaries or transacting parties. By specifying the condi-
tions under which a transaction may be executed, a blockchain allows two
or more parties to complete their transactions efficiently and more quickly,
with greater security of data and assets. Such critical implications on data,
assets, and processes ultimately reflect on the marketing mix variables of
the implementing firms. Specifically, companies that have been successful in
implementing blockchain have realized impressive gains in each of the four
 10 Transformative Marketing Using Blockchain 319

key marketing mix variables—product, price, place, and promotion, as seen

from the following examples.
Product. Blockchain is being effectively used to secure firm offerings. This
can be seen in various industry applications such as retail, pharmaceuti-
cals, transportation, automobiles, healthcare, and real estate, among others.
For instance, Indonesia has announced plans to implement blockchain solu-
tions to enhance the efficiency and security of global trade and support
information sharing and transparency between all supply chain members.80
Through actions such as container tracking, monitoring of shipment transit
time, and shipment movement information, blockchain can improve ship-
ment visibility and increase trust among the transacting members. Similarly,
the Indian state of Andhra Pradesh has adopted blockchain solutions to
facilitate land registration. This solution, apart from digitizing the purchase
and sale of land, works towards avoiding potential land ownership disputes,
as the ownership details are secure, transparent, and indisputable.81 Other
countries that have initiated the adoption of blockchain for land registry
purposes include the United States, Sweden, Switzerland, France, Japan, and
Brazil.82 The whole route of diamonds, from extraction to retail, is tracked
by De Beers using blockchain technology. This guarantees and confirms that
diamonds are obtained ethically and without passing through conflict areas.
This increases the product’s authenticity and ethical assurance for consumers.
By providing adequate protection in safeguarding a firm’s assets, blockchain
can be efficiently integrated to manage products and services in a wide range
of industries.
Price. While blockchain may not be directly used in pricing strategies of
firm offerings, it does have an indirect effect on prices, through cost savings.
For instance, Data Gumbo’s blockchain technology designed specifically for
oil and gas companies to automate payments is expected to generate about
$3.7 billion annually in cost savings for the implementing companies.83 Such
cost savings can then be used to create value by capturing lost revenues and
generating new revenue sources. In this regard, the biggest impact area of
blockchain in an organization is in cost savings by enhancing operational
efficiencies. A recent study found that approximately 70 percent of the value
at stake in the short term for firms implementing blockchain is in cost
reduction.84 In this regard, over time, blockchain could guide firms beyond
just realizing cost savings to generating value, thereby moving away from a
price-conscious mode of operation. This would likely manifest through new
business models and enhanced revenue streams that focus on process effi-
ciencies. Blockchain technology can also be used to guarantee transparent
pricing. Examples include blockchain initiatives like Ocean Protocol that seek
320 V. Kumar and P. Kotler

to democratize the value of data and establish transparent pricing for data
services.85
Place. Blockchain delivers significant advantages to firms in terms of
location. Specifically, firms have started using location intelligence technolo-
gies such as GIS to ensure transparency in operations. This has given rise
to geo-spatially enabled blockchains, or simply geo-blockchains, that use a
crypto-spatial coordinate system to add an immutable spatial context that
regular blockchains lack.86 A key distinguishing feature of a geo-blockchain
is the inclusion of proof of location that allows for accurate locating of phys-
ical world events. Specifically, geo-blockchain records transactions that are
agreed on by all coordinating parties and recorded in one distributed ledger,
providing proof of location and other details. Accordingly, geo-blockchain
records not just what goods changed hands, but where that happened, and
under what conditions (Chiappinelli, 2019). Such a system removes the
instances of firms having to reconcile contradicting versions of an object’s
journey details, as captured by the coordinating parties. Many firms across
various industries such as retail, healthcare, manufacturing, and logistics have
implemented geo-blockchains to mainly track the origin/journey of goods,
in addition to documenting transaction details. For instance, companies such
as Walmart, Porsche, DeBeers, Nespresso, and FOAM have adopted geo-
blockchain technology to obtain data that all transacting members agree on
efficiently (Bolger, 2019).87
Promotion. Since blockchain is technology-oriented around the security
needs of users,88 its crucial benefits are seen during interactions between
parties. With specific regard to marketing promotions, blockchain can be
used effectively in marketing communications and media management.
Several firms that have started implementing blockchain for their promo-
tional activities are seeing early gains. For instance, Cathay Pacific has
implemented blockchain in managing its loyalty program so that customers,
airline partners, and the airline itself can manage member rewards in
real time.89 In terms of media management, Unilever has implemented
blockchain to improve online advertising efficiency. Through this implemen-
tation, Unilever was able to improve ad reconciliation efficiency wherein
advertisers ensure contracted agreements are delivered.90 Similarly, Toyota
implemented a blockchain solution for managing its digital ad strategy. The
implemented solution involved directing ad spending in an efficient manner
that subsequently reduced ad fraud and increased web traffic by 21 percent.91
Additionally, blockchain might offer a remedy for more transparent adver-
tising. In one such instance, the Basic Attention Token (BAT) of the Brave
Browser is used to change how consumer ads are delivered. Users receive BAT
 10 Transformative Marketing Using Blockchain 321

in return for watching commercials, ensuring a more open and cooperative

advertising paradigm. Influencer marketing authenticity certification may be
another instance of blockchain-assisted promotion. Blockchain can be used to
confirm the legitimacy of influencers’ following and engagements, as fraudu-
lent followers and engagement are a major concern in influencer marketing.
Platforms like SocialBook give businesses the tools enabled by blockchain
they need to ensure authentic influencer collaborations.92 Finally, content
authenticity may be achieved using blockchain. Blockchain technology can
be used to validate promotional information in the age of fake news. For
instance, The New York Times has been experimenting with using blockchain
to verify news images and other information.93

Driving Customer Engagement Through Blockchain

Blockchain has enormous potential in allowing firms to engage with their

customers which can result in enhanced levels of direct contribution (i.e.,
purchases) and indirect contribution (i.e., referrals, influence, and feedback)
to the firm.94 Companies that have implemented blockchain to improve CE
have started seeing early success. For instance, counterfeiting in the wine
industry is estimated to cost the industry around $70 billion annually.95
To stave off such losses and improve revenues, blockchain is being used to
remedy the situation.
For instance, Cellr is a blockchain solution that embeds RFID tags in
bottle caps that allow wine buyers to verify the product’s origin and that the
wine has not been tampered with. Further, through a mobile phone app the
RFID tags are designed to deliver product information, conduct promotions/
content, offer usage tips, and provide product discounts that can improve
customer engagement. Additionally, in the event of the cap being tampered
with, a message regarding the breach can be sent to the prospective buyer
and/or the company officials. Therefore, blockchain is being used to not only
protect the firm’s offering but also drive CE which can ensure customers
continue to stay with the firm. Miller Lite uses blockchain to engage with
its customers. The company has designed and deployed a mobile game about
beers and has geo-targeted customers in over 230,000 bars and restaurants
across the US Consumers answering all the trivia questions correctly get to
win a $5 prize that can be used to purchase a Miller Lite. This game is built on
blockchain and uses non-fungible tokens to provide the quiz, social badges,
and rewards for social media sharing and to ensure that the $5 prize token
cannot be counterfeited.96
322 V. Kumar and P. Kotler

Research has identified that strengthening loyalty can help stimulate

CE.97 In this regard, aside from promoting one-time uses, blockchain is
also being used to promote CE by building/strengthening customer loyalty.
For instance, online beauty brand Cult Beauty implemented blockchain
to provide information to enable decision-making, ensure transparency
regarding product information, and communicate the sustainable impact of
their products (i.e., vegan, cruelty-free, recyclable, etc.) to their shoppers
directly and consistently. This system is expected to improve engagement and
loyalty for both the brands and the retailer.98 Similarly, blockchain is also
being used to manage reward points. For instance, Singapore Airlines’ digital
wallet, KrisPay, allows members to transfer KrisFlyer points to partner retail
merchants in real time. The redeemed points can be applied across a variety
of retailers in several product categories. Further, rewards can be used for
either full or partial payment and accumulate in the same way as traditional
miles.99 NBA Top Shot, a platform developed by Dapper Labs on the Flow
blockchain, enables fans to purchase, sell, and exchange legally licensed NBA
collectible highlights. Both basketball fans and cryptocurrency enthusiasts
have been highly engaged because of these digital “moments”.100 Therefore,
blockchain is being increasingly used to drive CE, with more companies
expressing interest and commitment to do so.

Designing Digital Strategies with Blockchain

Blockchains have two key characteristics—they are distributed, and they

are in digital form.101 Therefore, they have much to contribute in terms
of aiding firms in designing digital strategies. To understand blockchain’s
contribution in designing digital strategies, firms need to ascertain two crit-
ical components—the capabilities they have, and the value they intend to
generate.102
The journeys that companies undergo in developing their said capabilities
are largely unique. In this regard, research has investigated the differences
between legacy firms and digital natives in developing certain capabili-
ties.103 Developing successful digital strategies requires substantial upfront
and sustained investment in firm capabilities in three key areas—technology,
marketing, and human resources.
The existing technological capabilities (i.e., software, applications, systems,
and technical know-how) of firms will inform them of their preparedness
to embrace the digital ecosystem and identify gaps to be filled to achieve
digital maturity. While digital natives are expected to be well-prepared in
 10 Transformative Marketing Using Blockchain 323

technological expertise and know-how, legacy firms will have to adopt a more
thoughtful approach to making them technologically adept.
A legacy firm that has successfully used blockchain to revamp itself is
Kodak. The company has been having a difficult time since the introduc-
tion of smartphones and advanced digital photography formats. In 2018,
Kodak used blockchain technology to launch KodakOne, a digital manage-
ment platform for the creation of an encrypted digital ledger of copyright
ownership. Accordingly, photographers can add new images as well as archive
images to the system. The blockchain system stores the images in a public
ledger format, thereby providing protection to the rightful owners of the
image and preventing any ownership dispute.104 Further, Kodak subse-
quently announced the launch of their token named KodakCoin, designed
to work on the KodakOne platform to provide a completely secure method
of digital rights management for photographers. Accordingly, token holders
will be able to upload new images, archive older work, and manage rights for
their images on the platform.105
With periodic changes in customer needs, constant updating of marketing
capabilities is essential for firms to develop successful digital strategies. Given
recent consumer preferences to know about a product’s origin and journey
before they make a purchase, luxury brand manufacturer LVMH is imple-
menting blockchain for proving the authenticity of high-priced goods and
tracing the origins from raw materials to the point of sale and beyond to the
used-goods markets.106
The development of successful digital strategies depends on skillful human
talent and technology management. In addition to relevant talent acquisition
and management, technological capabilities also include continuous learning
management, especially regarding NATs and organizational vision in incor-
porating all relevant NATs in all value-creating functions. Since technology
is constantly evolving, employees also need to be able to don multiple hats,
work across departmental silos, and constantly update and upgrade their skills
regarding NATs. Newer firms in traditional industries such as human resource
management, legal services, and tourism are changing the narrative of regular
business functions. For instance, Aworker is a blockchain-based platform that
lets job seekers establish their qualifications instantly, thereby increasing their
chances of landing job offers. Additionally, due to the transparent and decen-
tralized nature of blockchain, such a system increases the speed and efficiency
of assessing the candidates and determining the best competitive compensa-
tion packet in real time. Companies can therefore minimize their hiring and
onboarding expenses in an impactful manner than the traditional way.107
324 V. Kumar and P. Kotler

The success of digital strategy implementations also depends on the

problem(s) the digital strategy is attempting to solve. Specifically, firms must
be clear in establishing what value is being created via the digital strategy and
for whom.108 For instance, the value created through a blockchain imple-
mentation could focus on (a) conducting transactions (e.g., Ripple for global
payments through various financial institutions), (b) negotiating contracts
(e.g., BitProperty allows anyone anywhere in the world (except the United
States and Japan) to invest in real estate), (c) aggregation and/or dissemina-
tion of information (e.g., RiskBlock provides proof of insurance and notice
of loss to insurers and insurance companies), (d) establishing authenticity
(e.g., Provenance provides chain-of-custody and certification details of supply
chains), (e) managing access control (e.g., MedRec provides secure access
to patient records for patients and authorized medical professionals), (f )
rights management (e.g., Monegraph enables artists to define their licensing
terms and facilitate transactions with publishers or digital-art buyers) and (g)
securing ownership control (e.g., Ubiquity records property information to
ensure a clean record of ownership), among others. Further, such value can
be created for one or more groups of users such as customers, firms, financial
intermediaries, government, channel partners, and citizens, among others.

The Future of Blockchain in Marketing

The discussion thus far has focused on what blockchain can offer to individ-
uals and organizations. To provide a brief recap, blockchain is a foundational
technology that consists of an electronic, distributed ledger and creates an
immutable database for securely transferring data. The decentralization of
records ensures that no single point of weakness exists, which lowers the like-
lihood of hacking and data breaches. Additionally, the decentralization of the
ledger implies that no single entity can make changes to the ledger without
following a consensus protocol, in which most of the users on the network
must agree with the change after authenticating themselves via mathemat-
ical algorithms. Further, the blockchain’s security and automatic execution of
transactions help hasten processes that would otherwise be dependent on the
approval of intermediaries or transacting parties. In all, blockchain exempli-
fies the following three distinguishing elements: (a) decentralized electronic
records secured by cryptography, implying greater security, (b) immutability
of records and consensus-based system ensure the integrity of records through
the blockchain, and (c) allows disintermediation rendering the middle-men
 10 Transformative Marketing Using Blockchain 325

unnecessary through automated execution of contracts.109 Looking ahead,

the future of blockchain for marketing purposes appears to be promising
and varied. While we can expect progress in blockchain capabilities in many
organizational areas, three areas that stand out are discussed here.

Data and Transaction Security

It is almost a given that newer technological innovations pay closer atten-

tion to making the usage experience safe and secure for all users concerning
data and transaction security, compared to legacy technologies. This is also
largely reflective of user needs and preferences in adopting newer technolo-
gies that stem from their concern about losing control over their data.110
Yet, research among users has uncovered that when privacy is offered at the
expense of loss of user experience, users are more likely to stay away from
selecting the choice that would offer them greater protection.111 Businesses
must contend with and navigate this challenging paradox thereby requiring
them to carefully balance business operations and security setting prefer-
ences. Even within companies, differences in attitudes towards security in the
blockchain platform exist.112,113
In the future, blockchain offerings could increasingly focus on tapping
newer sources of value for all the stakeholders involved, rather than be limited
to serving functional benefits. In this regard, the following key guiding prin-
ciples are expected to motivate companies to develop innovative business
models and generate more value.114 First, blockchain will not offer data and
transaction security protection; instead, the appropriate security features will
have to be decided based on the various business contexts. Second, no tech-
nology is perfect, and integrating a newer technology with existing systems
may expose (new) security threats. Finally, there is a trade-off between secu-
rity and efficiency, and determining levels of acceptable performance may be
necessary to finalize the appropriate security settings.

Impact on Advertising Transparency

The US advertising industry has posted consistent performance in the past

few years, with two notable outcomes. First, in 2018 digital advertising
revenues crossed $100 billion for the first time to reach $107.5 billion.115
Second, in 2019 the half-yearly advertising revenues crossed $50 billion for
the first time to reach $57.9 billion.116 These two impressive firsts indicate
industry vitality and impactful changes that could continue in the future.
326 V. Kumar and P. Kotler

An industry development that has played a crucial role in this improved

performance is the programmatic advertising model adopted by the industry.
Programmatic advertising (PA) refers to the use of software, automated
processes, machines, and algorithms to buy digital advertising. Here, adver-
tisers buy targeted page views and audiences on a spot market through real-
time auctions.117 This contrasts with traditional advertising where proposals
for ads are developed, tenders are called for, price quotes are generated, and
price negotiation is involved before the ad spots are decided. The growth of
PA is impressive and is estimated to account for 88 percent of all digital ads
in the United States by 2021.118, 119
The quick growth and positive impact of PA can be observed through the
major benefits it presents (especially over the traditional advertising models)
to the ad ecosystem—that is, firms, ad agencies, and consumers.120 First, the
reach of PA is much wider. Since multiple ad exchanges are involved in the
selection, firms can cast a wider net in terms of audience reach and potential
ad spaces instantly. Essentially, this improves the scale of advertising while
keeping the cost of advertising from going up. Second, firms and ad agencies
have real-time access to data on ad placements and activity, thereby improving
transparency of the process. Third, the real-time data on ad placements and
activity is complemented with real-time data on ad insights. This allows firms
and ad agencies to change the scope and content of the ad campaigns on
short notice. Fourth, PA goes beyond just impressions and click-through
rates. Specifically, it enables specific targeting, creating ideal user profiles,
geo-targeting, and personalization to reach the right audiences. Finally, since
automation is the key driver of this ad model, not only do firms get to decide
on launching the campaigns immediately, but also avoid reaching out to users
who are not their audiences. This instills efficiency and robustness in devel-
oping and running ad campaigns. Even though PA serves the ad ecosystem
well, the inclusion of blockchain makes it even more appealing. In all the
five major benefits, blockchain can potentially improve ad buying efficiency,
ensure real-time access to the members of the eco-system, identify ad fraud,
provide authenticity of information, and ensure that there are only authorized
people involved in the ad campaign (see Image 10.3).
In this regard, Pepsico recently tested the viability of using blockchain
to ensure advertisers only pay for ads served in environments deemed to
be viewable, safe for the brand, and free of advertising fraud.121 The trial
test involved the comparison of ad campaigns with and without blockchain-
based smart contracts, with initial results showing an improved ad efficiency
of 28 percent because of using smart contracts. Similarly, for Super Bowl
 10 Transformative Marketing Using Blockchain 327

Image 10.3 Blockchain for advertising effectiveness. Blockchain is used to improve

efficiencies in ad buying and ad development
(Source Photo by Scott Graham on Unsplash)

2020, Avocados from Mexico developed a blockchain-powered campaign to

recruit, register, reward, and track consumer engagement that resulted in the
generation of 53,000 registrations for its loyalty program.122 Demand Side
Platforms (DSPs) and Supply Side Platforms (SSPs), which are middlemen
in programmatic advertising, can be eliminated using blockchain, cutting
costs and improving transaction efficiency. For instance, NYIAX (New York
Interactive Ad Exchange) uses blockchain to provide a platform for trading
future ad inventory and is based on the Nasdaq infrastructure.123 Such early
uses of blockchain in digital advertising show that the members of the ad
ecosystem can be integrated more tightly while providing enhanced visibility
of the transaction details to all members. While the promising results for
PepsiCo, Avocados from Mexico, and NYIAX are only in early implementa-
tion, the future could see more uses of blockchain in the ad industry that can
be truly transformative.

Online Marketing Campaign Management

Recent changes in technology have allowed consumers to interact with firms

through a variety of touchpoints that subsequently lead to purchases and
continued interaction. In this scenario, online channels are a critical compo-
nent of the current marketing landscape. Particularly, WOM has increasingly
328 V. Kumar and P. Kotler

taken a more primary role among marketers wherein, consumers provide

information to other consumers who can become potential customers/
marketers of the firm offerings they share information about. Consequently,
firms are increasingly investing in social channels to rapidly create or propa-
gate their brand through viral content, social media contests, and consumer
engagement efforts. To this effect, firms develop and implement online
campaigns to serve a set of established goals.
Formally, a campaign (online and offline) refers to a series of inter-
connected promotional efforts designed to achieve precise marketing goals.
Typically, a campaign is composed of one or more promotions, each of which
is an initiative, or a device designed to attract the customers’ interest. Further,
a campaign can be aimed at prospects or existing customers and usually is
undertaken within a defined timeframe.124
In developing online campaigns, firms have always included social
networks as an integral part of the campaign. By connecting three key dimen-
sions—who, what, and when—social networks primarily operate through
a wide range of media to enable functions such as exchanging ideas (e.g.,
blogs and microblogs), networking (e.g., job search), content sharing (e.g.,
news, video, audio and photo sharing sites), location services (e.g., local
networking), promoting products (e.g., websites), providing feedback (e.g.,
review websites), conducting polls (e.g., online surveys), and so on.
With more firms paying attention to human connection, online campaigns
almost always have some form of WOM and/or influencer marketing. The
American Marketing Association refers to influencer marketing as “…lever-
aging individuals who have influence over potential buyers and orienting
marketing activities around these individuals to drive a brand message to the
larger market” .125 Further, the Marketing Accountability Standards Board
defines an influencer as “ a person whose views influence other members
of the buying center in making the final decision” .126 In the social media
setting, research has contributed two key metrics—customer influence effect
(CIE) and customer influence value (CIV).127 Whereas the CIE measures the
net spread and influence of a message from an individual, the CIV calculates
the monetary gain or loss realized by a firm that is attributable to a customer,
through their spread of positive or negative influence. In tracking these two
metrics for a company’s social media campaign, Kumar et al.128 demonstrated
a 49 percent increase in brand awareness, an 83 per increase in ROI, and a 40
percent increase in sales revenue growth rate, thereby bringing accountability
to social media marketing.
 10 Transformative Marketing Using Blockchain 329

In recent times, blockchain has emerged as an attractive addition to a social

media manager’s toolkit. This is because influencers often recommend a firm’s
offering(s) that could win over new customers for the firm. That is, the right
type of influencer could bring in impressive gains for a firm/brand. While
research has devised a way to recognize, identify, and recruit influencers,129
still operational challenges such as the influencer payment system (which
is not often transparent) and customer trust issues in an influencer, among
others.
In this regard, blockchain can, through smart contracts, help list the terms
and prices of the influencer marketing services; set potential warranty condi-
tions until the conditions of the influencer service have been met; serve as
a transparent way for dispute resolution that is; speedily launch marketing
campaigns; remove challenges in measuring campaign effectiveness; identify
fraudulent messages that could mislead consumers; and integrate members
within a single influencer marketing ecosystem (see Image 10.4). In this
regard, blockchain-based companies such as SPIN Protocol and Boosto work
to bring together marketers and influencers for influence marketing. Simi-
larly, WOM Protocol enables brands, content creators, publishers, and social
networks a way to monetize WOM recommendations on any app or plat-
form. While such early implementations are only from digital natives that
are built on the blockchain platform, more such implementations could see

Image 10.4 Blockchain for managing influencer marketing. Blockchain can be used
to manage influencer marketing programs efficiently
(Source: Photo by NordWood Themes on Unsplash)
330 V. Kumar and P. Kotler

even established companies getting into blockchain applications for managing

influencer marketing. Overall, the future looks promising for marketing with
blockchain now gaining a firm place in a brand manager’s toolkit.

Key Terms and Related Conceptualizations

Asset-backed tokens Tokens that are tied to tangible or

intangible assets, such as gold
Blockchain A distributed ledger and immutable
database for securely transferring
data
Governance tokens Tokens that allow token holders to
vote on decisions regarding their
host blockchain
Hybrid blockchain, or consortium A blend of public and private
blockchain blockchains wherein, the
determination of what blocks get
added to the chain and what the
current state is, is controlled by a
select group of participants
Influencer A person whose views influence other
members of the buying center in
making the final decision
Influencer marketing Leveraging individuals who have
influence over potential buyers and
orienting marketing activities around
these individuals to drive a brand
message to the larger market
Non-fungible token (NFT) A token that is valued independently
and is frequently used to represent
digital assets like artwork or
collectibles
Private blockchain, or permission An invitation-only blockchain network
blockchain governed by a central authority that
decides the level and extent of read/
write access participants get in the
operations of the blockchain
Programmatic advertising The use of software, automated
processes, machines, and algorithms
to buy digital advertising
Public blockchain, or permissionless A blockchain where all participants in
blockchain the network have access to all the
ledgers, and no central agency/body
manages the network, including
approving or banning transactions
Security tokens Represent ownership and are linked to
physical assets, much like stock shares
in a firm
(continued)
 10 Transformative Marketing Using Blockchain 331

(continued)
Tokens Flexible tools in the blockchain that
enable everything from
straightforward transactions to
intricate platform interactions
Utility tokens Give users access to platform services
or features

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In R. W. Palmatier, V. Kumar, & C. M. Harmeling (Eds.), Customer
engagement marketing (pp. 1–27). Palgrave Macmillan.
95. Dowling, N. (2020). Wine counterfeiters beware. Cosmos. https://cos
mosmagazine.com/technology/wine-counterfeiters-beware.
96. Palmer, D. (2019). Miller Lite teams with blockchain firm for
customer engagement game. Coindesk. https://www.coindesk.com/
miller-lite-teams-with-blockchain-firm-for-customer-engagement-
game.
97. Bijmolt, T. H., Krafft, M., Sese, F. J., & Viswanathan, V. (2018).
Multi-tier loyalty programs to stimulate customer engagement. In
98. Lawlor, S. (2019). Blockchain technology is being used to lift the lid
on false claims in the beauty industry and it’s set to change the way we
shop. Glamour. https://www.glamourmagazine.co.uk/article/what-is-
blockchain-technology.
99. Vadino, J. (2019). Securing customer loyalty programs with
blockchain for retail. Retail Touchpoints. https://retailtouchpoints.
com/features/executive-viewpoints/securing-customer-loyalty-pro
grams-with-blockchain-for-retail.
100. Conti, R. (2023). Guide To NBA Top Shot. Forbes Advisor. https://
www.forbes.com/advisor/investing/cryptocurrency/nba-top-shot/.
101. Felin, T., & Lakhani, K. (2018). What problems will you solve with
blockchain? MIT Sloan Management Review, 60 (1), 32–38.
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102. Kumar, V. (2021). Intelligent Marketing: Employing New Age Technolo-

gies. Sage Publications.
103. Kopalle, P. K., Kumar, V., & Subramaniam, M. (2020). How legacy
firms can embrace the digital ecosystem via digital customer orienta-
tion. Journal of the Academy of Marketing Science, 48(1), 114–131.
104. Grigonis, H. K. (2018). KodakOne uses blockchain and web crawlers
to spot stolen images. Digital Trends. https://www.digitaltrends.com/
photography/kodakone-creates-photo-registry-blockchain-ces2018/.
105. Greene, T. (2018). Kodak is the latest company to jump on
blockchain. And one of the few that make sense. TNW . https://the
nextweb.com/hardfork/2018/01/09/kodak-is-the-latest-company-to-
jump-on-blockchain-and-one-of-the-few-that-make-sense/.
106. Allison, I. (2019). Louis Vuitton owner LVMH is launching a
blockchain to track luxury goods. Coindesk. https://www.coindesk.
com/louis-vuitton-owner-lvmh-is-launching-a-blockchain-to-track-
luxury-goods.
107. James, A. (2018) Aworker—Disrupting the HR industry through
next-gen blockchain technology. Bitcoinist. https://bitcoinist.com/
aworker-disrupting-hr-industry-next-gen-blockchain-technology/.
108. Felin, T., & Lakhani, K. (2018). What problems will you solve with
blockchain? MIT Sloan Management Review, 60 (1), 32–38.
109. Kumar, V., Ramachandran, D., & Kumar, B. (2020). Influence of
new-age technologies on marketing: A research agenda. Journal of
Business Research. https://www.sciencedirect.com/science/article/abs/
pii/S0148296320300151.
110. Auxier, B., Rainie, L., Anderson, M., Perrin, A., Kumar, M., &
Turner, E. (2019). Americans and privacy: Concerned, confused
and feeling lack of control over their personal information. Pew
ResearchCente r. https://www.pewresearch.org/internet/2019/11/15/
americans-and-privacy-concerned-confused-and-feeling-lack-of-con
trol-over-their-personal-information/.
111. Athey, S., Catalini, C., & Tucker, C. (2017). The digital privacy
paradox: Small money, small costs, small talk (NBER Working Paper
No. 23488). National Bureau of Economic Research. https://www.
nber.org/papers/w23488.pdf.
112. A recent survey found that while existing companies that inte-
grate blockchain into their operations (established enterprises) believe
blockchain provides greater security than conventional IT solutions
(71%), not many emerging disruptors feel the same way (48%). The
survey also revealed that emerging disruptors found the opportunity
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for new business models and the creation of new value chains to
be significant benefits of blockchain (Pawczuk, L., Massey, R., &
Holdowsky, J. (2019). Deloitte’s 2019 global blockchain survey.
Deloitte Insights. https://www2.deloitte.com/us/en/insights/topics/
understanding-blockchain-potential/global-blockchain-survey.html).
113. While the two types of organizations have different attributes of
blockchain technology, value can be brought in when the disruptor
leads the way in identifying innovative solutions and the established
enterprises can make it mainstream.
114. Zhang, R., Xue, R., & Liu, L. (2019). Security and privacy on
blockchain. ACM Computing Surveys (CSUR), 52(3), 1–34.
115. IAB. (2019a). IAB internet advertising revenue report—2018 full
year results. https://www.iab.com/wp-content/uploads/2019/05/Full-
Year-2018-IAB-Internet-Advertising-Revenue-Report.pdf.
116. IAB. (2019b). U.S. digital ad revenue climbs to $57.9 billion in
first half 2019, up 17% YOY, according to IAB internet advertising
revenue report. https://www.iab.com/news/u-s-digital-ad-revenue-cli
mbs-to-57-9-billion-in-first-half-2019/.
117. Cui, Y., Zhang, R., Li, W., & Mao, J. (2011). Bid landscape fore-
casting in online ad exchange marketplace. In Proceedings of the 17th
ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining (pp. 265–273).
118. Fisher, L. (2019). US programmatic ad spending forecast 2019.
eMarketer.com. https://www.emarketer.com/content/us-programma
tic-ad-spending-forecast-2019.
119. The United States contributed more than $200 billion of the
$418.4 billion in global programmatic ad spending in 2021,
and this amount was expected to surpass $493 billion by the
end of 2022 (Statista. (2023). Programmatic advertising in the
United States. https://www.statista.com/topics/7912/programmatic-
advertising-in-the-us/#topicOverview).
120. Brayer, M. (2020). What is programmatic advertising? Outbrain.
Accessed from https://www.outbrain.com/blog/programmatic-advert
ising/.
121. Page, R. (2020). Can blockchain deliver on its big advertising
promises? CMO.com. https://www.cmo.com.au/article/671101/can-
blockchain-deliver-its-big-advertising-promises/.
122. Ellwanger, S. (2020). How blockchain fueled avocados from Mexico’s
super bowl campaign. MediaPost.com. https://www.mediapost.com/
publications/article/346755/how-blockchain-fueled-avocados-from-
mexicos-super.html.
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123. Rogers, B. (2021). Carolina Abenante Cofounds NYIAX To Bring

Nasdaq-Like Transparency To Digital Ads. Forbes. https://www.for
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nyiax-to-bring-nasdaq-like-transparency-to-programmatic-ads/?sh=
2a0f1a3c1369.
124. Kumar, V., & Reinartz, W. (2018). Customer relationship manage-
ment—Concept, strategy, and tools (3rd ed.). Springer.
125. AMA. (2020). Influencer marketing. https://www.ama.org/topics/inf
luencer-marketing/.
126. MASB. (2020). Buying roles. https://marketing-dictionary.org/b/buy
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127. Kumar, V., Bhaskaran, V., Mirchandani, R., & Shah, M. (2013).
Creating a measurable social media marketing strategy: Increasing
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Marketing Science, 32(2), 194–212.
128. Kumar, V., Bhaskaran, V., Mirchandani, R., & Shah, M. (2013).
Creating a measurable social media marketing strategy: Increasing
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Marketing Science, 32(2), 194–212.
129. Kumar, V., Bhaskaran, V., Mirchandani, R., & Shah, M. (2013).
Creating a measurable social media marketing strategy: Increasing
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130. Hileman, G., & Rauchs, M. (2017). Global blockchain bench-
marking study. Cambridge Centre for Alternative Finance. https://
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bal-Blockchain-Benchmarking-Study_Hileman.pdf.
131. Tama, B. A., Kweka, B. J., Park, Y., & Rhee, K. H. (2017). A critical
review of blockchain and its current applications. In 2017 Inter-
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132. Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017). An
overview of blockchain technology: Architecture, consensus, and
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blockchains/.
 11
Putting It All Together

Avant-garde. This book began with this term to characterize the changes
occurring in the marketing world, and its subsequent impact on firms,
consumers, and other stakeholders. We hope this book has effectively
conveyed the revolutionary effect that new-age technologies, or NATs, are
having on the state of marketing today. In particular, long-standing marketing
strategies are changing dramatically regularly, redefining several aspects of
our everyday lives. This is a result of the growing pressure on businesses
to (a) outperform their rivals; (b) quickly adjust to shifting market condi-
tions to stay in business; and (c) provide customers with timely offerings
that genuinely meet their needs. More than ever, it seems like businesses are
required to manage a multitude of constraints and factors at once, all the
while needing to be agile and quick to respond to disruptions in the broader
business environment.
Technology is the driving force behind this evolution of business, as it
consistently demonstrates its capacity to fundamentally upend established
business procedures and generate novel prospects for transformation. NATs
offer both significant opportunities and difficulties to uphold the status quo
in the current business environment.1 Artificial intelligence (AI), genera-
tive AI, robots, machine learning (ML), drones, Internet of Things (IoT),
blockchain, and metaverse are the eight NATs that are covered in this book.
All eight of these NATs offer competent and practical opportunities for orga-
nizational activities that can benefit the organization as well as its other related
stakeholders.
While each of the preceding chapters has focused on the individual
NATs, this concluding chapter aims to tie in all the individual chapters

© The Author(s), under exclusive license to Springer Nature 345

Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7_11
346 V. Kumar and P. Kotler

into an overarching strategic framework—an integrated strategy for stake-

holder engagement—that can be informative in understanding the power of
transformative marketing using NATs. Figure 11.1 illustrates this framework.
As provided in Figure 11.1, each of the NATs, when adopted using
the Marketing 5.0 concept, provides firms with opportunities to develop
capabilities to perform better and to utilize technological advancements
better. Subsequently, these capabilities will better prepare firms to deploy
strategic and tactical marketing actions in a timely, efficient, and effective
manner. These firm marketing actions would then result in the creation of
a technology-based enhanced customer experience (CX). This is a crucial
outcome for firms, as demonstrated by academic research as it leads to better
customer engagement (CE).2
The connections up to this point have been covered in the previous chap-
ters from each NAT’s perspective. Benefits to all parties involved (customers,
staff, community, channel partners, and government) can also be seen
following the development of improved CX. In addition to discussing the
advantages for the other stakeholders, this chapter will provide a summary of
the framework that has been covered thus far in the book.

New-Age Technologies for Better Marketing:

A Strategic Framework
As was previously established, technology is advancing quickly and is now
widely present in practically every aspect of our lives. The convergence of
NATs in a Marketing 5.0 world suggests a sophisticated, networked smart
device ecosystem that can benefit both service providers and consumers.
Although there are examples of businesses using NATs for marketing purposes
on their own, new developments show that there is a need and desire to use
these technologies as part of integrated marketing strategies. The continual
gathering of data, continuous learning, and intuitive service delivery pred-
icated on the acquired knowledge enables the ensuing generation of value
from NAT-driven marketing strategies.3 This section provides a discussion of
the components described in Figure 11.1.

New-Age Technologies

Current business trends show that companies are becoming more interested
in using data to inform regular business operations and the creation of
targeted marketing campaigns. The usage of NATs has become apparent in
 Employing New Age Generation of Unique
Technologies Firm Capabilities

Artificial Intelligence (AI)

(Chapter 3) Engaging Key
• Data-related Stakeholders
Generative AI
(Chapter 4) o Data sanctity
Through o Data-driven
the insights Customers
Machine Learning Marketing
(Chapter 5) • Operations-related
5.0 Concept o Process
improvements Employees
Metaverse • Data-driven Enriched
(Chapter 6) through automation Better
marketing Strategic
o Transparency in Customer
• Predictive & Tactical Channel Partners
Internet of Things operations
marketing Marketing Experience
(Chapter 7) • Contextual • Management-related
o Creation and Actions
marketing Community
Robotics • Augmented management of
(Chapter 8) marketing marketplaces
• Agile o Establishment of Government
Drones marketing technology-driven
(Chapter 9) ecosystems

Blockchain
(Chapter 10)

Fig. 11.1 NATs for transformative marketing: A strategic framework

(Source Adapted and extended from Kumar, V. (2021). Intelligent Marketing: Employing New Age Technologies. Sage Publications)
11 Putting It All Together
347
348 V. Kumar and P. Kotler

the process. Additionally, businesses are being encouraged to closely consider

NATs due to their potential to streamline the tracking and integration of
data from various sources as well as the subsequent mining of said data using
advanced techniques to generate insights. Furthermore, the NATs’ increased
potential for creating innovative solutions and the new business opportuni-
ties they offer are adding to their appeal. More significantly, businesses can
investigate the potential for combining several NATs to collaborate to find
creative solutions that benefit all parties involved in the exchange ecosystem.
AI technology plays a crucial role in the marketing industry by enhancing
intelligent searches, creating intelligent advertisements, personalizing offer-
ings and content delivery, and transforming customer service through the
use of bots, among other important actions. From a technical perspective, AI
can automate various activities involved in collecting, storing, managing, and
retrieving information, which in turn aids in the creation and management
of valuable offerings for businesses.4 Moreover, the success of AI initiatives
relies on aligning them with the goals of the organization and making them
a comprehensive effort that spans across hierarchies, functions, and stake-
holders. The impact of AI on various stakeholders is evident through several
factors, including the creation of personalized marketing campaigns to foster
genuine relationships with customers (which adds value to firms), the emer-
gence of new job roles (which adds value to employees), the development
of additional technology ecosystem offerings that enhance the final product
(which adds value to channel partners), the efficient handling of resource-
limited settings through human-centered design (which adds value to the
community), and the ability to deploy and manage public policy initiatives
(which adds value to the government).
Generative artificial intelligence (GAI) models are made to recognize
patterns and structures in current data and then produce new data samples
that follow those patterns. These devices can produce a wide range of
information, such as text, photos, audio, and more. Generating natural
language, synthesizing images, creating content, augmenting data, finding
drugs, and many more areas are just a few of the many uses for GAI. Partic-
ularly, GAI serves in activities such as product development & innovation,
marketing & sales, and research & development, among others (a source of
value for firms), enhancing work experience, boosting productivity via work-
flow automation, and empowering workers to achieve more (a source of value
to employees), managing channel relationships, optimizing operations and
collaborations, and empowering sales and support, among others (a source
of value to channel partners), fostering positive change and improving lives
across various sectors and user groups (a source of value to the community),
 11 Putting It All Together 349

and improving how governments operate, deliver services, and make decisions
(a source of value to the government).
Machine learning deals with the process of training machines to learn over
time. Firms are using ML for many functions that include personalizing
content and offerings, developing dynamic pricing strategies, identifying
counterfeit products, improving sales, and building and enhancing personal
relationships with customers, among others. ML also serves stakeholders by
its ability to aid customer management strategy initiatives (a source of value to
firms), expediting customer segmentation, lead customization, and marketing
element customization, thereby enabling employees to use their time produc-
tively for more meaningful actions (a source of value to employees), assisting
in accurate sales forecasting and thereby efficient inventory management (a
source of value to channel partners), assisting in environmental and natural
resource conservation efforts (a source of value to the community), and moni-
toring and managing cyber security threats through specific, timely responses
(a source of value to the government).
Metaverse is more than just a concept, but a concrete reality—an immer-
sive place in which our online interactions transcend the constraints of
traditional platforms. At the heart of the Metaverse is a web of intercon-
nected technologies, including virtual reality (VR), augmented reality (AR),
blockchain, artificial intelligence (AI), and others, all working together to
create an immersive and unified digital experience. These technologies serve
as the foundation for a new era, altering how we communicate, collaborate,
and form communities in the digital sphere, thereby creating value for all
parties involved. The metaverse also serves as a platform for businesses to
interact with their audiences and learn more about them (a source of value to
firms), a way for employees to collaborate in an interactive way (a source of
value to employees), a way to bring together multiple brands and advertisers
in one place to share an interactive space for customer courting (a source of
value to channel partners), a place for community building, discussions, and
interactions on matters of shared interest (a source of value to channel part-
ners), and a way for governments to easily provide services and applications
to citizens using a technology that simulates the three-dimensional world we
live in (a source of value to the government).
IoT represents an interconnected web of devices that can collectively
work in collecting, communicating, and processing information in real
time through the internet to perform or aid in performing certain defined
tasks. However, promising areas of IoT deployment such as smart cities
and connected travel solutions indicate this NAT’s increasing acceptance.
Further, IoT continues to serve various stakeholders through their use in
350 V. Kumar and P. Kotler

the development of an automation-driven ecosystem leading up to the term

“Industry 4.0” (a source of value to firms), the accurate identification of
when machinery parts/components may need replacements (a source of
value to employees), its role in avoiding duplication of effort (a source of
value to channel partners), its role in societal wellbeing functions such as
ambient assisted living (a source of value to the community), and its ability
in conducting governmental operations and managing national resources (a
source of value to the government).
Robotics facilitates daily lives, while also learning and applying thought as
they continue to work. This enables robotics to provide personalized service
that uniquely matches the needs of every individual. The abilities of robots
currently display a wide bandwidth to perform a variety of functions that
range from basic (such as moving goods through a warehouse) to nuanced
(such as responding to customer queries in a service setting and delivering
healthcare services). Further, robots continue to serve various stakeholders
through their versatility in being redesigned to accommodate changes in oper-
ations (a source of value to firms), their ability to work alongside humans
to complete several consumer-facing tasks (a source of value to employees),
their assistance in curation and personalization of offerings (a source of value
to channel partners), their use in the distribution of essential services such as
education, healthcare, and so on (a source of value to the community), and
their use in the delivery of public utility offerings (a source of value to the
government).
Drones provide firms with more access to users, more opportunities for
customer interaction touchpoints, more avenues for operational efficiencies,
and richer sources of information, among others. Drones also serve other
stakeholders by assisting in business functions such as agricultural activities,
construction, transportation, logistics, media, and so on (a source of value
to firms), repurposing some aspects of jobs that can be replaced or directed
towards critical and value-creating actions (a source of value to employees),
being economical while being visually captivating and therefore of use in
media (a source of value to channel partners), playing a vital role in emer-
gency and humanitarian relief efforts (a source of value to the community),
and serving as a critical asset of national security (a source of value to the
government).
Blockchain refers to the distributed ledger technology that is based on
creating a distributed consensus in the digital online world, thereby firmly
establishing trust in actions even when operating in the online world. This
technology contains salient features such as decentralized operation, secu-
rity, immutability, transparency, and autonomy, among other properties.
 11 Putting It All Together 351

Blockchain works on several consumer-facing applications such as ride-

sharing apps, ensuring food safety, online payments, insurance services,
and several more, thereby delivering real-time value to end users. Further,
blockchain benefits other stakeholders by enhancing the efficiency of supply
chain activities (a source of value to firms), authenticating candidate qualifi-
cations instantly to facilitate hiring processes (a source of value to employees),
managing access control and rights management of supplier-related processes
(a source of value to channel partners), addressing labor exploitation by
ensuring workers’ human rights (a source of value to the community), and
optimizing information technologies for managing public digital services (a
source of value to the government).

Generation of Firm Capabilities

The creation of firm capabilities was covered in great detail in each chapter,
albeit from a particular NAT perspective. Upon delineating the compre-
hensive structure of the NATs and how they align within the Marketing
5.0 world, several distinct capabilities emerge. Furthermore, companies that
frequently use multiple NATs for different organizational processes are specif-
ically mentioned when discussing the significance of the identified capabili-
ties. Combining several NAT deployments is anticipated to help businesses
develop capabilities that will benefit all of their business divisions. As illus-
trated in Figure 11.1, these capabilities can be grouped as data-related,
operations-related, and management-related and discussed here.
Data-related. These capabilities relate to how data can prepare firms for
better performance. Whereas data-related capabilities may indicate several
firm competencies, two specific capabilities are of interest—data sanctity, and
data-driven insights.
Data sanctity refers to how “clean” the information being recorded is in the
data. This suggests that the data thus obtained can be independently checked
to confirm its accuracy. Additionally, the traceability and transparency of
processes—which are frequently necessary for securing transactions—are
also related to data sanctity. Blockchain, for example, can securely store
all transaction records at every stage of the exchange process. Additionally,
blockchain gives external stakeholders (like consumers, the government, etc.)
access to data about the provenance of products, their ingredients and parts,
and their supply chain journeys. This promotes trust in businesses, lessens
counterfeiting, and establishes authenticity.
Data-driven insights pertain to the potential outcomes that businesses can
achieve using “clean” data. Data-driven insights are essential for managing
352 V. Kumar and P. Kotler

current and future firm offerings and customer expectations as businesses

gather more detailed and up-to-date information about their customers and
usage patterns. More significantly, businesses can create individualized offer-
ings by learning about customers’ preferences. In this sense, NATs like AI,
ML, and IoT equip businesses to provide the anticipated offerings to the
appropriate user at the appropriate moment. Businesses are also able to recog-
nize changing market trends and plan pertinent reactions to deal with them.
NATs also allow businesses to interact directly with their stakeholders. In
this sense, smart contracts that use cryptocurrency to compensate CE can
be created and managed using blockchain technology.
Operations-related. These capabilities have to do with how businesses can
perform business processes more effectively and efficiently. Process improve-
ments through automation and transparency in operations are two essential
skills here.
The NATs allow firms to realize process improvements through automation
which then prepares the firms to improve their product development and
optimize their processes. Through NATs such as robotics, IoT, and ML, firms
can monitor their operational assets and schedule proactive maintenance
to increase productivity, improve efficiency, and reduce operating costs.
Applications such as smart warehousing and smart transportation enable
intuitive demand fulfillment, warehouse automation, and route optimization
for maximum efficiency. Further, NATs such as generative AI and robotics
allow firms to automate customer service actions that range from handling
routine queries to addressing more complex issues.
The implementation of NATs greatly enhances transparency in operations,
especially when it comes to determining the origin of products and their
components. Furthermore, with increasing environmental concerns, both
customers and companies feel the need to track the entire journey of prod-
ucts and components to evaluate how production practices align with their
values. For instance, blockchain technology provides the necessary tools to
trace the supply chain of products, allowing customers to develop greater
trust in brands and make long-term decisions to support their offerings. By
utilizing the Global Location Number, which serves as a unique identifier for
a company’s physical locations such as stores and warehouses, businesses can
accurately track and share information about the production and harvesting
of food items. This number plays a crucial role in supply chain exchanges
and traceability programs, as it facilitates the precise capturing and sharing of
data regarding the movement of products along the supply chain.5
Management-related. The management’s ability to respond to and
prepare for marketplace changes, whether influenced by technology or not,
 11 Putting It All Together 353

is crucial. This suggests that NATs can enhance organizational efficiencies

at different levels and leverage technology to drive business activities. More
specifically, capabilities such as the creation and management of marketplaces,
and the establishment of technology-driven ecosystems can be developed to
assist managements.
In addition to helping businesses get things done, the NATs’ functionali-
ties also help in the creation and management of marketplaces. In other words,
management would be able to use NATs for purposes other than merely
enhancing their technical capabilities, particularly to generate new business
opportunities. Adoption of NATs can stimulate the development of new
markets, including AI-powered eHealth/mHealth solutions, ML-powered
online credit markets, blockchain-powered supply chain connectivity, crop
information access, and IoT-powered connected devices. By putting data at
the center of operations, these markets or offerings have completely changed
several industries. In particular, businesses can protect and store their data,
opening up a market for secure data sharing and monetization.
When NATs are implemented collectively and within the Marketing 5.0
context, they offer firms numerous benefits and can lead to the establishment
of technology-driven ecosystems. As mentioned in previous chapters, AI, gener-
ative AI, and ML are often implemented together. Similarly, robotics and IoT
have been combined to drive business transformation. Additionally, the joint
implementation of AI and industrial IoT has resulted in impressive opera-
tional and efficiency gains for organizations. By connecting devices on a single
platform, enabling them to exchange information with each other and with
users, and integrating multiple functionalities, firms can gain a significant
competitive advantage. This advantage allows firms to understand their users’
behaviors and decisions, utilize these insights for new product development,
improve service quality, manage customer experiences, and ultimately foster
loyalty among stakeholders.

Strategic and Tactical Marketing Actions

When it comes to strategic marketing initiatives, NATs have the power

to significantly alter how businesses are organized and run. Initiatives like
customer relationship management (CRM), which entails tasks like bringing
in new clients, keeping hold of current ones, and winning back former clients,
may fall under this category of strategic actions. Moreover, among other
things, NATs can help create profitable customer loyalty programs, valuable
brands, and effective product development procedures. Businesses can use
354 V. Kumar and P. Kotler

AI/ML technology and specific customer data, for instance, to provide indi-
vidualized goods and services. Additionally, NATs like AI, ML, and IoT can
help managers improve the value proposition for customers over time and
support real-time learning. By adopting a strategy that focuses on curated
products delivering increasing value to customers, companies can achieve
customer retention and establish a sustainable competitive advantage—a
crucial outcome of strategic marketing actions.
When it comes to short-term tactical marketing actions, NATs can be used
to target a particular behavior or result. Delivering superior brand experi-
ences, service delivery initiatives, pricing, product management, distribution,
and promotions, as well as targeted advertising and communications content,
are a few examples of such tactical actions. For example, businesses can
use drones and robotics to automate and streamline processes. Customers
may receive better experiences from such effective actions. Technologies like
blockchain and the Internet of Things can also help businesses with data and
security management, which can lead to process economies and increased
functional efficiency. These kinds of projects can create memorable customer
experiences, automate, and optimize business procedures, create corporate
equity, and eventually get companies ready to produce value for all parties
involved.

Customer Experience

The strategic and tactical marketing actions adopted by firms using the NATs
are expected to result in the creation of customer experience (CX). Research
studies have advanced the concept of personalization, a distinct feature of
NATs, to operate in the pathway to CX. These research findings suggest that
NATs are well-suited to help firms establish CX that can subsequently add
value to all the stakeholders involved.6
When clients receive communications and offerings that directly speak to
their needs and preferences, the NATs guarantee that they will stay involved
with the business. Developing curated offerings using AI and generative AI,
creating personalized interactions in service settings using robotics, reducing
variations in the service experience using IoT, identifying social topics impor-
tant to customers using machine learning (ML), delivering mesmerizing
experiences on metaverse that create conversations, providing functional
benefits to consumers using drones (e.g., interactivity, faster delivery times,
etc.), and fostering/building customer loyalty using blockchain are a few
examples of enhanced CX initiatives using NATs.
 11 Putting It All Together 355

Furthermore, social media interactions enable businesses to quickly assess

the value of the different ways they choose to communicate and engage
with their target audiences. In other words, consumers are vocal about
their experiences and opinions with brands and businesses, fueled by digital
communication options. When properly organized, these kinds of experi-
ences can aid businesses in building stronger stakeholder engagement (SE).
Consequently, the creation of SE benefits all parties involved in facilitating
the exchange relationship, not just businesses and consumers. The NATs are
essential in creating overall value for all stakeholders in such a situation.

Stakeholder Engagement/Benefits

In the multi-entity environment of business ecosystems, the members

involved in coordinating, facilitating, and directing the exchange process are
known as stakeholders, and the aim of the exchange process revolves around
satisfying the mutual interests and expectations of the stakeholders. Several
decades of academic research continue to investigate the role and impact of
stakeholders in the overall exchange process, with a critical research area being
stakeholder value and stakeholder engagement.7
Academic scholars and practitioners continue to be interested in the
concept of stakeholder value because value is an obvious outcome of interest
for the stakeholders (in any format of exchange). One important aspect of
shareholder value is that it is best realized through a continuous exchange
process.8 The bidirectional flow of value between the related parties (i.e.,
stakeholders) in such a process allows the parties to continuously assess the
value acquired. The relationship is frequently managed and tracked using
the value that has been realized. For the association to be fruitful and
fulfilling, stakeholders must continually assess the value that comes from their
connections.
Ecosystems and business models are changing fundamentally as a result
of NATs. Technology is still changing how businesses operate in NAT envi-
ronments, but these changes are still very much in line with the idea of
value. The benefits of NAT implementation for firms are substantial, as this
book has demonstrated. The following discussion centers on five important
stakeholders that are typically involved in a business environment: customers,
employees, channel partners, the community, and the government.
Customers. As a stakeholder group, customers share a particularly close
relationship with firms from a value standpoint. On the one hand, firms
deliver value to customers through firm offerings that are intended to satisfy
customers.9 In return, customers provide value to the firm through their
356 V. Kumar and P. Kotler

loyalty,10 their contribution to firm profits,11 and indirect engagement.12

The NATs in a NAT environment deliver newer and innovative ways for
users to modify or change their behavior. For example, IoT enables end users
to integrate devices that were previously unattainable (e.g., smart locks, ther-
mostats, etc.). Similar to this, AI enables ongoing learning of end users’ usage
patterns, which can then be applied to customize the user experience (person-
alization apps, for example). Furthermore, end users can now benefit from
improved experiences (via metaverse), and personalized communication (e.g.,
health tips from wearables, personalized learning solutions, etc.) thanks to AI,
ML’s ongoing analysis of IoT data.
Because customers share their personal information, these advantages for
the final user are made possible. In these situations, blockchain is used to
protect personal information and give users more control over who can access
it. Furthermore, by enabling end users to follow the path of products through
the supply chain, blockchain will foster greater consumer engagement and
brand trust (e.g., tracking foodborne outbreaks, detecting food counter-
feiting, etc.). Ultimately, by improving physical movement-related tasks and
providing functional support, robotics and drones improve end users’ quality
of life. End users who use these technologies continue to be drawn in by the
benefits provided by NATs.
Employees. Internal marketing has been used to address the idea that
employees are a company’s “internal customers.”13 This kind of perspec-
tive shows how important employees are to the company. Workers are
a vital component of all business sectors, performing tasks ranging from
the regular, highly standardized physical transportation of goods to special-
ized services requiring a high level of customization. Employee criticality is
most evident in service-oriented industries, such as financial consulting and
medical services, where the caliber of the service offering is secondary to the
caliber of the service personnel delivering it. The traditional view of how
employees add value to companies has changed dramatically in a NAT envi-
ronment. The implementation of NATs is frequently planned to overlap with
regular staff duties to maximize value creation through the synergistic effects
of technology and human interaction.
Studies regularly reveal that the concern of machines taking over human
jobs is not a universal threat. While machines excel in simple and repetitive
tasks, they are not suitable for tasks that require innovation and creativity,
such as customer service and content creation. As a result, technology compa-
nies are now focusing on developing robots that can adapt to a wide range
of job functions, rather than replacing humans altogether. This has led
 11 Putting It All Together 357

to collaborative efforts between robotics, drones, and humans in indus-

trial settings, where they work together in tasks like picking and packing,
ensuring employee safety, and even healthcare and surgical applications. Addi-
tionally, AI, generative AI, and ML applications are designed to enhance
employee capabilities and assist in generating insights, managing customers,
and handling knowledge management tasks. These advancements demon-
strate that machines and humans can work together to create greater value
for all stakeholders.
Channel Partners. Channel partners play a crucial role in maintaining the
operations of a company. They are designed to work in harmony with the
company to ensure that its products or services are produced, distributed,
and made available to the target audience promptly, thereby creating value
for customers. Additionally, channel partners also bring value to the company
in their unique ways, particularly in the context of the NAT environ-
ment. With the integration of NATs, companies are increasingly focusing
on integrating their supply chains to minimize resource wastage, eliminate
redundant efforts, improve overall process efficiency, and streamline the
exchange process. For example, the use of AI, generative AI, metaverse, and
ML enables channel partners to deliver products and process enhancements
that can generate valuable insights for subsequent decision-making by the
company, such as product personalization and pricing strategies. Further-
more, IoT is also utilized by many channel partners to ensure smooth
operations of routine tasks while adding value through actions like preventive
maintenance, asset management, and smart energy systems.
Community. The communities that businesses operate in are an integral
part of it. A company can operate in the middle of several communities at
once. Communities are often built around company offerings (like product
feedback, and technical support groups), consumer emotions (like love or
rage), corporate governance (like privacy and human rights), causes (like
the environment, and diversity), or a mix of the above. It is also critical to
remember that not all communities are centered in the company’s immediate
vicinity. Because of the internet’s energizing power, communities usually get
stronger thanks to the advantageous network effects it provides. Communi-
ties have a clear influence on the generation of overall value even though
they do not usually participate in the regular course of the firm’s economic
exchange.
NATs in the environment play a crucial role in helping firms minimize
their environmental impact, adapt to changing environmental conditions,
develop products and services that address the social and environmental needs
of communities, and enhance transparency in their business operations. To
358 V. Kumar and P. Kotler

achieve these objectives, firms need to closely monitor consumer sentiments

expressed through various online and offline channels, covering a wide range
of emotions from love to hate.
For instance, by leveraging AI and ML technologies, firms can analyze user
sentiments, particularly related to societal issues, and take appropriate actions
to align themselves and their offerings with the prevailing societal context.
Further, companies are using metaverse to create environments that nurture
community building by promoting inclusivity and openness. Additionally,
drones are increasingly being utilized for valuable societal purposes such as
disaster management, relief and recovery missions, and infrastructure assess-
ment. Similarly, robots are being deployed in community-oriented activities
like agriculture, healthcare, and public hygiene to contribute to the overall
welfare of the public. These initiatives highlight the significant benefits that
communities can derive from the implementation of NATs.
Government. Similar to communities, the government is an essential
component of the business environment. Due in part to the uncertainty
surrounding the predictors of firm success, determining how governments
can add value to businesses is subjective. Businesses, for example, have tradi-
tionally defined success based on several factors, including offerings (e.g.,
novel products), size (e.g., market share), resources (e.g., human capital),
strategic approach (e.g., customer-focused), and financial health (e.g., prof-
itability). In light of this, the best way to gauge the value that the government
adds to businesses is to look at the kind of business environment that it
creates.
In this sense, technological advancements are ushered in by the NAT
environment to create favorable business conditions. The use of AI, ML,
metaverse, and IoT, for example, has consequences for the environment,
energy use, and consumer privacy. As a result, governments are imposing
stricter regulations on businesses (such as the General Data Protection Regu-
lation (GDPR) in the European Union). Drones, robotics, and blockchain
also support critical administrative procedures related to smart cities, e-
governance, and collaborations between the public and private sectors.
Drones, AI, and ML are examples of NATs that help governments ensure
the welfare of the nation in times of national emergency.
The COVID-19 pandemic of late sufficiently illustrated government
attempts to use NATs to obtain information and provide relief. We were
able to recover from the pandemic thanks to several initiatives, including
the use of drones to disinfect large areas, crowd surveillance to enforce social
distancing, and the delivery of vital supplies to affected populations.14 In a
similar vein, governments are using AI and ML to help them plan future
 11 Putting It All Together 359

response measures like researching the virus, identifying illnesses, coming up

with treatment plans, and comprehending the broad effects on the public.15
These examples demonstrate how governments still gain from the use of
NATs.

Value and Social Well-being in a New-Age

Technology World
NATs, as described in the overall architecture, are now deeply embedded in
our daily lives. The value that NATs add wherever they are employed is a
distinguishing feature of their emergence. As more value is produced for all
NAT users, a critical long-term implication becomes clear: the establishment
of stakeholder well-being.16 Several marketing studies have looked at well-
being in the context of stakeholders. For example, the triple bottom line
(a concept that reflects a corporation’s economic, environmental, and social
worth) considers the well-being of all stakeholders connected with the firm.17
According to research, green actions by businesses drive not only the envi-
ronmental but also the social and economic components of sustainability
through recycling operations implemented by businesses.18 Furthermore,
the impact of corporations’ corporate social responsibility (CSR) efforts
on various stakeholders has been acknowledged as contributing to societal
well-being.19 Furthermore, the cause-related marketing concept has been
demonstrated to include societal well-being in business actions, ensuring that
commercial activity is more than just a financial venture.20
While the use of NATs is primarily a technological undertaking, it may
and does help in ways other than technology. While existing knowledge on
how NATs might contribute to the well-being of stakeholders is limited, the
preliminary evidence of NATs’ capacity to do so is both interesting (from the
aspect of advancing knowledge) and enriching (from a practical and societal
standpoint). In this regard, continuing research is looking into how enter-
prises’ use of NATs might help to ensure the well-being of stakeholders while
also discovering growth potential for the firms that utilize them.21
So far, the practical applications of NATs in numerous sectors of personal
and economic actions have proven to be beneficial and valuable. Firms are
always discovering fresh ways to use NATs to execute various corporate activ-
ities. These solutions generate “value in use,” which means that the operations
done utilizing NATs generate value through cost savings, efficiency, and
better resource usage. NATs assist in how we do things when we do things,
360 V. Kumar and P. Kotler

and how we get things done in our personal lives. The most significant advan-
tage appears to be the time saved in executing each task. The value received
from NATs varies greatly in our social life. This is mostly determined by
the functional area of the application. That is, the value generated differs
depending on whether NAT is used for nature protection, community relief,
public governance, and so on. As a result, it is becoming increasingly clear
that NATs can provide not only practical benefits to our everyday actions but
also provide overall value and well-being.
One key idea that emerges from the book is the notion that technology
serves as a powerful force for bringing people together. Throughout the
various chapters, the discussion provides ample evidence to support this idea.
As technology becomes more integrated into our lives, it permeates every
aspect and becomes a permanent fixture. This permanence leads to repeated
use and action, ultimately contributing to the creation of value and well-
being for all stakeholders involved. Additionally, the widespread adoption of
technology across different markets and geographical locations fosters collec-
tive growth and fosters a sense of shared value creation. By empowering both
businesses and governments, technology has the potential to bridge gaps and
unite people and resources, ultimately promoting harmony and purposeful
action. In this context, the use of NATs can play a crucial role in unifying
and enabling progress, rather than dividing and conquering. We hope that
this book serves as a step towards achieving this goal.

Key Terms and Related Conceptualizations

Data sanctity Refers to how “clean” the information being

recorded is in the data
Data-driven insights Refers to the potential outcomes that businesses can
achieve using “clean” data

Notes and References

1. Kumar, V. (2021), Intelligent marketing: Employing new age technologies.
Sage Publications.
2. To name a few, studies have found that CE: (a) functions as a critical
success factor (Kumar, V., & Pansari, A. (2016), “Competitive advan-
tage through engagement,” Journal of Marketing Research, 53(4), 497–
514; Verhoef, P. C., Reinartz, W. J., & Krafft, M. (2010), “Customer
engagement as a new perspective in customer management,” Journal
of Service Research, 13(3), 247–252); (b) creates a value for firms
 11 Putting It All Together 361

(Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T., & Till-
manns, S. (2010), “Undervalued or overvalued customers: capturing
total customer engagement value,” Journal of Service Research, 13(3),
297–310); (c) informs firms about consumer behaviors (Van Doorn,
J., Lemon, K. N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P.
C. (2010), “Customer engagement behavior: Theoretical foundations
and research directions,” Journal of Service Research, 13(3), 253–266);
(d) supports the creation of interactive, co-creative customer experi-
ences (Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011),
“Customer engagement: Conceptual domain, fundamental proposi-
tions, and implications for research,” Journal of Service Research, 14(3),
252–271); and (e) manifests from the creation of positive service expe-
riences (Kumar, V., & Rajan, B. (2017), “What’s in it for me? The
creation and destruction of value for firms from stakeholders,” Journal
of Creating Value, 3(2), 142–156).
3. Kumar, V. (2021), Intelligent marketing: Employing new age technologies.
Sage Publications.
4. Kumar, V., Rajan, B., Gupta, S., & Dalla Pozza, I. (2019), “Customer
engagement in service,” Journal of the Academy of Marketing Science,
47(1), 138–160.
5. Fernandez, A. (2020), “The Three Drivers of Food Traceability
Changes in 2020,” Food Safety Magazine, June 2, [accessed from
https://www.foodsafetymagazine.com/enewsletter/the-three-drivers-
of-food-traceability-changes-in-2020/].
6. Personalization creates a connection between consumers and businesses
(Murthi B. P. S., & Sarkar, S. (2003), “The Role of the Management
Sciences in Research on Personalization,” Management Science, 49(10),
1344–1362; Vesanen, J., & Raulas, M. (2006), “Building bridges for
personalization—a process model for marketing,” Journal of Interactive
Marketing, 20(1), 1–16), and this connection is likely to strengthen
the relationship that develops as a result (Simonson, I. (2005), “Deter-
minants of customers’ responses to customized offers: Conceptual
framework and research propositions,” Journal of Marketing, 69(1),
32–45). Furthermore, positive firm–customer relationships influence
customer engagement behaviors (Van Doorn, J., Lemon, K. N., Mittal,
V., Nass, S., Pick, D., Pirner, P., & Verhoef, P. C. (2010), “Customer
engagement behavior: Theoretical foundations and research direc-
tions,” Journal of Service Research, 13(3), 253–266), satisfied customer
relationships with emotional bonding result in an enhanced customer
experience (Pansari, A., & Kumar, V. (2017), “Customer engagement:
362 V. Kumar and P. Kotler

the construct, antecedents, and consequences,” Journal of the Academy

of Marketing Science, 1–18), and a personalized experience marketing
approach, when carried out through the strategy of curation and the AI
tool, can yield better marketing results in a NAT environment (Kumar,
V., Rajan, B., Gupta, S., & Dalla Pozza, I. (2019), “Customer engage-
ment in service,” Journal of the Academy of Marketing Science, 47(1),
138–160).
7. For example, stakeholder value is defined as the difference between the
accrued benefits (tangible and intangible) and the associated costs that
firms and individuals/organizations realize in a commercial exchange
process (Kumar, V., & Rajan, B. (2017), “What’s in it for me?
The creation and destruction of value for firms from stakeholders,”
Journal of Creating Value, 3(2), 142–156). In a multi-stakeholder
setting, stakeholder engagement is defined as the attitude, behavior, the
level of connectedness (1) among customers, (2) between customers
and employees, and (3) of customers and employees within a firm
(Kumar, V., & Pansari, A. (2016), “Competitive advantage through
engagement,” Journal of Marketing Research, 53(4), 497–514).
8. Kumar, V., & Rajan, B. (2017), “What’s in it for me? The creation and
destruction of value for firms from stakeholders,” Journal of Creating
Value, 3(2), 142–156.
9. Anderson, E. W. (1998), “Customer satisfaction and word of mouth,”
Journal of Service Research, 1(1), 5–17.
10. Dowling, G. R., & Uncles, M. (1997), “Do customer loyalty programs
really work?” Sloan Management Review, 38(4), 71–82; Oliver, R. L.
(1999), “Whence Consumer Loyalty?” The Journal of Marketing, 63,
33–44.
11. Reinartz, W. J., & Kumar, V. (2003), “The impact of customer rela-
tionship characteristics on profitable lifetime duration,” Journal of
Marketing, 67 (1), 77–99; Reinartz, W. J., & Kumar, V. (2000), “On
the profitability of long-life customers in a noncontractual setting:
An empirical investigation and implications for marketing,” Journal of
Marketing, 64 (4), 17–35.
12. Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T., & Till-
manns, S. (2010), “Undervalued or overvalued customers: capturing
total customer engagement value,” Journal of Service Research, 13(3),
297–310.
13. Berry, L. L. (1981), “The Employee as Customer,” Journal of Retail
Banking, 3(1), 33–40; Grönroos, C. (1982), “An applied service
marketing theory,” European Journal of Marketing, 16(7), 30–41.
 11 Putting It All Together 363

14. Banker, S. (2020), “Is the Future of Drones Now?” Forbes, June 11,
[accessed from https://www.forbes.com/sites/stevebanker/2020/06/11/
is-the-future-of-drones-now/#57855e7e3284]; Lewis, N. (2020), “A
tech company engineered drones to deliver vital COVID-19 medical
supplies to rural Ghana and Rwanda in minutes,” Business Insider, May
12, [accessed from https://www.businessinsider.com/zipline-drone-cor
onavirus-supplies-africa-rwanda-ghana-2020-5].
15. Leong, B., & Jordan, S. (2020), “Artificial Intelligence and the
COVID-19 Pandemic,” Future of Privacy Forum, May 7, [accessed
from https://fpf.org/2020/05/07/artificial-intelligence-and-the-covid-
19-pandemic/].
16. Kumar, V. (2021), Intelligent marketing: Employing new age technologies.
Sage Publications.
17. Elkington, J. (1994), “Towards the sustainable corporation: Win-
win-win business strategies for sustainable development,” California
Management Review, 36(2), 90–100.
18. Crittenden, V. L., Crittenden, W. F., Ferrell, L. K., Ferrell, O. C., &
Pinney, C. C. (2011), “Market-oriented sustainability: a conceptual
framework and propositions,” Journal of the Academy of Marketing
Science, 39(1), 71–85.
19. Peloza, J., & Shang, J. (2011), “How can corporate social responsibility
activities create value for stakeholders? A systematic review,” Journal of
the Academy of Marketing Science, 39(1), 117–135.
20. Ballings, M., McCullough, H., & Bharadwaj, N. (2018), “Cause
marketing and customer profitability,” Journal of the Academy of
Marketing Science, 46 (2), 234–251; Kumar, V. (2020), Global impli-
cations of cause-related loyalty marketing. International Marketing
Review, 37(4), 747–772.
21. Kumar, V., & Ramachandran, D. (2020), “Developing a firm’s growth
approaches in a new-age technology environment to enhance stake-
holder wellbeing,” working paper, Georgia State University, GA.
 Index

A Alexa 12, 31, 32, 34, 35, 71, 110,

ABB 190 131, 211, 279
Accessibility 96, 161–163, 216, 261, Algorithms (develop, comprehend,
272, 315 evaluate) 103
Accountability 8, 307, 310, 328 Alibaba 315, 317
Adaptability 9, 120, 151, 185, 226, Allstate 283
232, 273 Aloft hotels 219
Adidas 45 Amaggi 117, 118
Adobe’s Adobe Cloak 128 Amazon 12, 31, 34, 35, 53, 81, 87,
ADT 190 89, 110, 119–121, 123, 125,
126, 196, 228, 229, 232, 267,
Advanced capabilities 255
278, 280, 282, 285
Aerial photography 258, 263, 264
Amazon Bedrock 89
Aerodyne 270
Amazon Echo 219
Africarare 150
Amazon Fresh 121
Agile marketing 13, 14, 21, 25, 42, Amazon Go stores 196, 197
79, 117, 151, 185, 226, 273, Amazon Managed Blockchain 12
314 Amazon MTurk 131
Agrimor 270 Amazon Web Services (AWS) 12,
Aibo robotic dog 229 270
AI-powered chatbots 3, 31, 40, 73 Ambient assisted living (AAL) 179,
AI-powered robots 222 198, 350
Airbnb 119 Ambiotex 191
Aircards 151 American Express 120
Aldi 314 Amgen 304

© The Editor(s) (if applicable) and The Author(s), under exclusive 365
license to Springer Nature Switzerland AG 2024
V. Kumar and P. Kotler, Transformative Marketing, Palgrave Executive Essentials,
https://doi.org/10.1007/978-3-031-59637-7
366 Index

AMP Clarity 223 Autonomous Aircraft Inspection

AMP Robotics 223 (AAI) program 272
An Post 197 Autonomous mobile robots 228
Apple 35, 37, 110, 121, 219, 273, Autonomous systems 259, 260
274 Auto-tagging 110
Apple Watch 37, 121, 177, 191, 192 AVA 156
Aquabot 219 Avatar realism 161
Arcade City 311 Aworker 323
Artificial intelligence (AI) vii, 3–5, AWS Robomaker 232
15, 16, 32, 39, 40, 43, 46, 54, Azure AI Health Bot by Microsoft
55 74
Artificial neural networks (ANNs) Azure cloud 183, 304
33, 55, 104
ASOS 115
B
Buy the Look 115
Backpropagation 104
Asset traceability 318
Balenciaga 153
Asset tracking and management 255
Barcelona 194, 275
Atea 315
Bard 31, 32, 65, 72, 73
Atlanta Braves 142 Basic Attention Token (BAT) 320
Augmented marketing 13, 14, 21, Bayer 74, 304
22, 25, 41, 78, 117, 151, 184, Bayesian networks 4
225, 272, 314 Bellabeat–Leaf Urban 38
Augmented reality (AR) 3, 5, 9, 12, Bestic 211
19, 20, 38, 78, 90, 124, 141, Bias 3, 6, 162, 223
142, 144, 151, 155, 156, 160, Bidirectional flow of value 355
167, 225, 239, 349 Biomechanical research 213
Augmenting capabilities 262 Biryani By Kilo 279
August 186 Bitcoin 142, 300–302, 305, 332
Aura Blockchain Consortium 312, BitCongress 314
313 BitProperty 324
Authenticity 301, 302, 307, BizRate 230
311–313, 316, 319, 321, 323, Blockchain 3, 8, 9, 11–13, 15–17,
324, 326, 351 20, 23, 141, 145–147, 157,
Autodesk 128 159, 164, 299–327, 329–333,
Automated customer interaction 31 336, 338, 341, 342, 345,
Automatic systems 259 349–354, 356, 358
Automation 4, 5, 32, 71, 79, 80, 88, BloombergGPT 89
119, 124, 128–131, 174, 179, BMW 304
180, 185, 192, 203, 212, 222, Boehringer Ingelheim 191
224, 229, 232, 273, 275, 279, Boeing 46, 272, 273
308, 310, 326, 333, 348, 350, Bon Viv Spiked Seltzer 151
352 Boosto 329
Automation technologies 212, 222 Bossa Nova 219
 Index 367

Brand experiences 3, 184, 222, 225, Carmax 44

354 Carnegie learning 36
Brand interactions 68, 184 Carrefour 315, 317
Brand loyalty 19, 87, 159, 183 Cartier 312
Brand outcomes 190 Cathay Pacific 320
Brand positioning 153 Celebrity Beyond 158
Brand trust 356 Celebrity Cruises 158
Bransys 190 Cellr 321
Brave browser 320 Center for Research on the
Brightspace insights 35 Epidemiology of Disasters
Broad Branch Market 231 (CRED) 268
Browsing behavior 12, 75, 85, 86 Change business methods 152
Budapest 275 Changing user demographics 280
Buddy 219 ChatGPT 31, 32, 65, 68, 72, 73, 92
Burberry 126 Chick-fil-A 125
Burger King 187–189 Chipotle 142
Business processes 9, 38, 128, 172, Circulor 312
196, 222, 234, 304, 352
Citymesh 271
Closed-loop supply chain 197
Coca-Cola 75, 76, 159, 285
C
Coca-Cola’s GAI initiative 75
Café X 211
Codi 36
California Farm Bureau Federation
(CFBF) 266 Collaboration 6, 9, 84, 108, 141,
Capabilities 2, 4, 6, 9, 14, 19, 20, 145, 146, 152, 154, 164, 185,
23–25, 27, 36, 40, 43–46, 54, 187, 213, 217, 224, 226, 227,
56, 74, 82, 87, 88, 90, 96, 270, 273, 321, 348, 358
108–110, 116–118, 120, Collaborative filtering 47
123–127, 129, 131, 134, 154, Community building 349
156, 174, 175, 180–182, Community relief 360
185–190, 193, 198, 213, 219, Competition 3, 37, 70, 83, 85, 88,
228, 229, 232, 233, 235, 236, 117, 122, 148, 157, 163, 230,
239, 241, 256, 258, 261, 262, 235, 276
268, 272, 274, 276, 277, 279, Competitive advantage 29, 38, 46,
281, 282, 285, 286, 295, 310, 83, 187, 192, 228, 233, 240,
316, 317, 322, 323, 325, 346, 275, 276, 295, 309, 353
351–353, 357 Computational methods 5, 10, 103,
dynamic 24, 25, 187, 228, 240 105
static 24, 26 Computational resources 161
Capability development 187, 277, Computer intelligence 20
281, 295 Confidentiality 307
Capgemini 190 Connected environments 172
Cardano 302 Consensus protocol 324, 332
Carl’s Jr. 86 Consumer acceptance 256
368 Index

Consumer behavior viii, 2, 19, 38, 87, 100, 101, 114, 157, 160,
42, 75, 76, 78, 122, 175, 270, 171, 175, 181, 183, 190, 192,
273, 361 198, 206, 226, 232, 234,
Consumer well-being 178, 198 276–278, 282–284, 296, 346,
Content delivery 348 353, 354, 361
Contextually relevant content 41, Customer feedback 40, 48, 81, 82,
70, 181 185, 188, 233
Contextual marketing 13, 14, 20, Customer heterogeneity 124
22, 25, 40, 77, 116, 150, 183, Customer influence effect (CIE) 328
224, 271, 312 Customer influence value (CIV) 328
Continuous learning 4, 5, 32, 308, Customer journey 2, 14, 20, 25, 29,
323, 346 68, 123, 310
CopyAI 47 Customer needs 14, 24, 31, 40,
Corporate agility 22 44–47, 67, 81, 82, 84, 117,
Cortana 31, 32, 38, 131 119, 128, 153, 172, 181, 186,
Crop health 266 188, 225, 227, 256, 275, 276,
Cross-functional teams 21, 25, 42, 300, 316, 323
79, 84 Customer-oriented marketing 1, 11
Crurated 313 Customer profiles 32, 47
Cryptocurrency 148, 300, 301, 307, Customer relationships 10, 47, 51,
310, 322, 334, 352 52, 124, 237, 361
Crypto loans 299 Customer response 32, 122, 126
Crypto-spatial coordinate system Customer satisfaction 44, 47, 82,
320 87, 114, 115, 190, 224, 285
Cubelets 218 Customer segmentation 75, 126,
CultBeauty 322 349
Curation 48, 49, 124, 238, 240, Customer sentiments 47, 52, 76, 81
253, 350, 362 Customer service 3, 6, 10, 52, 73,
Customer care and back-office 75, 76, 80, 131, 219, 235,
support 66 236, 247, 276, 352, 356
Customer-centric marketing Customer service transformation 348
strategies 23 Customer value 206, 234, 278
Customer churn 127 Customization 47, 68, 96, 120, 149,
Customer delight 128 158, 229, 232, 356
Customer engagement (CE) 14, 23, CVS 172, 268
32, 47–49, 51, 87, 88, 97, Cybderyne’s Hybrid Assisted Limbs
113, 122, 125, 130, 142, 148, 219
152, 177, 181, 190–192, 206, Cyberbullying and harassment 162
222, 226, 232, 233, 235, 253,
256, 278–280, 296, 300, 310,
321, 322, 337, 346, 352, 360, D
361 D:verse 313
Customer experiences (CX) 6, 10, Dall-E 32, 68, 71–73, 82
12, 14, 19, 38, 40, 41, 75, 85, Dapper Labs 322
 Index 369

Dash 230 Digital currency 300, 301

Dash & Dot 218 Digitalization 11–13, 22
Data analysis 29, 34, 110, 223 Digital landscape 19, 88
Data augmentation 70, 104, 106 Digital literacy 163
Data authentication 304 Digital strategies 14, 31, 48, 67, 88,
Data-based analytics 4 125, 126, 159, 160, 172, 191,
Data-driven insights 76, 84, 278, 233, 234, 256, 280, 281, 300,
351, 360 322–324
Data-driven marketing 3, 13, 14, Digital trade finance transactions
21, 25, 39, 51, 75, 114, 148, 299
181, 182, 223, 269, 310 Digital twins 6, 46, 142, 147
Data ecosystem 21, 22, 120 Digital world 4, 5, 10, 141, 145,
Data granularity 174, 176 151, 180
Data management 6, 24, 109, 304, Direct firm-customer interactions
310, 316, 317 318
Data mining 104–106, 132 Disaster response 256, 268, 288
Data-oriented technology 174 Discreet Variational Auto-Encode
Data processing 161 (dVAE) 72
Data sanctity 351, 360 Discrimination 162
Data science techniques 116 Disney 72, 125, 142
Data variance 107 Disposable income 227
DeBeers 320 Disruption 174, 300, 345
Decentraland 146, 148, 154, 156 Disruptive technology 83
Decentralized 11, 21, 25, 42, 79, Distributed ledger technology 299,
142, 145, 148, 152, 156, 159, 305, 350
163, 302, 309, 310, 323, 324, Dolphin 219
332, 350 Domino’s Pizza 282
Decision trees 105, 107 DoorDash 279
Deep Brew 41 Drife 311
Deep learning 4, 15, 31–34, 47, 65, Driving customer engagement 14,
72, 77, 94, 104, 110, 120, 31, 47, 67, 87, 124, 158, 172,
130, 223 190, 232, 256, 278, 321
Degree of autonomy 214, 240, 259 Drone adoption 262, 287
Delivery 9, 53, 59, 122, 128, 151, Drone delivery 267, 275, 276, 279,
161, 190, 213, 215, 227, 228, 280, 285, 294
232, 256, 260, 275, 276, Drone-in-a-Box (DiaB) 271
278–280, 294, 311, 318, 350, Drones vii, viii, 3, 8, 9, 11–13, 15,
354, 358 19, 20, 47, 255–285, 287,
Demand forecasting 120, 128, 129 288, 290, 292–294, 298, 345,
Demand Side Platforms (DSPs) 327 354, 356–358
DHL 188, 228, 267, 278, 285 DroneUp 269
Diageo 188 DRONOS software 270
Diesel 313 Dynamic capabilities 24, 187, 228
Digicash 302 Dynamic customer experiences 171
370 Index

Dynamic pricing 46, 271, 349 F

Facebook 34, 110, 142, 192, 271
Facial recognition 34, 110
E Fairness 307
eBay 120, 231 Farfetch 89
Ecco 121 Fasal 185
Echo 34, 229 Fashion Innovation Agency (FIA) 87
Ecosystem-based innovation 299 Federal Aviation Administration
Effective business models 187 (FAA) 263, 267, 270, 284
Efficiency vii, 8, 9, 11, 22, 23, 26, FICO 119, 126
40, 42, 76, 79, 80, 84, 85, 89, Fifth age of virtual worlds 142
117, 126, 129, 130, 175, 180, Financial services 29, 30, 66, 127,
182, 201, 216, 218, 222, 304
224–226, 228, 229, 237, 256, Firm capabilities 13, 14, 31, 54, 67,
261, 274, 278, 306, 310, 315, 82, 120, 154, 172, 187, 188,
319, 320, 323, 325–327, 228, 256, 276, 300, 317, 322,
351–354, 359 351
Effie 219 Firm-customer interaction 53
E-gold 302 Firm response to market changes
Ekso Bionic 219 187
Ekso NR 219 First-mile delivery solution 267
Elisa 232 Fitbit 37, 177, 191, 192
ELIZA–chatbot 67 Flexible automated assembly lines
ElliQ 229 213
Emergency Events Database Flirtey 285
(EM-DAT) 268 Fluid AI 131
Emergency response innovation 271 FOAM 320
Employee criticality 356 FoldiMate 219
Employee diversity 83 Follow My Vote 314
Enhanced customer experience 145, Ford 317
283, 346, 361 Forecasting 32, 34, 40, 120, 129,
Enhanced security 310 149, 349
Enterprise drones 255 Fortnite 142, 143, 146, 154
Environmental consciousness 227 Fossil–Q Tailor 38
Ethereum 148, 156, 302, 305 FreshAI by Wendy’s 86
Ethical sourcing 304 Friday 186
ETS 111 Functional benefits 193, 325, 354
Eufy 219 Function-oriented technology 216,
Everledger 317 229, 261, 277
Evo 174, 179 FURO 230
Evolutionary algorithms 4 Future-oriented technologies 238
 Index 371

G H
Gaming industry 141 Hamburg 275
Gap 20, 84, 142, 281, 322, 360 Hamburg Port Authority 174
Garmin 37 Hannah 159
GE 188, 285 Hanwa Life 159
Genentech 304 Hardee’s 86
General Data Protection Regulation HashCash 302
(GDPR) 7, 9, 358 Haystack 131
Generating new content 65 Healthcare 1, 22, 30, 36, 38, 40–42,
Generative artificial intelligence 66, 73, 74, 109, 134, 173,
(GAI) 15, 65–71, 73–95, 97, 175, 177, 178, 191, 199, 213,
348 215, 217, 218, 231, 233, 236,
Generative design algorithms 46 237, 302, 319, 320, 350, 357,
Genetic algorithms 130 358
Gen Z 153, 167 Heathrow Airport 189, 236, 283,
Geo-blockchain 320 318
Geofencing 186, 187, 189 HelloFresh 122
Georgia State University 35 Heterogeneity 124, 173
Geospatial information 275 High-quality cameras 263, 267
Giant Eagle 231 Hilton’s Connie 124
Gilead 304 Hitachi 110, 190
Gladwell Gecko 219 HOBOT 219
GlaxoSmithKline 191 Honeywell 190
Global trade 319 Horizon robotics 226
Google Hubert.ai 36
Gmail 111, 125 Human-centric marketing 2
Search 125 Human intervention 13, 103, 106,
Search Generative Experience 44 120, 179, 180, 216, 231, 234,
Google’s Duplex 35 261, 303
Google ads 271 Humanitarian relief efforts 350
Google Assistant 34, 35 Humanizing customer experience 41
Google Cloud Robotics Platform Humanoid robots 213, 221, 253
232 HX2 230
Google Glass 37 Hybrid systems 258, 286
Google Home 178, 219, 229 Hyper-connected digital universe
Google Maps 111 144
GPS units 267 Hyper-localized offerings 189
Grammarly 48, 111
Graphic visualization 105
Greater data security 318 I
Greenfence 315 IBM Watson 31, 48, 79, 139, 239
Gucci 142, 153, 154, 156 Ikea 155, 156
iLife 219
Illegal deforestation 282
372 Index

Image classification 104 Intelligence amplification (IA) 117,

Immersive experience 3, 12, 15, 19, 132
145, 148, 151, 153, 162, 285 Intelligent advertisements 348
Immersive virtual environment 144 Intelligent automation 222, 223,
Immutable 11, 15, 302, 303, 324, 310
330 Intelligent driving technologies 226
Immutable spatial context 320 Interaction orientation approach 190
Improve agility 274 Interactive experience 20, 78, 156,
Inclusivity 162, 358 181
Industrial automation 172, 179, Interactive robots 236, 237
180, 203, 215, 240 Interactivity 5, 158, 236, 279, 354
Industrial IoT (IIoT) 180, 198, 353 Interconnectedness vii, viii, 10, 144
Industrial revolution 1, 179, 180, Interconnected virtual realms 141,
198 164
Industry 4.0 180, 198, 350 Internet connectivity 266
Inference 7, 34, 108, 309 Internet of Things (IoT) viii, 2, 3,
Influencer payment system 329 8–10, 12, 13, 15, 17, 20, 22,
23, 41, 43, 47, 171–176,
Influencers 51, 52, 157, 264, 279,
179–201, 216, 317, 318, 345,
321, 328–330
349, 352–354, 356–358
Information asymmetry 316
Intuitive service delivery 346
Information exchange 176, 208
iPhone X–facial recognition 110
Information fatigue 280
iRobot 219, 229
Information infrastructure 176
Istanbul Airport 190
Information storage and retrieval
104
Infrared mapping 266 J
Innovation-friendly regulatory JAMOR 219
environments 175 Jasper 47, 71
Insight generation 192 Jet 53
Insights AI 85 Jet Blue 76
Instantaneous 3, 232, 233, 303 JPM Coin 304
Institute of Electrical and Electronics JP Morgan Chase 304
Engineering (IEEE) 180 Julia 219
Institutional performance 68 June 17
In-store navigation 215, 278
Instreamatic–audio marketing
platform 77 K
Integrated strategy for stakeholder Kanega 191
engagement 346 Kansas City Chiefs 123
Integrity 24, 182, 307, 308, 310, Kashiwa-no-ha, Japan 194, 196
311, 316, 324 Keeko robot 53
Intel 154, 285 KelaHealth 224
Intel Drone Show 285 Kelkoo 231
 Index 373

Kenneth Cole 189 Logistic regression 107

K-fold cross-validation, LogSentinel 317
leave-one-out cross-validation London Heathrow Airport 189, 283
113 Loomo 211
Kiki 220 Lowe’s 215, 219
Kiosk robot 230 LoweBot 215, 236
K-nearest neighbors 107 Luna Lights 191
Knowledge-driven strategic business LVMH 312, 323
decisions 106 Lyft 111
Knowledge management 309, 357 Lyrebird 128
KodakCoin 323
KodakOne 323
Kontakt 196 M
Kraft Foods 43 Machine learning capabilities 267
Kraft Heinz 43, 129 Machine learning (ML) vii, viii, 3–7,
KrisFlyer 322 10, 15, 25, 29, 33, 40, 44, 67,
KrisPay 322 70, 73, 103, 104, 110–112,
Kroger 172 114–117, 130, 132, 225, 267,
345, 349, 354
Machine-to-human connectivity 176
L Machine-to-human interaction
L’Oréal 48 capabilities 125
L’Oreal Modiface App 153 Machine-to-machine connectivity
Labor-saving technology 266 176
Large language models for Dialogue Machine vision-enabled robot 213
Applications (LaMDA) 72 Macy’s On Call 124
Large language models (LLM) 44, Major League Baseball 189
72, 73 MANA 148
Last-mile delivery solution 267 Mapbox 184
Las Vegas, USA 194, 195 Market expansion 20
Latency 161, 233, 241 Marketing 3.0 2
Lead customization 126, 349 Marketing 4.0 2
Legal Robot 131 Marketing 5.0 2, 13–15, 20–22, 25,
Lego WeDo 218 38, 75, 103, 114, 142, 145,
Leka 211, 218 148, 181, 212, 222, 223, 269,
Lenddo 131 310, 346, 351, 353
Lenskart 114, 115 Marketing element customization
Levi Strauss 83 126, 349
Lexical ambiguity 33 Marketing mix 14, 31, 46, 67, 83,
Liberty Mutual 283 86, 121, 122, 132, 154, 155,
Lighthouse 211 158, 172, 188, 229, 256, 277,
Lin by Seedtag 77 278, 300, 318, 319
Litecoin 302 Marketing strategy 46, 48, 53, 83,
Liv 34, 131 90, 172, 277
374 Index

Market trends 84, 117, 270, 352 Moro 219

Markov chains 67 Morpheus 122
Mars 93 Multi-dimensional 178, 198
Mass, segment-level and Multirotor drones 258, 260, 286
individual-level personalization Multi-sensory solutions 128
121 Mystore-E 124, 239
McCann, D. 48, 108
McCormick, Foods 48, 239
McDonald’s 86, 116, 142, 189 N
Meal-time assistance 211 Nala Robotics 225, 226
Mediachain 306 Nao 211, 218, 230
Medical robot 230 NASA 280
MediLedger 304 Natural language processing (NLP)
MedRec 324 4, 15, 29, 31–33, 48, 56, 72,
Mercedes-Benz 46, 312 73, 90, 111, 113, 118, 130
Merchandising and advertising NBA collectible insights 322
platforms 172 Need for authenticity 227
Meta 154, 157 Nespresso 320
Meta (Facebook) Ads 142 Nest 34, 131, 191
Meta horizon worlds 154, 159 Nestle 53, 89, 121, 171
Metaverse viii, 3, 10, 19, 20, 141, Netflix 24, 25, 110, 123, 125, 128,
142, 144, 145, 147–165, 129
167–170, 299, 345, 349, 354, Network of sensors 10
356–358 Neural networks 4, 31–33, 55, 65,
Mezi 34, 131 67, 72, 89, 94, 103–105, 107,
Micro-electric-mechanic sensors 110, 154, 221
(MEM) 36, 55 New product development 353
Micropayments 310 New product ideation, generation,
Microprocessor-controlled industrial delivery 84
robot 213 New York Interactive Ad Exchange
Microsoft 37, 43, 46, 74, 93, 142, (NYIAX) 327
175, 182, 183, 201, 232, 304 New York Power Authority (NYPA)
Microsoft HoloLens 37 284
Midjourney by Midjourney Inc. 65 NexTag 230
Milan 275 NextMeet 152
Miller Lite 321 Nike 45, 84, 142, 155, 157, 191,
Minecraft 154 192
Mitsui Chemicals, Inc. 79 Nike Swoosh 157
Mobility 9, 163, 173, 215, 217 Nivea 189
Model transparency, traceability 310 Nivea Sun Kids 189
Moley 219 NLP capabilities 77, 124
Mondelez 89, 91 Non-fungible tokens (NFTs) 142,
Monegraph 324 303, 321, 330
Monetization 163, 310, 353 Norwegian Seafood Trust 315
 Index 375

Nvidia Corporation 142 Personalization 2, 5, 10, 39, 47, 49,

52, 53, 68, 75, 88, 90, 91,
115, 121–124, 132, 218, 361
O Personalization elements 234
Ogilvy 53 Personalized customer actions 29
Ogilvy Paris 88 Personalized customer engagement
Oklahoma Gas and Electric 3, 49
(OG&E) 284 Personalized customer interaction 29
Olivia 34, 131 Personalized digital shopping
Omnichannel engagement 90 experiences 148
Omnichannel models 122, 190 Personalized offerings 6, 23, 49,
Open Web Application Security 121, 234
Project (OWASP) 308 Personal transporter 211
Operational efficiency 86 Pfizer 304
Optimize harvesting process 273 Phrasee 89, 100
Optimizing customer engagement Pillar Learning 36
behaviors 148 Pillo 211
Optimizing operations 348
Pizzaiola 225
Optimus 221, 222
Playchess.com 117
Oracle 116, 188
Pokémon Go 142, 143
Order management, fulfillment,
Poncho 128
returns 121
Organizational efficiencies 353 Popeyes 86
Otto 120, 121 Porsche 320
Oura Rings 38 Pounce 35
Prada Group 312
Pragmatic ambiguity 33
P Predicting customer behavior 82,
Padova, Italy 194, 195 114
Pandora 34, 110, 131 Prediction 5, 10, 33, 34, 36, 38, 52,
Panera Bread 86 71, 103, 104, 108, 112, 113,
Patagonia 125 116, 117, 122, 124, 128, 129,
PathAI 135 132, 185, 222, 224, 270, 299,
Pattern recognition 6, 108 308
Payload 257, 258, 260, 261, 286 Predictive analytics 5, 22, 25, 32,
Payment frauds 112 40, 108, 110, 115, 122, 149,
PayPal 111, 112 182, 224, 271, 309
Pay-per-click advertisements 48 Predictive marketing 13, 14, 20–22,
Peer-to-peer network 299 25, 39, 76, 115, 149, 182,
Pepper 218, 219, 232 224, 270, 311
PepsiCo 91, 171, 326, 327 Pricerunner 231
Pepsi Super Bowl LIII Halftime Show Pricing trends, adjustments 46
285 Prime Air 282
Perceptive managerial judgment 108 PrimeAir packages 12
376 Index

Privacy 3, 5, 7–9, 37, 77, 82, 92, R

162, 163, 169, 171, 267, 282, Radio Frequency Identification
283, 300, 306, 309, 325, 333, (RFID) 172, 173, 176, 184,
357, 358 197, 321
Process efficiency 357 Ralph Lauren–Fortnite Item Shop
Process improvements 352 154
Procter & Gamble (P&G) 84, 182, Rammas by the Dubai Electricity
183 and Water Authority 87
Product and service development 66 ReCheck 317
Product curation 44 Recommendation engines 87, 110,
Product delivery 49 119
Product development 41, 46, 74, 83, Reconnaissance 256, 260
84, 129, 188, 284, 348, 352, Red Bull 172, 285
353 Regulations 3, 6, 7, 9, 164, 283,
Product-driven marketing 1 311, 358
Regulatory support 12, 256
Productivity 10, 24, 25, 38, 43, 89,
Reinforcement learning 4, 39, 107,
96, 117, 118, 175, 180, 218,
113, 132
227, 234, 270, 278, 348, 352
Renault 317
Product management 354
Repeatability 173
Product personalization 122, 357
Resource allocation 270
Product segments 189
Resource-based view (RBV) 23, 26,
Programmatic advertising (PA) 326, 228
327, 330 Resource configuration 228, 229
Propy 304 Resource conservation 349
Proximity sensor 216 Retargeting 49
Public governance 360 Returnable transport packaging
Public infrastructure 256 (RTP) 196
Purchase history 12, 32, 41, 46, 75, Revolutionize customer experiences
85, 86, 114, 186 152, 153
ReWalk’s Exo-Suit 219
Ria 2.0 by Healthifyme 239
Ring 190
Q Ringly–Aries smart ring 38
QTrobot 218 Ripple 302, 305, 324
Qualcomm Technologies 184 RiskBlock 324
Quality control and testing 84 Risk identification and mitigation
Querium Corporation, Stepwise 36 267, 283
Quicker contract processing 318 RizzGPT 78
QuillBot 47, 71 Roar, Volvo’s robotic refuse collector
Quotient Health 135 230
Roblox 146, 149, 154
Robomow 219
Robot butlers 219
 Index 377

Robotic capabilities 213, 221, 235 Sensory perception 90

Robotic process automation (RPA) Sentiment 40, 95, 113, 337, 358
216, 222, 231, 234, 240, 243, Sentiment analysis 113
257, 258, 261, 286 Sephora 186
Robotics vii, 13, 19, 31, 211–214, Service operations 29, 30, 66
216, 219, 222–236, 238, 240, Service quality improvement 229,
241, 243, 245, 247, 252, 277, 234, 353
310, 350, 352–354, 356–358 Service robots 11, 17, 215–220,
Robotics powered solutions 234 240, 253
Robotic surgical systems 224 Shipment visibility 319
Robots 3, 8, 9, 11–13, 15–17, 20, ShopBot 230, 231
47, 72, 124, 128, 132, 211, Shopify 109, 134, 146, 156
213, 215–222, 224, 225, Simulation 35, 70, 154, 232
229–232, 236, 238, 240, 247 Singapore Airlines 322
Roomba 211, 219, 229 Siri 16, 31, 32, 34, 35, 110, 131,
Root 218 219
RTL Deutschland 91 Slack 128
Rule induction and refinement 105 Slice Factory 225, 226
Smart bottles 188
Smart cities 2, 15, 172, 175, 176,
S 178, 194, 195, 208, 349, 358
Sainsbury’s 314 Smart contracts 303, 309, 310, 316,
Salesforce Einstein Analytics 39 326, 329, 352
Sales intent 49 Smart home video surveillance
Sales strategy 49 system 211
Samsung 37 Smart screens 171
Samsung Galaxy Fit 177 Smart transportation options 129
SAP 138, 188 Social and emotional reasoning 90
SavorEat 232 Social connectedness 227
Schnucks Markets 231 Social media engagement 12
Search engine optimization 48, 52 Societal wellbeing 350
Semantic ambiguity 33 Solana 302
Semi-supervised learning 107, 132 Solutions-focused offerings 280
Semi-supervised machine learning Spam filtering softwares 107
65, 94 Specialized robots 211, 212
SENSE by Citymesh 271 Speech recognition 279
Sensors 5, 8, 22, 25, 36, 38, 55, Speech recognition software 107
118, 171, 172, 174, 176–179, SPIN Protocol 329
182, 183, 185, 187, 188, Spotify 39, 53, 110, 306
190–193, 195, 196, 198, 216, Spotify–AI DJ, Discover Weekly 39
221, 236, 257, 260–262, 270, Stanley, Morgan 82
274, 281 Starbucks 40, 41, 306
Sensors–biological, chemical, Statistical model (SM) 65, 108, 114,
meteorological 261 127
378 Index

Stitch Fix 45, 82 Technology management 323

Strategic flexibility 228 Technology-neutral 299
Strategic marketing actions 354 Telematics 187, 317
Streamlined communication 174 Temporary communications
Superbowl 129, 326 infrastructure 269
Supervised machine learning 65, 94 Tensor Processing Units of Google
Supply chain efficiency 310 Cloud 74
Supply chain transparency 312, 319 Tesco 279, 314
Supply-side platforms (SSPs) 327 Tesla 190, 221, 222, 229
Surveillance 9, 11, 191, 215, 231, Tevel 273, 274
255, 256, 261, 267, 288, 293, Text categorization 104
358 Text-to-3D models 71
Sustainability initiatives 22, 184 Text-to-image models 69, 71
Sustainable competitive advantage Text-to-task models 71
23, 26, 354 Text-to-text models 71
Sustainable marketing 20 Text-to-video models 71
Sustainable Skylines 270, 271 The New York Times 321
Syntactic ambiguity 33 Thermal sensors 267
Synthesia 71, 91 The Sandbox 146, 159
The voice 124, 148, 149
3D vending machines 151
T Tokenization 152, 160
Taco Bell 120 Topic modeling 113
Tactical marketing actions 346, 353, Toppr 121
354 Toyota 84, 320
Tactile internet (TI) 233, 241 Transformative marketing 3, 5, 15,
TADA 311 19, 20, 110, 141, 171, 255,
Tailored experiences viii, 22, 25, 77 346, 347
Target 3, 41, 42, 52, 54, 86, 106, Transparency 9, 195, 237, 300, 304,
155, 160, 230, 256, 354 306, 307, 309, 310, 314–317,
Target audience 2, 19, 38, 52, 75, 320, 322, 325, 326, 333,
89, 114, 142, 148–150, 152, 350–352, 357
157, 160, 223, 269, 312, 355, Transparent 11, 15, 40, 303, 315,
357 319, 320, 323, 329
Targeted marketing 12, 19, 25, 32,
Travel assistance 31
76, 82, 346
Travelers 158, 283
Task-specific recommendations 177
Trend analysis 118
Technological localization 226
Tug 230
Technology-backed strategy 108
Typeface 91
Technology ecosystem offerings 348
Technology effectiveness 309
Technology efficiency 25, 309
 Index 379

U Vedantu 121
UAS Traffic Management 280 Vertex AI by Google Cloud 74
Uber 46, 111, 119, 121, 126 Virgin Voyages 91
Uber Eats 53, 119, 121 Virtual assistance 211
Uber Freight 85 Virtual reality headsets 169
Ubiquity 324 Virtual reality technologies 12, 141,
Ubuntuland 150 164
Ugo 219, 229 Virtual reality (VR) 3, 5, 9, 10, 19,
Unacademy 121 38, 78, 128, 141, 144, 148,
Unilever 89, 172, 320 151, 156, 160, 161, 169, 225,
Unit load devices 318 263, 274, 276, 349
Unmanned Aerial Vehicles (UAVs) Voatz 314
16, 17, 255, 256, 258, 269, Vodafone 318
286 Voice assistants 32, 35
Unstructured data (UD) 105, 110, Volkswagen 226, 227, 317
132, 316 Volvo 129, 230, 312
Unsupervised learning 107, 113, 132 VRIO framework 23
Unsupervised machine learning 116
UPS 267, 268, 278, 285
W
UPS Flight Forward 267, 269
Urban city planning 175 Walmart 123, 149, 172, 219, 228,
Urchin Tracking Model (UTM) 271, 230, 231, 278, 279, 306, 315,
280 320
USAA 283 Walmart Land 149
US Air Force 272 Walmart Universe of Play 149
U.S. Cognitive Tutor 36 Wearable devices 36, 37, 171, 174,
U.S. Department of Defense 42 177
User engagement 6, 157, 314 Wearables 8, 22, 36, 37, 57, 172,
User experience 31, 41, 88, 123, 174, 176–179, 191, 199, 201,
145, 161, 325, 356 219, 313, 356
User-facing interactions 31 Weather-dependent 266
User involvement 173 Wendy’s 86, 125, 230
User sentiments 358 Whisper by OpenAI 72
UVD Robotics 218 Whole Foods 125
Wing systems 257, 258
Wokker Noodles 285
V
WOM Protocol 329
Value creating opportunities 80, Workhorse Group 269
186, 227, 275 WPP partnership with Nvidia 80
Value for firms 129, 282, 348, 360
Value growth for firms and X
customers 278 Xrana 219
Value to channel partners 348–351
Value to employees 348
Value to the community 348–351 Z
Value to the government 348–351 Zenbo 211