From Cash to QR Codes: Marketing
Strategies that Popularised E-Wallets
3 campaigns that convinced millions of Indians to go cashless
India is one of the fastest-growing and most innovative markets for digital
payments in the world, especially after the demonetization in 2016, the COVID-
19 pandemic in 2020, and the government initiatives to promote digital
payments. Registering 25.5 billion transactions in 2020 (60% more than China),
India is expected to touch $1 Trillion by 2026.
After the success of debit cards, e-wallets have now become popular and the
preferred way of payment. But you know how difficult it is to convince your
parents to try something new. Imagine doing that for MILLIONS of Indians.
How did India achieve this remarkable feat? And what can you, as a marketer,
learn from it?
Let’s take a look at some case studies (and why it worked) that established these
e-wallets in India:
1) GPay’s ‘Go India’ Campaign:
GPay launched a campaign called ‘Go India’ in October 2020, which invited users
to virtually visit different cities in India and collect stamps to get rewards and earn
money. The campaign used the tagline ‘GPay Go India, Safar Bhi Aur Cashback
Bhi’ (GPay Go India, Travel and Cashback Both) and a catchy tune to attract users.
The campaign was designed to create awareness and engagement among users
about GPay’s features and benefits. It also tapped into the travel aspirations of
users who were stuck at home due to the pandemic. The campaign used
gamification, social media, and word-of-mouth marketing to create a buzz and
drive participation.
The Result:
The campaign was a huge hit among users who enjoyed playing the game and
exploring different cities. The campaign attracted more than 10 million new users
to GPay in just two months. It also increased GPay’s UPI transactions by 40% and
its market share by 15%.
Why it Worked:
Gamification can create a unique and memorable marketing campaign that
resonates with customers and achieves marketing goals. By adding elements of
fun, challenge, reward, and competition, gamification can increase customer
engagement, loyalty, and retention, along with positive word-of-mouth
marketing!
2) PhonePe’s ‘Karte Ja. Badhte Ja’ Campaign:
PhonePe launched a campaign called ‘Karte Ja. Badhte Ja’ (Keep Doing. Keep
Growing) in January 2019, which used a motivational song to inspire users. It also
highlighted the various use cases and benefits of PhonePe, such as bill payments,
recharges, transfers, investments, etc.
The campaign was aimed at creating a positive and aspirational image of PhonePe
and its users. It also wanted to showcase PhonePe’s versatility and convenience
as a one-stop solution for all payment needs. The campaign used emotional
appeal, storytelling, and celebrity endorsement to connect with users.
The Result:
The campaign was successful in creating a positive and aspirational image of
PhonePe and its users and increasing their trust and confidence in the platform.
The campaign also increased PhonePe’s app usage by 45% and its revenue by
30%.
Why it Worked:
Emotional appeal can create a powerful marketing campaign that connects with
customers on a deeper level. By using emotions such as inspiration, motivation,
happiness, or nostalgia, emotional appeal can influence customer behavior and
loyalty.
3) Paytm Karo Campaign:
Paytm is one of the oldest and most popular digital payment apps in India. It
launched a campaign called ‘Paytm Karo’ (Do Paytm) in 2015, which used various
communication channels and tools, such as TV commercials, radio spots, print
ads, social media posts, and QR codes, along with featuring celebrities such as
Amitabh Bachchan, Sachin Tendulkar, and Alia Bhatt, to endorse Paytm and its
services. The campaign also offered various incentives and benefits to customers,
such as cashback, discounts, coupons, loyalty points, etc. for using Paytm.
The campaign was aimed at creating awareness and adoption of Paytm among
the masses. It also wanted to position Paytm as a simple and convenient solution
for all payment needs. The campaign used simplicity and repetition to create a
strong recall and recognition of Paytm and its slogan.
The Result:
The campaign increased Paytm’s app downloads by 60% and its user base by 40%.
The campaign also increased Paytm’s transactions by 50% and its revenue by
35%.
Why it Worked:
Simplicity and repetition can create an effective marketing campaign that
increases recall and recognition of a brand and its message. By using simple
words, phrases, or images, and repeating them across multiple channels and
platforms, simplicity and repetition can create a lasting impression on customers’
minds.
Key Takeaways:
So, those were the marketing campaigns that majorly increased the use of e-
wallets in India.
Remember these points for your next marketing strategy
- Use games for higher engagement.
- Connect emotionally with the audience.
- Keep it simple and repeat it enough times.
Your Marketing QOTD:
Marketing is not the art of finding clever ways to dispose of what you make. It is
the art of creating genuine customer value.
– Philip Kotler
Are you sure you know what
Artificial Intelligence (AI) is?
AI is trending nowadays, it’s hard to ignore that. But the
term is not something new: AI already existed way before
the ideation of current huge Transformer networks and
impressive Large Language Models (LLM).
Long before terms like Deep Learning (DL), Machine
Learning Operations (MLOps), and Artificial Neural
Networks (ANN) were common in the news and internet
posts, Artificial Intelligence had already been born. Born,
and healthy growing years before the launch of famous
tools like ChatGPT, Stable Diffusion, SAM, LLaMA, Bard,
and AlphaZero.
However, the name Artificial Intelligence has been
controversial since its first days. Claiming for machines to
be intelligent was something big, especially in a time in
which the limits of what a computer program could do were
shorter than we know today. The origins of computer AI
date back to the decades of 1940 and 1950, even when
we could find many previous traces of the design or
construction of automatic machines in human History.
But the real question is: what is it? Is Artificial
Intelligence an umbrella term for computer programs that
can actually think as we humans do? Is it the name for
computer programs that can actively learn and adapt
themselves? Or something else?
The answer is not easy, but I will try to clarify the idea.
Seeking the definition of Artificial Intelligence
Russel and Norvig wrote a marvelous introduction for their
infamous book Artificial Intelligence: A Modern Approach, in
which they discuss what AI is and how it became what it is.
Even the authors don’t have a complete and absolute
definition of AI, but they give us brilliant hints:
The field of artificial intelligence, or AI, is concerned with
not just understanding but also building intelligent entities
— machines that can compute how to act effectively and
safely in a wide variety of novel situations.
In general terms, what we understand today for AI is the
development of computer systems that can perform
tasks that typically require human intelligence. These
tasks include many fields like visual perception, speech
recognition, decision-making, and language translation or
generation. As Russel and Norvig say:
AI is relevant to any intellectual task; it is truly a universal
field.
Following this broad definition, the literature usually
considers at least two main types of AI:
Narrow or Weak AI. The program is designed and
developed to perform a particular task, and/or in a
specific environment.
General or Strong AI. The program is designed and
developed to perform any task, learning and adapting
from any environment as humans do — better or worse.
As you can guess, current AI models are still stuck in the first
group. Even when the development of modern LLMs is one
of the most promising paths in the search for a General
AI, there isn’t any program yet capable of complete and
autonomous reasoning and adaptation. Computer programs,
be they AI or not, are still running with many internal and
external limitations. However, AI research is currently
focused on the development of more general and
adaptive models, capable of performing multiple tasks and
learning from different environments, tending bridges
between the two types of AI.
But how can we differentiate an AI program from any other
computer program?
Think about this: any Python script that sums up the prices
of your grocery list and adds the taxes to the results, could
be considered “a computer program that performs a task
that typically requires human intelligence”.
In the end, you make use of your own human
intelligence and your math skills, to sum up those prices by
yourself. It is a human task, requiring human
intelligence. So why shouldn’t we consider AI that Python
script?
Many experts will tell you that AI systems are also designed
to learn from experience, adapt to changing inputs, and
perform tasks without being explicitly programmed for each
specific task. And that is true for many modern AI systems
(remember: we are on the seek for more general AI systems),
but not for all. There is AI beyond Machine
Learning: Bayesian Networks, Fuzzy Logic programs,
or Inductive Logic Programming systems are typical
examples. Even when we are accustomed to hearing about
highly deep and complex neural networks, plain
deterministic algorithms can be part of an AI system too.
Remember: the most Narrow AI is still AI!
So, what makes a grocery Python script and the object
detection software from Telsa different? Is it just the
complexity?
No, it is not the complexity. It is the purpose. AI
performs tasks that simulate human behavior or
reasoning. Sometimes the program simulates the human
mental process, and sometimes just the outcome because
we know little about our own brains. In the end, the AI
program is a mathematical model for the resolution of
a human task, that simplifies the whole mental
process. It is not an exact implementation of the same steps
we perform in our heads, but a workaround!
Bringing back the example of the Python script: summing up
a list of prices is an already well-determined
mathematical operation, that we can
describe unequivocally and repeatedly. On the other hand,
the recognition and spatial allocation of vehicles in our field
of vision is a task that we humans perform with knowledge
that cannot be expressed mathematically, and thus requires
a model to simulate the results.
The first cannot be considered AI, since it does not model
the intelligent agent that performs the task. It just solves a
problem, just performs a task, as any other mechanism in
human History has done before. There are no more mental
processes, no reasoning, no thinking or feeling about the
problem.
The vehicle recognition looks more like AI. It simulates the
human reasoning that we are not able to completely
explain and gives us similar results, using a mathematical
model. Even if we tried, with our current knowledge we
cannot describe and reproduce the exact mental process. If
you believe the trick still relies on complexity, think of
simpler tasks, like text recognition: identification of black
characters over white backgrounds. AI does that, simulating
our own reasoning, even when we humans don’t use “letter
recognition equations” when we read.
Conclusion
Even the simplest algorithm can be an AI if it models the
agent performing an intelligent task, and simplifies the
complexity of our human intelligence. We want AI
programs to decide for us, to guide our decisions, to
challenge us, or to automate our tasks. But it’s easy to
understand that, when we are modeling something
extremely complex as human thinking, we will need
more and more complex models in the future to
improve our results.
Why you should care about AI in
Marketing
If you are looking for fresh and efficient ways to reach and engage your
customers, Artificial Intelligence is the way to go.
But why should you care about AI in marketing? For the stat nerds,
- in 2021, the AI in marketing niche was valued at 15.84 billion USD.
- Also, 80% of industry experts incorporate some form of AI in online
activities, especially with ad targeting.
The topic for today is not about whether AI should be used or not, I think you
must have come across enough views and counterviews, especially this year.
With this topic, we are witnessing how technology is altering the ethos of
work.
Before AI, marketing relied heavily on traditional methods and intuition; with
AI, it has been transformed through data-driven insights, personalised
experiences, and increased efficiency.
AI is not just a buzzword anymore, it is changing how we approach various
niches of work, and marketing is one of them, especially digitally.
Let’s talk about the relationship between AI and marketing and look at
marketing campaigns that have been focused on AI personalisation.
Get your gear on and let’s plunge!
Technical Glossary:
Before we jump into the marketing aspect, here are a few terms for AI in
marketing that might be used further.
1. Machine Learning (ML):
This enables machines to learn from data and improve their performance
over time without being explicitly programmed.
For example, TensorFlow.
2. Data Mining:
The process of discovering patterns, trends, and insights from large datasets
using various techniques, including statistical analysis and ML.
For example, RapidMiner.
3. Natural Language Processing (NLP):
The ability of a machine to understand, interpret, and generate human-like
text. NLP is crucial for chatbots, sentiment analysis, and content creation.
For example, spaCy.
4. Chatbots:
AI-driven programs that simulate conversations with users are often used in
customer support or as virtual assistants.
For example, Chat-GPT.
5. Predictive Analytics:
The use of data, statistical algorithms, and machine learning techniques to
identify the likelihood of future outcomes based on historical data.
For example, IBM Watson.
6. Personalization:
Tailoring marketing content and experiences to individual users based on
their preferences, behaviours, and demographics, often powered by AI
algorithms.
For example, Optimizely.
7. Algorithm:
A set of rules or instructions designed to perform a specific task. In AI
marketing, algorithms are used for tasks like recommendation engines and
predictive modelling.
For example, Algorithmia.
8. Neural Networks:
A set of algorithms, modelled loosely after the human brain, that are
designed to recognize patterns.
For example, Keras.
9. Customer Lifetime Value (CLV):
The predicted net profit a business can make from a customer throughout
their entire relationship.
For example, Zaius.
10. Programmatic Advertising:
The automated buying and selling of online advertising in real-time using AI
algorithms to target audiences more precisely.
For example, MediaMath.
11. Computer Vision:
The ability of machines to interpret and make decisions based on visual data,
such as image recognition or video analysis.
For example, OpenCV.
12. Attribution Modeling:
Determining the channels or touchpoints that contribute to a conversion
helps marketers understand the customer journey.
For example, Google Analytics.
AI in Marketing Strategies:
Here are some real examples of how marketing has been done using the
help of AI:
AI for Ads:
AI optimizes ad targeting, predicts consumer behaviour, and generates
personalized content, enhancing efficiency and effectiveness in advertising
campaigns. In fact, Cosabella dropped their agency and uses AI in their
digital marketing!
About the Brand:
Cosabella is a lingerie retailer headquartered in the US with a global online
presence. Instead of using a regular digital agency, they made a strategic
shift in October 2016 and chose to work with an AI platform called "Albert”
as they wanted a smarter way to handle online advertising.
Working with AI + Results:
To make online advertising easier, Cosabella teamed up with Adgorithms,
the company behind Albert. They let Albert take charge of important
tasks like identifying and converting the best customers. The results were
impressive: in just one month, Albert increased Cosabella's search and
social return on ad ad spend by 50% and decreased the ad spend by 12%.
Albert's success also meant more people visited the website, with a 37%
increase, and more people became new customers—30% more, to be exact,
along with 1,500 additional transactions.
Albert didn't just bring in more money; it changed how Cosabella used social
media. Before Albert, social media accounted for 5-10% of their revenue,
but Albert contributed to 30% of the paid revenue.
Overall Thoughts:
Albert didn't stop there. It did some smart things, like figuring out what kinds
of ads people were getting tired of and making ads that worked better. Even
though Albert did so well, Cosabella still thinks regular agencies have their
place in marketing. But for certain jobs, like managing online ads, Albert is
the better choice.
Cosabella's switch to using Albert for online ads brought in more money got
more people interested, and made advertising work better—leading to a
decisive preference for AI over traditional human-centric approaches.
Video Courses Using AI:
AI aids video course creation by automating script generation, enabling
personalization, reducing production time, and facilitating global scalability,
enhancing accessibility. Let’s look at a real-life example.
About the brand:
Cyber Inc is a security and privacy awareness company that aims to prevent
cyberattacks. Catering to both small businesses and multinational
companies, Cyber Inc. operates in the IT services sector.
Working with AI + Results:
Cyber Inc. wanted to scale its business and enter new markets through video
content. But there were challenges in creating them traditionally, like time,
budget, and linguistic localisation. That’s when they used Synthesia, an AI-
driven video creation platform.
The AI-powered content generation process involves extensive data
collection, NLP analysis, course outline generation, dynamic video scripting,
and personalised adaptation.
They created a custom avatar using AI, allowing them to produce training
videos 80% faster, without the need for actors, expensive equipment, or
studio space.
The platform also facilitated training scripts in 6 languages, aiding quick
expansion and wider reach. Editing and generating new versions of the
content was also simpler and quicker.
Overall thoughts:
This shows how integrating AI-driven solutions can help to overcome hurdles
posed by traditional methods and usher in a new era of efficiency, cost-
effectiveness, and global scalability in video production.
With online courses being popularly preferred, AI platforms like this can be
used to make the content creation process more accessible and efficient to
everyone.
AI, Analytics, and Big Data:
AI in analytics and big data processes vast datasets, identifies patterns,
predicts outcomes, and enhances decision-making, driving personalized
insights, and targeted marketing strategies. Here is how Starbucks did it.
About the Brand:
Starbucks, the global coffee giant with 25,000 stores and 90 million
transactions weekly, has leveraged AI in its rewards program and mobile
app with 17 million and 13 million users respectively, Starbucks has
become a frontrunner in using data to enhance customer experiences and
shape strategies.
The data collected from these platforms, coupled with information about
weather, holidays, and special promotions, has become a goldmine for
directing marketing, sales, and business decisions.
Working with AI + Results:
The rewards program and app empower Starbucks to gather valuable
insights into customers' coffee-buying habits. The digital flywheel program,
an AI engine, takes this personalization further by suggesting new products
based on ordering preferences and contextual factors like weather and
location.
Starbucks relies on data to drive menu updates and special limited-offering
items. Seasonal promotions, like launching Frappuccino specials during
heatwaves, showcase Starbucks' adaptive use of data.
Starbucks also introduced an AI-driven virtual barista through its mobile app.
This feature allows customers to place orders using voice commands or
messaging.
Overall thoughts:
The wealth of customer data doesn't only enhance personalization but also
drives targeted marketing. Starbucks uses customer purchase history to
send personalized offers and discounts, re-engaging customers who haven't
visited recently.
In essence, Starbucks exemplifies how the marriage of big data and AI can
transform not just a customer's coffee order but the entire experience, from
personalization to strategic business decisions.
AI in Social Media Marketing Campaigns:
Recently, AI has been integrated into marketing campaigns as well to
provide personalised experiences that majorly drive engagement.
Dark Fantasy x SRK:
One of the most popular actors in the world, Shah Rukh Khan’s fans often
fantasise about meeting him. In their #HarDilKiFantasy (Every heart’s
fantasy) campaign, Sunfeast Dark Fantasy took this wish a step further by
enabling users to share the screen with King Khan using cutting-edge
Generative AI technology.
Generative AI Technology:
Sunfeast Dark Fantasy employs Generative Artificial Intelligence (GenAI)
which transforms fan selfies into visually appealing ads, seamlessly
integrating them into scenarios with SRK.
This technology revolutionizes the ad-making process, offering a
personalized touch. This enables hyper-personalisation, flexibility to choose
scenarios, and realistic high-quality advertisements.
Fan Participation:
Fans actively participate by sharing their selfies, which GenAI then
transforms into fantasy ads. The campaign encourages fans to share these
personalized ads on social media platforms using the hashtag
#MyFantasyAdWithSRK. The ease of fan involvement enhances engagement
and promotes a sense of connection with the brand.
Brand Proposition:
The company introduces a refreshed brand proposition: "Sunfeast Dark
Fantasy – Har Dil Ki Fantasy" (Every Heart's Fantasy). This aims to establish a
profound emotional connection with consumers, tapping into the universal
desire for a touch of fantasy in everyday life.
The "Dark Fantasy ad with SRK" campaign showcases the transformative
power of GenAI, turning a simple selfie into a fantasy advertisement,
showing its potential to enhance brand engagement and marketing efforts in
creative and memorable ways.
Coca-Cola’s Diwali Wishes:
This Diwali, Coca-Cola introduces a groundbreaking fusion of art and
technology, to celebrate Diwali. Through the integration of OpenAI's DALL-
E and GPT-4 models, Coca-Cola enables consumers to send personalized
Diwali wishes to their loved ones via unique AI-generated wish cards.
They created this portal for crafting magical Diwali greetings. The campaign
spans across India, Bangladesh, Nepal, Sri Lanka, and Bhutan, reflecting the
brand's commitment to a widespread celebration.
Coca-Cola provides a diverse range of options for x creating personalized
wish cards. From cards adorned with colourful diyas to featuring quirky auto-
rickshaws, iconic Coca-Cola cans, bottles, and traditional rangolis, users can
craft a masterpiece that captures the essence of India's Diwali.
Source: The Financial Express
Statement from Coca-Cola's Global Head of Generative AI:
Pratik Thakar, Global Head of Generative AI at Coca-Cola, emphasizes the
brand's commitment to connecting culture, creativity, and technology. The
"Create Real Magic" platform invites consumers to utilize AI for crafting
original artwork using iconic creative elements from Coca-Cola's archives.
The Diwali wish cards are a testament to celebrating people and culture
through AI.
Encouraging Uniqueness and Personalization:
Coca-Cola encourages individuals to break away from conventional
messages and generic season's greetings. By creating one-of-a-kind Diwali
wish cards powered by AI, participants can celebrate #MagicWaaliDiwali by
being themselves.
Recognition for Outstanding Creations:
The best creations will be proudly displayed on prominent digital billboards in
Mumbai and Delhi NCR, providing contributors with due credits. This
recognition adds an extra layer of excitement and motivation for participants
to unleash their creativity.
Coca-Cola's Commitment in India:
Coca-Cola in India, as one of the leading beverage companies, offers a wide
portfolio of high-quality and refreshing beverage options. The company's
vision of 'Beverages For Life' includes products ranging from hydration and
sports drinks to coffee, tea, nutrition, juice, and dairy-based products.
In essence, Coca-Cola's AI-generated personalized wish cards for Diwali
showcase the brand's commitment to innovation, creativity, and celebrating
cultural moments with a touch of technology.
The campaign not only adds a unique flavour to Diwali celebrations but also
reinforces Coca-Cola's position as a brand that embraces the spirit of joy and
connection.
Limitations:
1. Creativity and Innovation Challenges:
AI, proficient in data analysis, faces hurdles in embracing human-like
creativity. For instance, it cannot create emotionally resonant campaigns
like this one from ICICI.
2. Privacy and Ethical Concerns:
The extensive use of consumer data in AI-driven marketing raises significant
privacy and ethical concerns. So, we need a delicate balance between
personalized marketing and respecting data protection regulations.
3. Customer Relationship Building:
Despite advancements, AI may struggle to replicate the human touch
required for building authentic customer relationships, including empathy,
understanding, essential for building genuine connections and trust.
Learn AI Marketing:
After looking at the impact that AI can create in marketing and how
accessible it is, you might want to check these courses out to hone your
skills.
1. Artificial Intelligence in Marketing on Coursera.
2. AI in Marketing on Udemy.
3. AI for Marketing (No-Code) on Udemy.
Click to become a well-rounded and irreplaceable marketeer!
In a Nutshell:
While AI in marketing has some limitations, the benefits it brings to the table
are transformative. The key lies in striking a harmonious balance, leveraging
AI for its analytical abilities while recognizing the irreplaceable role of human
creativity and emotional intelligence.
The future of marketing is being redefined by delivering personalised, data-
driven, and highly effective campaigns. This will help to unlock the full
potential of AI in creating impactful and resonant marketing campaigns with
the audience!
Key Takeaways
(screenshot this)
Embrace AI in marketing for efficient customer reach and engagement.
Leverage AI platforms to enhance marketing strategies and save time.
Strike a balance between human creativity and artificial intelligence.
