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How augmented reality impacts retail marketing: a state-of-the-art review

from a consumer perspective

Article in Journal of Strategic Marketing · June 2023

DOI: 10.1080/0965254X.2021.1972439

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How augmented reality impacts retail marketing: a state-of-

the-art review from a consumer perspective

Abderahman Rejeb, Karim Rejeb & Horst Treiblmaier

To cite this article: Abderahman Rejeb, Karim Rejeb & Horst Treiblmaier (2023) How augmented reality impacts

retail marketing: a state-of-the-art review from a consumer perspective, Journal of Strategic Marketing, 31:3, 718-

748, DOI: 10.1080/0965254X.2021.1972439

To link to this article: https://doi.org/10.1080/0965254X.2021.1972439

Abstract

Augmented reality presents numerous opportunities and challenges for marketers to enrich the

retail shopping experience. Although the technology is well established, practical marketing

applications are rare, and the existing literature is unstructured. We conduct a systematic

literature review with the goal of synthesizing the latest developments in the field and developing

research propositions. We analyze 91 papers and identify four major enablers of AR in retail

marketing: enhancement of the consumer experience, improvement of the customer-brand

relationship, support of marketing activities, and promotion of marketing competitiveness. The

challenges of AR adoption in marketing include technical limitations, consumer-oriented

challenges, technological immaturity, and organizational challenges.

Summary statement of contribution

1
In spite of the numerous advantages that augmented reality promises for retail marketing, the

current academic literature is largely unstructured and a systematic overview is missing. In order

to close this research gap, this paper summarizes previous findings and highlights the major

enablers and challenges of augmented reality in retail marketing.

Keywords: augmented reality; retail marketing; consumer experience; systematic literature

review; research agenda

1. Introduction

Augmented reality (AR) technologies constitute an innovative marketing resource that offers

numerous opportunities for businesses such as creating entertainment value, supporting purchase

decisions, or improving products’ ease of use (Kostin, 2018). Today, AR is becoming a

mainstream technology that is easily accessible for consumers (Park & Yoo, 2020), altering the

ways in which they buy and consume products and services (Piancatelli et al., 2021; van Esch et

al., 2019; Verhoef, 2021). According to Rauschnabel, Felix, & Hinsch (2019), in the future, AR

will be indispensable to marketing. Forecasts predict that the worldwide AR market size will

grow from roughly 3.5 billion USD in 2017 to more than 198 billion USD in 2025 (Statista,

2020a) with more than 1.73 billion worldwide mobile AR users in 2024 (Statista, 2021).

Similarly, a Deloitte survey among American companies highlights that 88% of mid-market

companies (firms with annual revenues of between 100 million USD and 1 billion USD) have

already started employing virtual and augmented reality as part of their respective business

models (Deloitte, 2019). In this context, AR can be defined as the digital technology used to

2
combine computer-generated information such as images and sounds with information from

users’ real-world environments (Baek et al., 2018).

The fundamental characteristics that define AR are the combination of real and virtual elements,

their interactions in real time, and their accurate three-dimensional (3D) registration (i.e.,

alignment) (R. Azuma et al., 2001). AR differs from virtual reality (VR) in that it allows for an

enhanced perception of reality rather than substituting it. Unlike AR, VR creates an artificial

environment in which the user is completely immersed in a simulation of the real world or an

imaginary world (Bretonès et al., 2010; Khan et al., 2011). The developers of AR applications

tend to create images and computer-generated enhancements that permit users to combine those

with real-world objects and interact with virtual elements in real life (Shabani et al., 2019). The

approach of enhancing users' sensory perceptions with AR has inspired marketing researchers to

further examine the importance of this technology in boosting e-marketing (Shabani et al., 2019),

supporting ad campaigns (Feng & Mueller, 2019), and creating effective advertising strategies

(Phua & Kim, 2018). Previously, AR technologies have forced brands to reconsider their existing

marketing strategies and practices in order to reach more consumers and bolster sales revenues

(He et al., 2018). For example, major companies such as IKEA and McDonald’s already apply

AR in their advertising activities and design AR applications in order to increase customer

convenience (Ng & Ramasamy, 2018). Moreover, advances in digitization have driven the

deployment of AR for marketing purposes at various touchpoints of the consumer journey, which

includes both offline as well as online interactions (Javornik, 2016a). While the offline retailing

environment offers consumers numerous opportunities for sensory control, online retailing still

lacks genuinely multi-sensory experiences despite of its reliance on visual features (Petit et al.,

2019). As a result, the lack of multi-sensory control over products makes the online environment

3
more suited to AR deployment, since the technology benefits consumers by increasing their

understanding of products without compelling them to visit offline stores and supporting their

purchase decisions (M. Park & Yoo, 2020). With the help of AR, retailers can bridge the gap

between offline and online experiences by combining the two and enabling consumers to

maintain a realistic expectation of the products (Fan et al., 2020). Therefore, in this paper, we

argue that AR constitutes a step forward in online product visualization, making the level of

consumer engagement superior as compared to traditional offline marketing experiences.

Moreover, we contend that AR is more capable of solving the problems of online retailing than

those of offline retailing because the technology has the potential to offer a more immersive and

engaging shopping experience and even allows to create an in-store (offline) experience within

consumers’ homes. AR has thus become a critical component in the mobile marketing repertoire

as it enables brands to enrich their consumers' perceptions as well as product and service

knowledge with (virtual) offerings (Scholz & Duffy, 2018).

Motivated by the increasing importance of AR and its popularity in marketing research and

practice, in this paper we investigate the objectives and challenges of AR in this field. Although

AR is considered a well-established technology that employs fundamental operating principles

dating back several decades, research exploring AR in business and marketing is still scarce

(Feng & Mueller, 2019). The proliferation of AR campaigns has attracted growing attention;

existing academic studies, however, do not provide a comprehensive documentation of the

impact of AR in marketing (Hinsch et al., 2020). Therefore, a clear presentation of exactly what

AR promises for marketing is necessary in order to advance knowledge and understanding of this

emergent technology and lay the foundation for systematic future research. AR literature that

deals with the early-stage development of marketing applications calls for increased academic

4
recognition and engagement. In this paper, we strive to fill this knowledge gap and synthesize

the existing research in order to provide a comprehensive overview of the objectives and

challenges of AR in retail marketing. We specifically strive to accomplish the following three

research goals:

RG 1: Presentation of the current state of the art of academic research in AR in retail marketing,

RG 2: Identification of companies’ objectives pertaining to the application of AR in retail

marketing, and

RG 3: Identification of companies’ challenges pertaining to the application of AR in retail

marketing.

To the best of our knowledge, no scientific efforts have been undertaken to survey the existing

AR literature and examine the potentials of this technology in the marketing field to date. The

systematic review of previous scholarly undertakings will benefit both researchers and

practitioners who are interested in learning how AR can potentially impact retail marketing. Both

scholars and marketers can obtain a holistic understanding and derive new insights into the

integration of AR in marketing activities. This will help to guide future research in this topical

area and enhance managerial understanding.

2. Methodology

To explore the state of the AR art in retail marketing research and applications, we conducted a

systematic literature review (SLR) following the guidelines by Tranfield, Denyer, & Smart,

(2003). SLRs provide an overview of the evidence behind different ‘manners’ and helps to

codify knowledge in a certain area (Nybo & Madsen, 2008). It necessitates a detailed description

of the selected keywords and eligibility criteria as well as the scouring of scientific search

5
databases using a thorough process for screening the publications for relevance based on the title,

abstract, and full-text analysis of the retrieved studies. The review steps that are followed in this

study ensure a rigorous and comprehensive documentation of the literature search and how we

generated knowledge and insights. Throughout the entire review process, meticulous attention

has been paid to ensure the inclusion of all relevant studies, the high quality of retrieved

literature, and the validity of the final synthesis. The SLR was guided by a protocol that was

developed by the authors (see Table 1). We undertook an iterative cycle, starting with the

definition of suitable search keywords, the selection of relevant studies, and, finally, the

performance of the analysis. Table 1 also lists the academic databases we used as well as the

inclusion and exclusion criteria.

Table 1. Research protocol

6
Research protocol Details

Research online Scopus and Web of Science. Scopus, a major scientific database,
databases contains over 20,000 academic journals spanning all scientific
disciplines (Maretti et al., 2019). Web of Science (WoS) indexes
more than 33,000 academic journals and conference proceedings
across all fields of sciences (Kimball, 2018).
Publication types Only peer-reviewed literature was considered. Both practitioner and
academic studies were considered. The search was limited to journal
articles to ensure the academic nature of selected studies and
enhance quality control (David & Han, 2004).
Language The review only included articles published in the English language.
Date range Unlimited. No specific time frame was used to conduct the search.
Search fields Title, abstract, keywords
TITLE-ABS-KEY ( "augmented reality" AND ( "market*" OR
Search keywords "advertis*" OR "target*" ) )

Inclusion criteria The selection was limited to publications that studied AR

applications in marketing.
Exclusion criteria Publications with a deep and pure technical focus were excluded.
Papers studying AR beyond the context of marketing-related topic
areas were filtered out.

The PRISMA Statement offers several recommendations guidelines that assist researchers and

evaluators in the proper identification, screening, suitability, and inclusion of all steps of the SLR

procedure (Moher et al., 2009; Page et al., 2021). The identification of the records was made

through two academic databases: Scopus and Web of Science (WoS). The search was carried out

using various keyword combinations and two Boolean operators, AND and OR in the abstract,

title, and keywords fields. After a preliminary search using the pre-specified keywords, our

initial set of publications included 264 papers, as shown in the PRISMA flow diagram in Figure

1.

7
After checking the title, author(s), and year of publications, the duplicated documents were

deleted, resulting in 200 eligible ones. A screening task was then performed to identify the

relevant articles for our research questions. During this process, several inclusion criteria (in this

case the coverage of AR applications in retail marketing) were applied to identify the relevant

articles needed to answer the research questions under study (Petti et al., 2018) and reduce

distraction towards impertinent articles. The first screening was carried out based on the titles

and abstracts, resulting in the elimination of the articles which discussed AR beyond the

marketing context. The remaining 115 articles were analyzed in full text, and only those which

discuss objectives and challenges of AR applications in marketing were considered for the final

analysis. By doing so, 91 relevant articles were selected and analyzed in detail.

8
 Figure 1. Schematic presentation of literature collection

In order to achieve our research goals pertaining to the presentation of the current state of the art

as well as the objectives and challenges of AR in retail marketing, we initially screened each

publication. The clustering process, which yielded four major categories respectively, was based

on an inductive approach that is frequently used in qualitative content analysis. In the first step,

we identified the core topics of each publication and then created and revised categories on a

higher abstraction level until a common agreement was reached among the researchers. The final

categories were disjunct and provided a sufficient level of abstraction to include all core topics

that we previously identified in the literature (Mayring, 2000). Every category also contained

9
several areas that were under-researched, which we later present as research propositions for

future studies.

3. Findings

3.1. Publications by year

The search and analysis were carried out in March 2021. Figure 2 presents the number of articles

published by year. Despite being an established field of research, AR in marketing has only

gained academic recognition in the last decade. Consequently, all marketing-related studies

investigating this developing technology were published between 2008 and 2020, but it has only

been in the last three years that interest has surged. Marketing scholars have become increasingly

aware of the opportunities arising from the adoption of AR in marketing. This mounting interest

is attributable to the evolution of marketing channels (Kostin, 2018), marketing communications,

and the rise of experiential marketing (Atwal & Williams, 2017; Schmitt, 1999). Brands

capitalize on innovative technologies such as AR to cope with new market conditions, identify

consumer needs, and use proper channels of customer feedback.

30
27
26
25
Number of publications

20

15
12

10 9
6
5 3 3
2 2
1
0
2008 2012 2013 2014 2015 2016 2017 2018 2019 2020
Year

10
 Figure 2. Year-wise distribution of AR studies in marketing

3.2. Publications by country

To illustrate the geographical distribution of AR publications in the context of retail marketing,

we referred to the authors' affiliations at the time of publication. As shown in Figure 3, the

analysis by country illustrates that the USA is the most active country in the AR marketing

research area with 37 articles followed by the UK and Australia. This is line with current

distribution of AR applications. The number of AR users in the US is predicted to reach more

than 95 million by 2022 (Statista, 2020b), reflecting the ability of AR to appeal to a high number

of US consumers. Another study showed that 72% of US consumers made spontaneous purchase

decisions because of AR (Business Wire, 2016). In contrast to the USA, researchers from the UK

authored 21 publications. For the global AR market, a report from Immerse (2019) reveals that

the UK has nearly 1,000 companies specializing in virtual, augmented, and mixed reality

markets. The report further notes that approximately half a million UK citizens work in firms

that use immersive technologies in their respective business models and contribute to the

development of the immersive economy.

In Australia, AR research started in the early years (Piekarski, 2004; Piekarski & Thomas, 2003).

The country has committed efforts to develop its Industry 4.0 agenda through the establishment

of official initiatives and agreements that aim to leverage modern technologies, including AR

(Dean & Spoehr, 2018). To illustrate, the city of Perth has recently introduced an EyeJack

mobile app that uses AR to provide multi-sensorial and experiential stimuli to tourists, simplify

the navigation of tourism destinations, and identify the cultural traits of particular touristic places

11
(Sigala, 2019). Australian researchers have contributed to the reviewed literature with six

publications. Finally, we identified eight researchers from Germany and six from both India and

South Korea. Additionally, we found numerous other affiliations, which indicates a widespread

interest in the topic.

40 37
35
Number of publications

30
25 21
20
15 13

10 8
6 6 5 5 4 4 3 3 3
5 2 2 2 2 1 1 1 1 1 1 1 1 1 1
0
United States

Australia

France

Norway
Netherlands

Italy

Finland
Malaysia
Canada
Hong Kong
Germany
India

Spain

China

Poland
Russia
South Korea

Belgium
Japan

New Zealand

Singapore
Sweden
Portugal

Switzerland
Lebanon

Taiwan
United Kingdom

Figure 3. Country-wise publication details

3.3. Publications by journal

We used the BibExcel tool to classify the journals. In total, the 90 selected studies appeared in 62

different journals, which indicates the relevance of the topic across numerous domains. As is

shown in Table 2, the Journal of Retailing and Consumer Services published a total of ten

articles followed by the Journal of Interactive Marketing with four articles and the Journal of

Destination Marketing and Management, the Journal of Destination Marketing and Management,

and the Journal of the Academy of Marketing Science, which published three articles each.

Additionally, 47 journals each published one article. The literature related to AR technologies in

12
the context of marketing spans numerous academic disciplines such as marketing, tourism and

hospitality, management, computer science, and other social sciences.

Table 2. Journal publications details

Number of
Source title publications

Journal of Retailing and Consumer Services 10

Journal of Interactive Marketing 4
International Journal of Retail and Distribution Management 3
Journal of Destination Marketing and Management 3
Journal of the Academy of Marketing Science 3
Australasian Marketing Journal 2
Business Horizons 2
Continuum 2
Current Issues in Tourism 2
ISPRS International Journal of Geo Information 2
Journal of Current Issues and Research in Advertising 2
Journal of Hospitality and Tourism Technology 2
Journal of Interactive Advertising 2
Journal of Research in Interactive Marketing 2
Tourism Management 2
Others 48

3.4. Publications by methodology

13
Figure 4 summarizes the research methods used in the 91 papers. In total, we identified eleven

different methodological approaches, most of which were empirical. Within this group, surveys

are the most popular method of investigation, with an explicit focus on evaluating the impact of

AR on consumer experiences and identifying specific benefits and challenges of using AR

technologies. The analyzed empirical studies mainly use primary data collected through surveys,

experimentation, and case studies, but also secondary data collected from social media. We also

found several experiments that were conducted to test the effectiveness of AR applications in the

marketing environment and assess the perceptions and attitudes of users toward the adoption of

AR in marketing-related experiences. Seven studies use a multi-methods approach that are often

conducted by developing AR apps and testing them with surveys. Furthermore, we found ten

papers that apply qualitative interviews, nine case study methods, two content analyses, two

prototype developments, and one paper that uses a mixed methods approach. Non-empirical

papers include fifteen papers that conceptually analyze AR technologies, eight that review digital

marketing trends and AR impacts on consumer behavior, and, finally, three papers that build

frameworks intended to support the consumer experience with AR.

25

20
Number of publications

20

15
15 14

10
10 9
8
7

5 3
2 2
1
0

14
 Figure 4. Distribution of selected papers based on research methods

4. Review discussion

The main objectives that we identified in the academic literature are enhanced consumer

experience, improved brand-customer relations, support for marketing activities, and the

promotion of marketing competitiveness. As far as challenges are concerned, we identified

technical limitations, consumer-oriented challenges, technological immaturity, and

organizational barriers (see Figure 5). Table 3 provides a full summary of our literature review,

including the method being used and the respective objectives and challenges. In the following

sections, we discuss each objective and challenge in more detail followed by the presentation of

one or more research propositions. The research propositions that we present are based on

existing gaps in the literature that we identified by summarizing and clustering the existing

literature as discussed in the methodology section.

Figure 5. AR objectives and challenges for retail marketing

15
 Table 3. Paper classification

AR objectives for retail AR challenges for retail

marketing marketing
Author(s) Methodology
E1 E2 E3 E4 C1 C2 C3 C4
(Aluri, 2017) Survey x x x x
(Baek et al., 2018) Experiment x x x
Multi-
(Blanco-Pons et al., 2019) methods x x x x
(Buhalis et al., 2019) Conceptual x
(Carrozzi et al., 2019) Experiment x x x x
(Chopra, 2019) Interview x
(Del Moral Pérez et al.,
2016) Case study x x x
(Enchexa & Pedersen, 2014) Conceptual x
Content
(Feng & Mueller, 2019) analysis x x x x x x x
(Feng & Xie, 2018) Survey x x x x
(Feng & Xie, 2019b) Experiment x x
Content
(Feng & Xie, 2019a) analysis x x x
Mixed
(Grzegorczyk et al., 2019) methods x x x x x x x
Multi-
(J. Guo et al., 2019) methods x x x x x
(He et al., 2018) Experiment x x x x
(Hilken et al., 2017) Experiment x x x x x
(Hilken et al., 2019) Experiment x x x x x
(Hinsch, Felix, &
Rauschnabel, 2019) Survey x x

16
(Hopp & Gangadharbatla,
2016) Experiment x x x x x x
Multi-
(Idris et al., 2019) methods x x
(Javornik, 2016a) Review x x x x x x
(Javornik, 2016b) Experiment x x x x x x
(Joshi, 2018) Conceptual x x
(T. H. Jung & tom Dieck,
2017) Framework x x x
(Jung et al., 2018) Survey x x x
(Kostin, 2018) Review x x
(Lagiewski & Kesgin, 2017) Case study x x x
Multi-
(Li et al., 2019) methods x x
(Liao, 2015) Interview x x x
(Loureiro et al., 2019) Review x x
(Marasco et al., 2018) Survey x x
(Ng & Ramasamy, 2018) Framework x x x x x x
(Olsson et al., 2013) Interview x x
(Pantano & Serxidio, 2012) Survey x
(Pantano et al., 2017) Survey x x x x
(Parise et al., 2016) Interview x x
(Park & Stangl, 2019) Survey x
(Park & Yoo, 2019) Survey x x x x
(Petit et al., 2019) Review x
(Phua & Kim, 2018) Survey x x
(Poncin & Ben Mimoun,
2014) Survey x
(Ramadan & Farah, 2017) Interview x x x
(Rauschnabel et al., 2019) Experiment x x x x

17
(Ruyter et al., 2018) Conceptual x x x x
Multi-
(Sasaki & Yamamoto, 2019) methods x
Multi-
(Scholz & Duffy, 2018) methods x x x x x
(Scholz & Smith, 2016) Framework x x x x
(Shabani et al., 2019) Case study x x x x x x
(Sihi, 2018) Interview x x x x
(Steinhoff et al., 2019) Conceptual x x
(tom Dieck & Jung, 2017) Case study x x x x
(van Esch et al., 2019) Survey x x x x x x
(Xishnexskaya et al., 2017) Conceptual x x x x
(Wang, 2013) Prototype x x
(Yaoyuneyong et al., 2014) Conceptual x x
Multi-
(Yim et al., 2017) methods x x x x x
(Zhu et al., 2008) Prototype x x x
(Chylinski et al., 2020) Review x x x x x x
(Haile & Kang, 2020) Survey x x x
(Wedel et al., 2020) Conceptual x x x x x
(Chang et al., 2020) Case study x x
(Hoyer et al., 2020) Conceptual x x x
(Cranmer et al., 2020) Interview x x x x x x
(Saleme et al., 2020) Survey x x
(K. Jung et al., 2020) Survey x x x x x x
(Jäger & Weber, 2020) Survey x x
(Yang et al., 2020) Experiment x x x x x x x x
(de Ruyter et al., 2020) Conceptual x x x x x x x x
(Cuomo et al., 2020) Case Study x x x
(Lacka, 2020) Survey x x x x x x

18
(Davis et al., 2021) Conceptual x x
(Tsai et al., 2020) Experiment x x x x x x x x
(Hawker & Carah, 2020) Experiment x x
(Dwivedi et al., 2020) Interview x x x x x x
(Penco et al., 2020) Survey x x x
(Huertas & Gonzalo, 2020) Interview x x x
(Hausmann & Schuhbauer, Case study
2020) x x
(Wei, 2019) Review x x x x x x x x
(Perannagari & Chakrabarti, Review
2019) x x x x x x x x
(Saar et al., 2019) Case study x x x
(R. T. Azuma, 2019) Conceptual x x x x x
(Yung & Khoo-Lattimore, Review
2019) x x x x x x x x
(Moroz, 2019) Case study x
(Shin et al., 2019) Survey x x x x x x x x
(Gómez-Barroso et al., Interview
2012) x x
(Mishra et al., 2021) Experiment x x x x x
(Xu et al., 2019) Experiment x x x x x x x x
(Biswas, 2019) Conceptual x
(Sood, 2012) Conceptual x
(Kotsios, 2015) Conceptual x x x x x
(Moriuchi et al., 2021) Survey x x x x x
Challenges
Objectives
C1: Technical limitations
E1: Enhance consumer experience
C2: Customer-oriented challenges
E2: Improve brand customer relationship
C3: Technological immaturity
E3: Support marketing activities
C4: Organizational barriers
E4: Promote marketing competitiveness

19
4.1. Augmented reality objectives for retail marketing

4.1.1. Enhanced consumer experience

AR has been heralded as a boon for consumers due to its ability to offer a wide array of

information and increased control over the purchasing experience (van Esch et al., 2019). AR

enriches consumers' perceptions by providing instant access to visual information such as digital

images, videos, texts, audio, and computer simulations (Hinsch et al., 2020; Pantano et al.,

2017). Furthermore, the application of AR in marketing is likely to influence information search

and decision-making processes through the overlay of digital information or objects over the

products in question. As such, AR constitutes a novel way to influence purchase decisions as

consumers will be able to virtually test products, thus stimulating perceptions of control and

ownership (Steinhoff et al., 2019). According to Pantano, Rese, & Baier (2017), the virtual try-

on functionality inherent in AR applications will benefit e-commerce and increase possibilities to

interact with the product under consideration via the ability to test offerings in terms of various

aspects such as texture, appearance, fit, or sound. The approach of adding virtual information to

an online purchase opportunity can lead to a sense of increased competence and feelings of self-

empowerment (Hilken et al., 2019). Likewise, the virtual testing of products increases perceived

control over shopping activities and intensifies the elaboration of vivid mental imagery (Park &

Yoo, 2019). In addition, AR can offer a wealth of informational resources that help to enhance

the personal awareness of the surrounding context (Park & Stangl, 2020). Similarly, AR

augments the sensory perception of customers in that they will be able to see how the products fit

to their needs while still enjoying the convenience of e-commerce and virtual shopping (Ng &

Ramasamy, 2018). AR thus creates highly immersive experiences that outperform conventional

20
online service experiences and mobile applications, allows for 360° degree product presentations

or photo-based try-ons, and responds to customer needs for embodiment and embedding (Hilken

et al., 2017; Javornik, 2016; Olsson et al., 2013; Park & Yoo, 2020). For instance, Hilken et al.

(2017) note that AR improves the cognitive potential of consumers, simplifies situational-

information processing, and can embed a product within a personally relevant context. To

illustrate these capabilities, Pantano, Rese, & Baier (2017) provide the example of a Ray-Ban

virtual mirror, which is a system that allows consumers to virtually try on the available glasses.

In this application, online shoppers use a computer camera to try on sunglasses as if they were in

the fitting room of a brick-and-mortar store (Baek et al., 2018).

The abundance of products and services offered to consumers may create confusion and add to

shoppers' decision-task uncertainty (Campbell, 1988). Consumers may find that an equivocal and

complex product mix exacerbates the difficulty of judging the relative quality of a product

among several choices (Boyer et al., 2002), thus making purchase decisions more difficult. In

such situations, AR makes it easier for consumers to make optimal purchase decisions. Exposed

to the bundling of numerous products and services features, AR can assist consumers by

reducing the efforts associated with intensive information searches and product screening in

order to differentiate between offerings and make the right choice (Wang, 2013). While the

proliferation of product-related information has substantially increased the cognitive efforts

needed to identify the right product, AR technology drives consumers to filter out unrelated

perceptions and thoughts from the main mental processes (Park & Yoo, 2019). AR enhances the

consumer experience by enabling quick access to high-quality product information, the easy

navigation of real-world environments, the timely flow of mobile payments, and the facilitation

of advertisements and social interaction (Olsson et al., 2013). Similarly, Hilken et al. (2019)

21
illustrate that social AR applications can enhance purchasing decision processes and enable

recommenders as well as decision makers to lean on each other's support in online shopping

settings. The ability to support customers during the purchase decision process can increase

customer satisfaction and repurchase intention while improving brand marketing. In this context,

Hilken et al. (2019) argue that AR optimizes consumer purchase decisions and enhances the

ability of retailers to influence consumer choices, resulting in positive ripple effects on loyalty

and word-of-mouth communication. Therefore, AR offers prospective and existing consumers

the basic product and service information, enhances the representation of digital offerings, filters

out distracting information (de Ruyter et al, 2018), empowers product choices, and maximizes

individual utility. Thus, we propose the following research propositions related to AR objectives:

RP O-1: How do consumers perceive AR in retail marketing?

RP O-2: Which individual consumer traits are responsible for the adoption of AR by consumers

in retail marketing situations?

4.1.2. Improved brand-consumer relationship

Maintaining strong brand-customer relationships is hinged on consumers’ willingness to sustain

an affective commitment and engagement with brands (Vivek et al., 2012). Consumer

engagement and involvement is therefore a critical factor for marketers. Similarly, scholars have

found that consumer engagement plays a key role in the process of communication-based trust

and transfer (Liu et al., 2018). Consistent with relationship marketing theory, the interactivity

and experiential value offered by AR technology fosters a new level of engagement that

surpasses mere usage intensity (Brodie et al., 2013; Vivek, Beatty, & Morgan, 2012). As a novel

emerging technology, communication scholars have started to recognize the importance of AR

22
displays and their implications for customer-brand relationships (Feng & Xie, 2019a; Liao,

2015). According to Shabani, Munir, & Hassan (2019), AR increases the involvement of

marketers and consumers with brands and maximizes the benefits for both parties. The

effectiveness of AR communication and its ability to circulate innovative marketing content can

contribute to the improvement of brand-expected value. As mentioned frequently in the reviewed

studies, AR interactivity is a distinctive feature that can pave the way to a highly immersive

environment and rich information exchange between the brand and consumers (Parise et al.,

2016). The technology represents a valuable communication instrument that enhances the level

of sociability and engagement by embedding the branded content into consumers’ conversations

(Scholz & Smith, 2016). By the same token, Scholz & Smith (2016) opine that AR can

significantly simplify the interpersonal and affective relationships between consumers and

strengthen brand communities. This can be seen as an enhanced communication infrastructure in

which customers can freely express their opinions and generate lasting and positive impressions.

Moreover, the adoption of AR in mobile shopping creates opportunities for strengthening

consumer and brand ties through innovative relational features (Scholz & Duffy, 2018). This is

because the technology enables consumers to maintain a timely and continuous access to mobile

communication environments (Vishnevskaya et al., 2017). In other words, AR creates a seamless

environment wherein brands can deepen their interaction with consumers, receive instantaneous

feedback, and identify new value creation opportunities. Feng & Xie (2019) report that AR

encourages consumers to interact with a print ad in order to obtain detailed knowledge of

specific product features. Wang (2013) develops a prototype based on AR for interior furnishing

design and highlights the benefits of AR in achieving a more realistic experience of "home

furnishing" products, further offering a reach information base to enhance companies’

23
communicative interactions with consumers. The unique user-brand interaction differentiates AR

from other technological innovations and enables increased brand awareness (Feng & Mueller,

2019) by reshaping the dynamics of communication between brands and consumers. Rather than

being passive recipients of conventional marketing messages and information, AR sustains the

active engagement of consumers with the focal brand (Ramadan & Farah, 2017). This is

consistent with the assertion of Rauschnabel, Felix, & Hinsch (2019) that consumers can rely on

AR technologies to craft brand-focused stories by drawing attention to the brands they favor the

most and avoiding brands that do not meet their expectations.

AR also provides opportunities for building brand attachment and engaging with consumers

through the support of experiential marketing (Schmitt, 1999). The creation of unforgettable and

entertaining experiences strengthens the degree to which consumers are emotionally involved

and engaged with brands. Immersive experiences create hedonic benefits (Rauschnabel et al.,

2019) and encourage consumers to respond and interact with brands by using multi-sensory

images, emotional arousal, and fantasies. For example, several world-renowned brands,

including Coca-Cola, McDonald's, and General Electric, have deployed AR in their marketing

strategies to offer creative advertising and packaging, improve shopping experiences, and

develop captivating games (Scholz & Smith, 2016). Ramadan & Farah (2017) note that AR

facilitates the gamification of retail and leads to the formation of new forms of communities

wherein consumers can connect, share their opinions, and urge marketers to take advantage of

those communities in order to introduce better products and positively respond to consumer

needs. Through the gamification of marketing experiences, AR encourages consumers to share

their experiences, resulting in increased brand engagement and loyalty. Therefore, we investigate

the following research propositions:

24
RP O-3: What is the impact of AR in retail marketing on the brand-consumer relationship?

RP O-4: How can AR systems be designed to foster consumer attachment with a certain brand?

4.1.3. Support for marketing activities

As digital media platforms have revolutionized marketing practices by providing new ways to

inform, engage, learn about, sell, and provide service to customers (Lamberton & Stephen,

2016), brands are forced to build upon these technological means and target consumers more

directly. Following advances in mobile technologies, consumers often use apps that are

convenient, easy to use, interactive, and location independent (Idris et al., 2019). Given this

backdrop, the deployment of AR in marketing gives brands unprecedented opportunities to

promote their products and services (Ng & Ramasamy, 2018). Consequently, a significant stream

of research has emphasized the importance of AR technologies to boost e-marketing in several

ways (Shabani et al., 2019). Innovative marketers can capitalize on the visualization features of

AR design to create immersive brand experiences, develop more creative advertising, and allow

consumers to perceive products in novel ways (Scholz & Smith, 2016). In advertising, AR

facilitates ad campaigns (Feng & Mueller, 2019) and offers a utilitarian value perception to

consumers (Feng & Xie, 2019a). Findings from a study on the application of AR for advertising

show that users strongly agree on the perceived usefulness and informativeness of AR-based

advertising (Idris et al., 2019). Correspondingly, Phua & Kim (2018) find that AR technology

enables advertisers to create ads that improve consumers’ self-brand congruity, self-referencing,

and perceived humor. The authors argue that the possibility to place consumers' own

25
photographs alongside brand logos and other branded content results in improved brand attitude,

higher purchase intention, and positive advertising outcomes in general.

Investigating the impact of AR on consumer behavior and advertising, Feng & Xie (2018)

develop a measurement instrument to gauge the content characteristics of YouTube videos that

feature AR campaigns. Their results indicate that AR enhances the efficacy of online campaigns,

creates easy-to-understand ad content, and offers entertainment value for consumers. Brands can

harness the power of AR to develop innovative marketing tools and support the creativity of

advertising activities. The effectiveness of AR ads has the potential to inspire consumers and

generate a sense of gratification. For example, Rauschnabel, Felix, & Hinsch (2019) argue that

the use of mobile AR apps as part of the immersive consumer experience can promote

visualization, trigger new ideas, and induce inspiration. Marketers can also benefit from AR

technologies to track and target potential market segments. Due to the recording functionality in

AR technologies, AR offers brands data and metrics that were previously impossible or hard to

track, such as the number of consumers who ultimately purchase the product or service being

promoted (Feng & Mueller, 2019). The approach of tracking consumers’ purchasing histories

and patterns increases the ability of brands to quantify the impact of their advertising campaigns,

develop appealing marketing content, and create tools for monetizing the measurable actions of

AR (Liao, 2015). The increased control over user data helps marketers to better profile potential

customers, identify their preferences, and analyze specific patterns of behavior. AR can also

accelerate the innovation process and generate new product development capabilities. In this

respect, Ng & Ramasamy (2018) maintain that AR is a novel and creative method to deliver

products and services. The technology enables brands to gain valuable knowledge-based

resources that can help advertisers to boost creativity and facilitate the development of new

26
products (Feng & Xie, 2019; Vishnevskaya et al., 2017). Hence, we posit the following

questions:

RP O-5: Which AR retail marketing activities create new value for consumers?

RP O-6: How can AR retail marketing be integrated into the existing portfolio of marketing

activities?

4.1.4. Promotion of marketing competitiveness

For brands, maintaining marketing competitiveness is a strategic goal that requires the delivery

of differentiated products and the satisfaction of consumers' needs for uniqueness. According to

Lee & Wilhelm (2010), competitiveness represents the ability of the firm to design, produce, and

market products superior to those offered by rivals. Since competitiveness is a critical success

factor for business survival, brands leverage new technologies in order to enhance their business

operations (Perakakis et al., 2019) and cope with the changing structure of marketing

communications. Research in this area has maintained that AR is an effective tool that revamps

marketing activities, delivers superior consumer value, and sustains competitive advantages (Ng

& Ramasamy, 2018). As discussed earlier, the customization-driven approach facilitated by AR

technologies enables brands to develop enhanced consumer experiences (Grzegorczyk et al.,

2019) and offer psychological feelings of product ownership and control (Carrozzi et al., 2019).

AR is also regarded as a key facilitator for brands that aspire to lock in consumers through

superior customization and personalization. By providing highly customized products, brands

can reach consumers more effectively and efficiently while simultaneously boosting market

share and profitability (Ng & Ramasamy, 2018). Highly customized and personalized AR

experiences can increase consumer satisfaction, purchase intention, and the long-term

27
commitment to repurchase products and services (Aluri, 2017). From a cost perspective, AR is

viewed as a potentially affordable technology. Shabani, Munir, & Hassan (2019) argue that the

use of AR in marketing is easily accessible and hence less expensive than conventional

marketing approaches. Equally, Kostin (2018) and Carrozzi et al. (2019) note that the relatively

low adoption costs of AR applications and high-demand potential from consumers makes the

technology cost effective and well suited for marketing. Hilken et al. (2017) point out that in

addition to providing consumers with an increased sense of control and ownership, AR-based

augmentation is less costly than existing product trial services like sampling and free return

policies. However, in spite of the declining costs, the resources that are needed for developing

AR applications might still pose a barrier, especially for small and medium-sized enterprises

(Golosovskaya, 2021).

The human-centric nature of AR technologies not only helps brands to effectively understand

and learn about consumers’ needs, but also to boost confidence in product choices, optimize

transaction efficiency, and properly implement product/service customizations (van Esch et al.,

2019). In this regard, Grzegorczyk, Sliwinski, & Kaczmarek (2019) illustrate the example of the

IKEA brand, which leverages AR to increase the playfulness of purchase experiences, inspire

consumers to spend more on the brand’s offerings, and improve its reputation. As a result, AR

can substantially increase the operational efficiency of the sales workforce and help brands attain

their sales objectives. This example also illustrates that AR systems can ensure more flexible and

integrated business processes that are adaptable to the continuous changes in marketing and

technological environments. For instance, the easy navigation capabilities that characterize AR

applications can aid consumers in finding stores and familiarizing themselves with the brand

(Grzegorczyk et al., 2019). This enhances the synchronization of information and processes

28
across various sales touchpoints, helps to build up closer connections with consumers, and

attracts new potential market segments. In the hospitality industry, for example, research has

found that AR technologies contribute to a destination’s competitiveness by increasing its ability

to attract visitors through solid destination marketing campaigns (He, Wu, & Li, 2018; Park &

Stangl, 2020; Vishnevskaya et al., 2017). According to Shabani, Munir, & Hassan (2019), the

use of AR in destination marketing can strengthen the emotional connections of tourists to the

destination, increase the sales of tourism packages, create destination loyalty, and deliver

memorable tourism experiences. Therefore, AR represents a strategic differentiator (Ruyter et

al., 2018) and a possible source for marketing competitiveness, leading to the following two

inquiries:

RP O-7: How can AR help to increase retail marketing competitiveness?

RP O-8: What features of AR can help retail marketing businesses to differentiate themselves

from their competitors?

4.2. Augmented reality challenges for retail marketing

4.2.1. Technical limitations

• Privacy concerns

Although AR represents a revolutionary technology in marketing, some technical limitations

exist. Several of the reviewed studies have identified privacy as a primary concern for the

integration of AR in marketing. For example, Feng & Xie (2019) investigate consumers’

responses to virtual try-on apps and the brand sponsors of these apps. Findings indicate that users

29
who exhibit high levels of privacy concerns tend to express perceived intrusiveness and negative

impressions toward the AR app, especially when viewing themselves virtually while trying on

the product. Hilken et al. (2017) show that increasing awareness among consumers regarding

firms’ privacy practices might lessen the positive effects of AR technology in marketing.

Carrozzi et al. (2019) note that opponents of AR technology attribute the failure of AR platforms

such as Google Glass to the lack of privacy. Privacy concerns are often triggered in conditions

where consumers' private information becomes vulnerable, causing consumers to feel victimized

and lose trust in brands. van Esch et al. (2019) further emphasize that the lack of privacy may

generate discomfort and feelings of loss of control as soon as they become aware of the

monitoring functionality of AR technology. Therefore, the ability of AR to safeguard the

personal information of consumers constitutes a barrier that can intensify the reluctance of

customers to use the technology. Four major research propositions emerge:

RP C-1: How do consumer privacy concerns impact the application of AR in retail marketing?

RP C-2: What are the requirements for creating privacy-by-design AR applications for

marketing?

RP C-3: How do consumers respond to privacy-by-design AR applications?

RP C-4: In privacy-sensitive situations, how can marketers rely on AR to signal low levels of

intrusiveness?

• Limited field of view

Even though AR visualization capabilities and real-time rendering are powerful features, the

limited optical potential of AR remains problematic. For example, Zhu et al. (2008) argue that

AR devices are still hindered by a limited field of vision, meaning that the user cannot have a

30
complete view of the reality that is augmented or a full sense of presence. Similarly, Javornik

(2016) notes that the display capability of AR might hamper its high mobility due to the limited

flexibility in the AR viewing mode, which only permits movement to a certain extent. Obtaining

a high resolution of computer-generated content is demanding. This is due to the need for

sufficient recognition of the location in order to calculate the position and orientation of the

virtual content and achieve high accuracy in the augmentation (Blanco-Pons et al., 2019; Zhu,

Owen, Li, & Lee, 2008). Therefore, issues related to the accuracy of calibration, latency in the

registration, and misalignment of virtual and real-world objects might curb the potential utility of

AR in retail marketing (Feng & Mueller, 2019). Hence, we propose the following research

propositions:

RP C-5: How does a limited field of view in AR applications impact retail marketing?

RP C-6: What technical improvements of AR applications are necessary to engage the full

human field of view in marketing?

• Technological complexity

Arguably, perceived system complexity represents a key factor when making an adoption

decision (Lian et al., 2014). AR systems are comprised of hardware, additional technical

components, and sub-systems of numerous layers that are necessary to realize the interactions

between users and the AR device (Guo et al., 2019). The adoption of AR in marketing also

necessitates more efficient hardware since some applications might be energy intensive and have

an increased demand for computing power (Grzegorczyk et al., 2019). These sophisticated

requirements may erode the benefits of AR and might make the technology useless for several

retail-marketing activities. Acknowledging these limitations, Ng & Ramasamy (2018) suggest

31
that AR needs to be more flexible and adaptable in terms of user interface, storage, and

processing power. In comparison to social media, Javornik (2016) observes that there is a lack of

connectivity in current AR apps and believes that this might negatively impact consumer

engagement with brands. The author further points out that AR might not be sufficiently flexible

in circumstances where retailers offer AR apps only for in-store usage.

RP C-7: How does the complexity of the technology impact the application of AR in retail

marketing?

4.2.2. Consumer-oriented challenges

Consumer acceptance represents a key driver and indicator of technology adoption (Sathye,

1999). This implies that the introduction of a new technology in marketing is dependent on

consumers’ receptiveness, readiness, and intention to engage in activities involving technology

(van Esch et al., 2019; Yim et al., 2017). To date, there is a lack of research concerning

consumer acceptance of AR in marketing as scholars have barely discussed this topic. Carrozzi

et al. (2019) point out that customers might be reluctant to view AR holograms of products in

case they sense that these are a means of collecting their personal information for marketing

purposes. Ng & Ramasamy (2018) argue that when a technological failure is caused by social

issues (e.g., privacy concerns), a domino effect might occur, and the whole population will be

reluctant to use the specific technology. In addition, the intention to use AR might vary from one

consumer to another. Consumers who favor real shopping experiences might discontinue their

use of AR due to the inability to properly evaluate the quality of products (Feng & Mueller,

2019). Similarly, Hilken et al. (2017) observe that customers who are less prone to use the

visualization capacities of AR might end up relying on their own mental imagery, thereby

32
denying the utilitarian value of AR-based augmentation. Hopp & Gangadharbatla (2016) note

that a lack of confidence and ability to use a new technology might deter consumers from

engaging with brands that offer AR-interactive content. As a result, AR acceptance is influenced

by consumers’ existing attitudes and expectations regarding the effectiveness of AR technology.

Furthermore, a previous negative AR experience will keep consumers from using the technology

in the future. Matzler et al. (2008) refer to this as risk aversion: a situation wherein consumers

seek to avoid encountering critical uncertainties and unclear situations. In tourism research, for

example, He, Wu, & Li (2018) find that when visitors are less willing to immerse themselves in

the virtual environment, the mental imagery process may fail, resulting in an ineffective AR

experience and decreased willingness to pay. The likelihood of a negative AR experience

increases when consumers undergo social pressure, which can result from threats to personal

autonomy and privacy, and experience negative self-presentation (Hilken et al., 2019;

Rauschnabel, Felix, & Hinsch, 2019; van Esch et al., 2019). Therefore, potential psychological

risks might arise when consumers feel disappointed as a result of their consumption and

interaction with a brand in the virtual space (Rauschnabel et al., 2019). Thus, we ask:

RP C-8: Which individual consumer traits foster or hinder the adoption of AR in retail

marketing?

RP C-9: How can AR applications be designed to best consider consumers’ needs and

preferences?

4.2.3. Technological immaturity

Although the benefits of AR in marketing are widely discussed, the immaturity of the technology

and the lack of widespread commercial applications still act as a barrier to its implementation.

33
Brands looking to invest in AR face the dilemma of understanding the advantages derived from

the leveraging of AR in retail-marketing experiences (Li et al., 2020). Consequently, marketing

researchers have argued that AR is still a novel technology that is surrounded by uncertainty and

ambiguity (Grzegorczyk et al., 2019; Hopp & Gangadharbatla, 2016; Javornik, 2016b, 2016a).

This uncertainty arises from the lack of consistency among social norms (Grzegorczyk et al.,

2019), weak consumer awareness of existing AR applications (Yim et al., 2017), and insufficient

AR use cases in marketing. For example, Pantano, Rese, & Baier (2017) highlight that there is

only a small number of eyewear retailers in Germany and Italy who have already used AR to

support online and mobile shopping. Because of the embryonic nature of AR, consumers tend to

feel less confident and rather skeptical regarding the convenience and utility of AR technologies

(Scholz & Duffy, 2018). Although novelty perceptions and uncertainties could fade away with

repeated interactions with the technology (Hopp & Gangadharbatla, 2016), managers are still

hesitant to integrate AR into their marketing strategies (Scholz & Duffy, 2018). Thus, we argue

that more research is needed that considers the current state of AR technology:

RP C-10: How does the technical immaturity of AR impact its widespread retail-marketing

adoption?

RP C-11: How do consumers perceive AR technology from a technical perspective?

4.2.4. Organizational barriers

The adoption of AR in marketing can pose several organizational challenges. These are

associated with the existing business environment of brands and the need to develop new

practices when AR is deployed in marketing. Given the immaturity of the technology, marketers

may perceive the uncertainty surrounding AR implementation and the lack of information as a

34
major barrier that constrains the intention to adopt AR (Ng & Ramasamy, 2018). Likewise, the

lack of a clear and comprehensive branding theory of AR could hinder the adoption of this

emerging innovation (Rauschnabel et al., 2019), and the costs related to the implementation of

AR can slow down the diffusion of the technology. Especially for small businesses, the

perceived investment cost and uncertainty are a big deterrent of AR adoption (tom Dieck & Jung,

2017). That said, the setup costs can be high, and organizations can thus face financial

constraints during their engagement in AR projects. The lack of familiarity with AR technologies

requires the commitment of other considerable resources for training, recruitment of a skilled

workforce, and development initiatives (Guo et al., 2019; Ng & Ramasamy, 2018). Javornik

(2016) emphasizes that early forms of AR were not robust and cost effective and hence did not

achieve widespread adoption. Therefore, AR applications should be commercially viable and

affordable in order to offer superior customer value and improve brand equity (Rauschnabel et

al., 2019). Thus, we suggest a close investigation of organizations’ capabilities to successfully

integrate the new technology:

RP C-12: What organizational structures and processes foster the adoption of AR for retail

marketing?

RP C-13: What organizational structures and processes hinder the adoption of AR for retail

marketing?

Table 4 summarizes the research propositions that we derived in the preceding sections and

orders them according to the respective categories that either pose an objective or a challenge to

a company. Taken together, they provide a comprehensive framework for future research

pertaining to AR in retail marketing.

35
 Table 4. Research propositions

Objectives Category Research proposition

Enhanced consumer How do consumers perceive AR in retail marketing?
O-1 experience
Which individual consumer traits are responsible for
Enhanced consumer the adoption of AR by consumers in retail-marketing
O-2 experience situations?
Improved brand- What is the impact of AR in retail marketing on the
O-3 consumer relationship brand-consumer relationship?
Improved brand- How can AR systems be designed to foster consumer
O-4 consumer relationship attachment with a certain brand?
Support for marketing Which AR retail marketing activities create new value
O-5 activities for consumers?
Support for marketing How can AR retail marketing be integrated into the
O-6 activities existing portfolio of marketing activities?
Promotion of How can AR help to increase retail-marketing
marketing competitiveness?
O-7 competitiveness
Promotion of What features of AR can help retail-marketing
marketing businesses to differentiate themselves from their
O-8 competitiveness competitors?
Challenges Category Research proposition
How do consumer privacy concerns impact the
C-1 Technical limitations application of AR in retail marketing?
What are the requirements for creating privacy-by-
C-2 Technical limitations design AR applications for marketing?
How do consumers respond to privacy-by-design AR
C-3 Technical limitations applications?
In privacy-sensitive situations, how can marketers rely
C-4 Technical limitations on AR to signal low levels of intrusiveness?
How does a limited field of view in AR applications
C-5 Technical limitations impact retail marketing?
What are the technical improvements of AR
applications necessary to engage the full human field of
C-6 Technical limitations view in marketing?

36
 How does the complexity of the technology impact the
C-7 Technical limitations application of AR in retail marketing?
Consumer-oriented Which individual consumer traits foster or hinder the
C-8 challenges adoption of AR in retail marketing?
Consumer-oriented How can AR applications be designed to best consider
C-9 challenges consumers’ needs and preferences?
Technological How does the technical immaturity of AR impact its
C-10 immaturity widespread retail-marketing adoption?
Technological How do consumers perceive AR technology from a
C-11 immaturity technical perspective?
Organizational What organizational structures and processes foster the
C-12 barriers adoption of AR for retail marketing?
Organizational What organizational structures and processes hinder the
C-13 barriers adoption of AR for retail marketing?

5. Discussion, conclusions, and limitations

Recent advances in information technologies, which are exemplified by the proliferation of

mobile technologies, create promising opportunities for organizations to sustain their brands’

value and enhance their marketing capabilities ( Guo et al., 2010). Within this context, mobile

devices have turned into important marketing vehicles that help brands to spread their reach and

ensure a pervasive electronic presence (Varnali & Toker, 2010). As a technology with a well-

developed technological foundation, AR has emerged to support marketing activities and reshape

the ways brands interact and create value for consumers. In this paper, we have investigated the

current state of the art on the topic of AR and retail marketing by conducting an SLR and

deriving several research propositions. In total, we thoroughly analyzed 91 articles for this

purpose. Our findings illustrate that AR is still an emerging and topical research area that has

witnessed a substantial increase in interest over the past few years.

37
The application of AR in marketing was first reported in 2008, and the number of articles has

significantly increased ever since. Early AR marketing publications focus on examining the role

of AR technologies to improve the consumer experience, support marketing activities, strengthen

the brand-customer relationship, and enable marketing competitiveness. AR is a promising

technological tool for expanding and creating immersive consumer experiences that resemble

those experienced in offline stores. By engaging consumers’ senses, AR improves interactivity

and generates a strong influence on consumer responses through trust, immersion, fun, and

enjoyment. Thanks to AR’s high-quality and rich information being blended into the real world,

marketers can offer consumers a more personalized shopping experience. Moreover, AR creates

vivid memories by enriching the physical reality and endowing it to offer a holistic consumer

experience and support sensory marketing strategies. AR not only can trigger visual senses but

also form subconscious triggers that impact human perception. For example, the sensory-motor

experience of virtually touching a product often creates the feeling that the product is more

tangible than a product that is only seen (Heller et al., 2019). Therefore, future studies may

explore AR's role in adding convenience and flexibility to shopping activities by creating a

sensory experience and increasing the capabilities of consumers to imagine the use of products or

services.

As a new interactive tool, AR offers marketers numerous innovative opportunities and enables

them to create more interactive, immersive, and lifelike ads. AR represents a novel marketing

tool that helps brands effectively communicate their advertising content to consumers and

develop emotional bonds with them. Replacing conventional advertisements with AR ads can

stimulate consumer affective responses and their willingness to purchase products. Through the

use of AR, brands can intensify emotional reactions and increase their ability to attract

38
consumers. The effectiveness of AR in advertising also manifests in the benefits from free brand

endorsement because consumer immersion and engagement with the technology encourage

experience sharing and the promotion of brands to the community and social networks. The

implementation of AR in adverting and marketing campaigns revitalize consumer intention to

engage with viral brand marketing and enables companies to increase their bottom-line.

Therefore, the improved form of engagement facilitated by AR may translate into diverse

marketing metrics such as word of mouth and positive intent (Buttle, 1998; Rahman et al., 2015;

Roy et al., 2014). This finding suggests that marketers seeking to incorporate AR in their

advertising and marketing campaigns should evaluate the potential al of the technology to trigger

physiological arousal and its influence on the willingness to pay for the products shown in AR

advertising.

As marketers continuously strive to enhance engagement between consumers and brands, there is

a potential for AR to influence consumer behavior by integrating virtual objects into consumers’

perceptions of the physical world in order to increase sales, support branding, and optimize

delivery of customer service. The technology also offers promising opportunities for various

marketing and advertising activities and functions, including storytelling, cross-channel

marketing, and social media. In this regard, a fruitful research direction is to investigate the extra

dimensions of AR necessary for facilitating experience storytelling in marketing and placing

consumers at the center of a story. This is because rich media that uses storytelling has a stronger

influence on consumer experiences than those without narration (Javornik, 2016a). Given the

overall lack of a more comprehensive branding theory of AR (Rauschnabel, Felix, & Hinsch

2019), it is recommended that future researchers identify the theoretical underpinnings that

explain consumer responses to the higher media richness, narration, and storytelling wrought by

39
the use of AR in marketing. AR marketing scholars can draw on established behavioral theories

(e.g., Theory of Reasoned Action, Theory of Planned Behavior, Theory of Experienced Utility,

Persuasion Theory) to examine the beliefs, attitudes, and affects of AR in marketing, and they

can predict consumer intention to engage in AR-based marketing experience and storytelling. To

date, this direction has not been sufficiently explored and remains a pending topic in AR

marketing.

By adopting AR in marketing, firms can achieve higher efficiencies, return on investments, and

profitability, resulting in better cost-effectiveness. AR marketing can affect consumer behavior

by infusing digital information into consumers’ perceptions of the real world in order to

maximize sales revenues, support branding, and target new customer segments. AR can also be

seen as a strategic marketing tool that sustains competitive advantages due to its positive impact

on consumer satisfaction and engagement. To maximize profits, brands are required to create

interactions that foster consumer satisfaction, brand loyalty and attachment. Moreover, AR is

particularly valuable for sales and marketing strategies since increased personalization and

consumer involvement can stimulate the desire for products and provide brands with new ways

to boost the competitive advantage and widen the consumer base. In this context, future studies

should guide marketers in devising AR-based sales policies and examining how the technology

can elevate sales revenues and facilitate sales services and increase customer retention.

In addition to the above-discussed AR objectives, in this paper we also identify the types of

research methodologies that are applied in the selected publications and find a dominance of

quantitative research as well as several conceptual and qualitative papers.

The goal of our study was to provide a systematic summary and analysis of the existing literature

and the derivation of research propositions related to objectives and challenges of AR in

40
marketing, which is an important prerequisite for conceptualizing and advancing theories in this

research area. Future research is needed that further investigates which theories are especially

suitable in order to explore this topic further and how existing theories can be refined by taking

the idiosyncrasies of AR into account. A significant number of existing publications focus on

studying the impact of AR on the consumer experience and discuss how the technology can

bolster advertising, brand attachment, uniqueness, and competitiveness. Additionally, the

technical limitations of AR are discussed in the literature, as are customer-oriented challenges,

technological immaturity, and organizational barriers to AR adoption. Conceptual and review

studies were mainly used to synthesize the progress of AR in marketing.

The present study represents one of the first attempts to systematize the existing body of

academic knowledge on the applications of AR in retail marketing. The literature reveals that

previous scholarly work on AR has emphasized the specific benefits of this technology in order

to improve the consumer experience. Little attention has been paid so far to the comprehensive

literature review of studies on AR in retail marketing. In this paper, we thus strive to deliver a

timely review study that provides a snapshot of the composition of current AR research with the

goal of enriching our collective understanding of AR in retail marketing and laying the

foundation for future research. We propose a comprehensive classification of AR objectives and

challenges in marketing based on the findings from the prior literature.

A structured research agenda on AR in retail marketing will help to better understand the

marketing areas prone to enhancement by the technology. Moreover, we find that technical

limitations and lack of consumer acceptance are still problematic for widespread adoption. Other

scholars may investigate possible solutions for companies and how to increase consumers’

willingness to engage in AR experiences.

41
The theoretical inferences derived from our SLR can provide useful insights for marketing

practitioners interested in AR technologies. This especially pertains to the retailing strategies and

tactics that are likely to be affected by the increased application of AR, which will help

practitioners to gain a clear and balanced picture of what drives and hinders AR implementation

in retail marketing. In doing so, marketers will recognize the role of AR in contributing to the

evolution of new marketing practices in their organizations. Previous research has shown that

brands can benefit from AR to offer unique consumer experiences, increase their marketing

efficiencies, offer highly customized and personalized products, and build brand loyalty beyond

conventional methods. Therefore, marketers should not be discouraged by the existing barriers of

AR adoption, but instead strive to better understand the technology’s idiosyncrasies as well as

consumers’ needs in order to be able to use the former to its fullest potential.

42
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