ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea)
https://www.revistaespacios.com Pag. 101
Vol. 43 (09) 2023 • Nov-Dic • Art. 7
Recibido/Received: 07/10/2023 • Aprobado/Approved: 02/11/2023 • Publicado/Published: 30/11/2023
DOI: 10.48082/espacios-a23v44n09p07
Customer loyalty in omnichannel retail: an AI-based
literature review
Fidelización del cliente en el comercio minorista omnicanal: una revisión de la literatura
basada en IA
FAILLI, Beatrice
1
REYES, Ana L.
2
RODRÍGUEZ, Beatriz
3
Abstract
With the rise of digital transformation retail companies have adopted an omnichannel strategy, to
integrate online and offline channels and provide a seamless customer experience. The concept of
omnichannel retail has gained popularity among researchers. However, limited research explores long-
term customer satisfaction and topics such as loyalty or advocacy. This paper conducts a quantitative
and qualitative analysis, revealing emerging trends in loyalty within omnichannel retail literature.
Keywords: omnichannel retail, customer loyalty, customer experience, LDA model
Resumen
Con el auge de la transformación digital, las empresas minoristas han adoptado una estrategia
omnicanal para integrar canales en línea y fuera de línea y brindar una experiencia perfecta al cliente.
El concepto de venta minorista omnicanal ha ganado popularidad entre los investigadores. Sin embargo,
hay investigaciones limitadas que exploran la satisfacción del cliente a largo plazo y temas como la
lealtad o la promoción. Este artículo realiza un análisis cuantitativo y cualitativo, revelando tendencias
emergentes en la lealtad del cliente dentro de la literatura minorista omnicanal.
Palabras clave: retail omnicanal, fidelización de clientes, experiencia del cliente, modelo LDA
1. Introduction and theoretical framework
As digital transformation advances, consumers are increasing technology and social media usage. Consumers
who are making heavy use of digital media are bombarded by marketing communication. Companies are
leveraging the new communication opportunities brought by digitalization to be more present along the
customer journey and to build touchpoints to acquire and retain customers. However, the proliferation of
marketing channels increases the level of complexity for companies that want to promote their products online
and offline. In particular, for retailers, the pressure from digital transformation has led to what we call
‘omnichannel retail’.
1
Universidad Rey Juan Carlos. España. Email: beatrice.ffb@gmail.com
2
Universidad Rey Juan Carlos. España. Email: ana.reyes@urjc.es
3
Universidad Rey Juan Carlos. España. Email: beatriz.rodriguez@urjc.es
ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea) - Revista Espacios – Vol. 44, Nº 09, Año 2023 • Nov-Dic
FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 102
Omnichannel retail is a concept that refers to the practice of retailers to integrate multiple sales and
communication channels, online and offline, in order to offer a better customer experience (Rigby, 2011). For a
retailer, omnichannel not only means expanding and integrating sales channels, but also managing more
touchpoints for marketing and communication. An omnichannel company needs to manage both offline and
online channels in an integrated way, along the entire customer journey (Neslin, 2022).
While the majority of papers in the literature focus on the positive impact of omnichannel retail on purchases,
few articles discuss the long term impact of omnichannel marketing in retail focusing on the post-purchase phase.
Some researchers have started to put their focus on the impact of omnichannel marketing on consumers’
preference for a brand, loyalty and repurchase. Nevertheless, there is not enough focus on this area yet.
Therefore, the purpose of this study will be to conduct a literature review focused on the post-purchase phase
to investigate what is the impact of omnichannel marketing and communication on customer loyalty. In order to
do this, the authors will analyse the Web of Science database to extract articles about omnichannel retail,
customer loyalty, and advocacy. The Systematic Literature Review (SLR) approach is followed, paired with a
quantitative and a qualitative analysis, following Reyes-Menendez et al. (2020).
1.2. Omnichannel retail
The concept of omnichannel retail became popular in 2003, when the company Best Buy used this term for the
first time to describe their customer-centric approach to retail. They realised that customers were using multiple
channels to shop, and they wanted to create a seamless experience for them, no matter how they chose to shop.
In the academic literature, Rigby (2011) was the first author to give a definition to omnichannel. He described
omnichannel retail as an integrated sales experience which benefits from the advantages of physical stores and
online shopping at the same time. This definition highlights the double nature of sales channels (online and
offline) and their integration. Moreover, the author mentions the concept of ‘experience’, calling attention to
the consumer perspective.
Not only Rigby, but also other authors relate to omnichannel retail as an ‘experience’. In fact, the concept of
omnichannel not only refers to a firm’s strategy, but it also involves the customer experience. For example,
Verhoef et al (2015) defined omnichannel management as the ‘synergetic management of the numerous
available channels and customer touchpoints, in such a way that the customer experience and the performance
across channels is optimised’ (Verhoef, 2015).
Omnichannel retail has evolved from the previous concept of ‘multichannel’ retail. While in multichannel retail
the focus was mainly on the increase of sales and communication channels, in omnichannel there is a major focus
on the customer’s perspective (Beck & Rygl, 2015; Picot-Coupey et al., 2016). Based on previous research, the
omnichannel retail literature focusing on consumers has been growing in the past few years (Failli Forzoni et al.
2022). However, there is still a gap in research that investigates customer loyalty. Therefore, the present paper
will focus on analysing omnichannel strategies and marketing in retail and the way they relate to customer loyalty
and advocacy. Some studies that focus on customer loyalty in the omnichannel context have already emerged.
Therefore, we will perform an in-depth analysis of the papers that associate omnichannel and loyalty in the retail
industry.
1.3. Loyalty
Customer loyalty has been defined as a commitment to rebuy or reconsider a preferred product or service, that
leads to repeated purchase of the same brand, regardless of marketing communications from different brands
(Oliver, 1999). In the earliest definitions, loyalty was considered more from a transactional point of view, as a
repurchase intention. Based on this perspective, customer loyalty can be calculated as follows:
𝐒𝐡𝐚𝐫𝐞&𝐨𝐟&𝐖𝐚𝐥𝐥𝐞𝐭 =Amount&spent&on&brand&X
Total&amount&spend&on&category&of&brand&X&&&
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FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 103
𝐑𝐞𝐭𝐞𝐧𝐭𝐢𝐨𝐧&𝐑𝐚𝐭𝐞 =(#&customers&at&t + 1) − (#&of&new&customers)#&
#&customers&at&t = 0& ×100
Lately, loyalty has been defined more as a feeling of attachment to a product or brand, rather than simply the
action of purchasing multiple times (Casidy & Wymer, 2016). Chaudhuri and Hoolbrook (2001) explained that
loyalty can have a behavioural or attitudinal nature. Behavioural loyalty refers more to the concept of
transactional loyalty, as it occurs when a customer makes repeated purchases of the same brand or product, but
without an emotional attachment. In this case, the customer might have faced a lack of choice or impossibility
to choose a different brand. On the other hand, attitudinal loyalty is characterised by a real preference for a
product or brand, that may or may not lead to repurchase.
As this type of loyalty does not necessarily lead to purchasing a product more times, marketers have developed
the concept of “advocacy” to describe a specific situation of attachment to a brand that leads to word of mouth
instead of repeated purchase (De Regt et al., 2021). Advocacy is considered as an indicator to identify loyalty. In
fact, it demonstrates attitudinal loyalty and can be considered as a positive outcome of the interaction between
a consumer and a brand, even when the customer has not bought again for the same brand. According to
Fullerton (2011), customer advocacy is the ‘willingness of people to give strong recommendations and praise to
other consumers on behalf of a product or service supplier’. Previous research explained that customers who are
considered loyal to a brand have the willingness to endorse and recommend the brand to their friends and family
(Kotler et al., 2017).
1.4. Omnichannel loyalty
Some authors have focused on analysing loyalty in an omnichannel context. By focusing on omnichannel loyalty,
companies aim to maximise customer experience across all channels throughout the entire customer journey. In
particular, the omnichannel communication is delivered at the right time and on the right channel for each
consumer (Hemsey, 2012). With this new approach to loyalty, companies need to structure a solid omnichannel
communication strategy, focusing on the design and management of the different touchpoints that the customer
will interact with, to make sure they can build the foundations for customer loyalty since the first interactions
between brand and consumers (Homburg et. al, 2015; Ziliani & Leva, 2020). The main authors that have focused
on omnichannel retail are summarised in table 1.
Table 1
Main authors from literature review
Author
Title
Methodology
Philip Kotler,
Giuseppe Stigliano
Retail 4.0
Book
Kotler, Hermanwan,
& Setiawan, 2021
Marketing 5.0
Book
Rigby, 2011
The Future of Shopping
Book
Ziliani & Leva, 2020
Loyalty Management: From Loyalty Programs to Omnichannel
Customer Experiences
Book
Chaudhuri and
Hoolbrook, 2001
The Chain of Effects From Brand Trust and Brand Affect to Brand
Performance: The Role of Brand Loyalty
Literature review
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FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 104
Author
Title
Methodology
Homburg, Jozić, &
Kuehnl, 2015
Customer experience management: Toward implementing an
evolving marketing concept
Mixed: innovation
diffusion theory
(IDT) and survey
Casidy & Wymer,
2016
A risk worth taking: Perceived risk as moderator of satisfaction,
loyalty, and willingness-to-pay premium price
Survey
Beck & Rygl, 2015
Categorization of multiple channel retailing in Multi-, Cross-, and
Omni-Channel Retailing for retailers and retailing
Literature review
Picot-Coupey, Huré,
& Piveteau, 2016
Channel design to enrich customers’ shopping experiences:
synchronizing clicks with bricks in an omni-channel perspective -
the Direct Optic case
In-depth case
study
(ethnography)
Reyes-Menendez et
al., 2018
Understanding the Influence of Wireless Communications and Wi-Fi
Access on Customer Loyalty: A Behavioral Model System
Survey
The relationship between customer loyalty and omnichannel retail is a topic that continues to expand. In
particular, some authors have analysed how the concept of loyalty has evolved, and how it can be influenced at
every touchpoint and from the early stages of the customer experience. If an omnichannel strategy in retail can
improve the customer experience, then this concept can also have an impact on loyalty based on the quality of
the experience. The present paper presents an in-depth analysis of the existing literature that focuses on
omnichannel retail related to loyalty and/or advocacy concepts.
2. Methodology
This paper aims to perform a systematic literature review (SLR) to analyse the existing research developments in
omnichannel retail (Gerea et al., 2021). In particular, this research will focus on the role of consumer loyalty in
omnichannel retail, as this is currently an underdeveloped topic in the literature (Failli Forzoni et al., 2022).
Scholars such as Webster & Watson (2002), Stieglitz et al. (2018), and Saura (2021) agree that a theoretical
framework that validates prior research is essential to lend credibility to any type of research and to advance the
field. For this reason, the authors of this paper started from analysing existing articles that deal with omnichannel
retail, communication, loyalty, and advocacy. Then the articles were classified to identify which articles
specifically analyse the topic of loyalty related to omnichannel.
To identify relevant articles, the scientific database of Web of Science was used, as it includes articles from
several publishers and from different research fields. The search on Web of Science produced 1503 results. The
following advanced search was performed to retrieve articles related to omnichannel retail, that also included
either loyalty, advocacy, communication, or consumer-related topics:
“(TS=(retail)) AND ((TS=(omnichannel OR multichannel AND loyalty)) OR TS=(omnichannel OR multichannel AND
communication)) OR TS=(omnichannel OR multichannel AND advocacy)) OR TS=(omnichannel OR multichannel AND
consumer)”
2.1. Chronological publication analysis
By running a chronological publication report, it is evident how the interest for these topics significantly increased
in the past 10 years, as shown in Figure 1. The research in Web of Science was performed between January and
March 2023, therefore the data for this year is incomplete and this year is not included in the analysis.
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FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 105
Figure 1
Chronological report
Source: Web of Science
The number of publications related to omnichannel and consumer in the post-purchase phase (loyalty, advocacy,
communication), has grown exponentially in the past ten years, with an average growth rate of 28% between
2011 and 2022. In particular, the authors have done a deep dive on the years with the highest yearly growth rate
in publications. Year 2011 is the year with the highest growth, as the number of publications almost doubled
compared to 2010 (+94%). It is important to also highlight more recent years, such as 2019 and 2021, that have
marked a significant growth in the number of publications in this field. In 2019 there was a +45% growth
compared to 2028, and in 2021 36% more articles were published compared to 2020. The number of publications
per year is reported in table 2.
Table 2
Number of publications per year
Publication years
Record count
% of 1503
2023
18
1.20%
2022
260
17.28%
2021
243
16.15%
2020
178
11.83%
2019
154
10.23%
2018
106
7.04%
2017
86
5.71%
2016
81
5.38%
2015
53
3.52%
2014
49
3.26%
2013
37
2.46%
2012
36
2.39%
2011
33
2.19%
2010
17
1.13%
2009
26
1.73%
Source: Web of Science
The authors analysed the text of the abstract of the selected articles to identify key themes and differences
arising each year. From a text analysis performed with word cloud it can be noticed that 2010 and 2011 share
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Pag. 106
three main terms: multi-channel, online, and channel. Beyond these key terms, the abstract of the articles
written in 2010 also show ‘regulations’, ‘customers’, ‘purchase’, ‘offline’, ‘customer’ and ‘satisfaction’ as the
most mentioned words. Figure 2 and Figure 3 can be compared to see the word cloud with the main terms from
the articles published in 2010 and 2011.
In 2011, we see the word ‘customer’ or ‘consumer’ repeated more times, accounting for 7.5% of the total words
contained in the abstracts, for a total of 140 consumer-related terms. In addition, we see the rise of ‘behaviour’,
‘research’, and ‘purchase’. Therefore, it can be assumed that in 2011 there was a higher attention on the
customer journey related to multi-channel purchases. In all the articles, both in titles and abstracts, the term
‘multi-channel’ is used, as opposed to ‘omni-channel’. In fact, it was only in 2015 that the focus shifted from
multi-channel to omni-channel, to meet the consumer needs, as written by the authors Beck & Rygl.
Figure 2
Year 2010: Most popular terms
summarised in word clouds
Figure 3
Year 2011: Most popular terms summarised in word clouds
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The second period with the highest growth in authors’ interest for omnichannel retail can be observed between
2018 and 2019. As opposed to 2010 and 2011, in 2018 we see that ‘omni-channel’ is the most common term
mentioned in the abstracts. ‘Multi-channel’ is still used in 2018, but it disappears from the top terms in 2019.
The articles are often mentioning words like ‘consumer’ in both years, proving that authors’ interest in consumer
behaviour is still growing. In this period we also see the rise of terms such as ‘offline’, ‘store’ and ‘data’.
Finally, this paper observed when some keywords are in common with the years before. The terms ‘experience’
and ‘strategy’ stand out as compared to the previous years, indicating an evolution in the approach to this topic,
that is more often referred to as a strategy that companies are considering implementing. For example, Asmare
et al. (2022) specifically focuses on identifying the drivers of an omnichannel retail strategy. Gao et al. (2021)
focus on the customer experience, explaining how this concept is crucial for retailers that have to adopt an
omnichannel strategy.
2.2. PRISMA Model
This research continues with the application of the PRISMA Flow Diagram (Moher et al., 2009) to filter the results
more precisely and exclude articles that did not match the search query or did not contain an abstract, following
the approach of Reyes-Menendez et al. (2020). The initial search produced a total of 1503 results, out of which
18 written in 2023 were excluded. In fact, the objective of the analysis was to evaluate the literature also from a
quantitative point of view, counting the number of articles written every year. As the research was conducted
between January and March 2023, this year only had a small number of articles that could not be counted in the
analysis. Moreover, the authors excluded 5 other papers from the results as they were not fitting the research
topic. As a result, this analysis will be performed on a total of 1480 articles. Figure 4 shows the selection process
operated following the model.
Figure 4
PRISMA Model
2.3. Content analysis with LDA model
To analyse the content of the selected paper, Saura et al., 2021 was followed. Therefore, the authors applied the
LDA machine-based technique, which is a mathematical model based on artificial intelligence that can show the
repetition and links between keywords contained in the abstracts of the selected articles.
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FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 108
The LDA (Dirichlet’s Latent Dirichlet Assignment) model was used for topic modelling. Topic modelling is a
research technique that allows to identify the themes contained in a selection of documents, that in this case
are the articles selected from the WOS database. The LDA technique has become increasingly popular in natural
language processing (NLP) and analysis of text, as it can be applied to classify text, document and information.
The model was developed with Python and allowed to analyse the topics of the selected articles from an
observation of the relationship and the repetition of keywords. First, each paper was assigned a topic
distribution. Then, for each word in the document, a topic is selected from the topic distribution of that paper,
and then from each topic’s word distribution a keyword is identified (Kherwa & Bansal, 2018). In this research,
the LDA model has been used with the purpose to analyse the most popular keywords and topics in the selected
dataset.
3. Results and discussion
3.1. Keywords
The table below summarises the main keywords analysed with the LDA model and how frequently they were
present in the articles dataset.
‘Customer’ is the most frequent keyword, as omnichannel management is a company strategy aimed at
enhancing the customer experience. ‘Customer’ is the most frequent keyword, present in every article, as it
appears 1480 times. The synonym ‘consumer’ is also one of the most popular keywords, repeated 570 times. As
omnichannel management is a company strategy aimed at enhancing the customer experience, the aim of this
paper is to further investigate the omnichannel topic from the consumer perspective. Finding ‘consumer’ as the
most popular term confirms an accurate selection of the papers that are analysed in this SLR.
Table 3
Keyword frequency
Rank
Keyword
Frequency
1
Customer
1480
2
Channel
1437
3
Omnichannel
1153
4
Retailer
1134
5
Store
1025
6
Consumer
570
7
Experience
527
8
Research
446
9
Purchase
437
10
Shopping
427
11
Product
407
12
Technology
362
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Among the top keywords, other popular terms can be found, such as ‘channel’ (frequency=1437), ‘omnichannel’
(frequency=1153), and ‘retailer’ (frequency=1134), which are all keywords that are used to define the main topic
of this paper. Moreover, keywords like ‘experience’, ‘research’, ‘purchase’, and ‘shopping’ suggest the
relationship between omnichannel retail and the customer journey. Table 3 shows the rank of the top 12
keywords present in the articles and their frequency.
3.2. Topics coherence
After an initial observation of the most popular keywords in the selected dataset, the authors will analyse the
topics of the articles. In order to evaluate topics, a topic coherence analysis was performed. Topic coherence in
topic modelling refers to the degree to which the topics identified by the model are semantically related. The
coherence score is calculated by measuring the similarity between the words in each topic. The higher the
coherence score, the more semantically related the words in the topic are. The highest level of coherence can
be reached with 24 topics (coherence=0.3395). This means that the LDA model has identified 24 topics that are
semantically related and that make sense. These 24 topics will be analysed to restrict the research agenda and
perform the final analysis (Figure 5).
Figure 5
Coherence by number of topics
Among the 24 topics, one of more dominant topics can be identified. A dominant topic is more prevalent in a
corpus than other topics. The words that are associated with the dominant topic are more likely to appear in the
corpus than the words that are associated with other topics. The bar chart shows the topic coherence. The chart
includes the level of coherence of the top 21 topics (excluding 3 topics with the lowest coherence). Topic 2 is the
dominant topic, as it has the highest level of coherence. Topic 2 corresponds to ‘channel integration’ and it can
be considered one of the most important topics discussed in the literature analysed with this study. The main
topic is followed by topic 10 ‘customer loyalty’, and topic 13 ‘channel strategy’.
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Figure 6
Dominant topic
3.3. Topics contribution
The selected topics make different levels of contribution to the literature. Below, the table lists each topic, its
level of contribution and keywords related to the topic. The topic with the highest contribution is ‘shopping
behaviour’, followed by ‘customer management’, and ‘in-store technology’. Moreover, numerous topics refer to
consumer behaviour and channel management, suggesting how omnichannel management is a company
strategy focused on enhancing the customer experience. Table 4 summarizes the topic tag, the percentage
contribution and the main keywords related to each topic.
Table 4
Topic percentage contribution
Topic
Number
Topic Tag
Topic
Percentage
Contribution
Keywords
21
Shopping
behaviour
0.804
channel, shopping, customer, retailer, distribution, logistic, perceive,
cost, consumer, omnichannel
22
Customer
management
0.803
omnichannel, integration, customer, retailer, fashion, channel,
distribution, approach, store, market
1
In-store technology
0.797
customer, channel, omnichannel, store, trust, intention, product,
propose, technology, research
14
Product research
0.792
store, shopping, channel, retailer, showroom, consumer,
omnichannel, behaviour, customer, research
3
Purchase
determinants
0.786
store, channel, product, effect, purchase, sale, retailer, customer,
marketing, consumer
20
Customer
satisfaction
0.783
channel, omni, store, satisfaction, communication, customer, sale,
pricing, effect, perception
2
Channel
integration
0.780
retailer, customer, quality, channel, omnichannel, technology,
research, experience, company, shopping
11
Marketing strategy
0.780
channel, omnichannel, strategy, experience, retailer, consumer,
customer, business, information, marketing
23
Price sensitivity
0.778
channel, customer, search, purchase, store, quality, retailer, effect,
price, perceive
5
Customer journey
0.777
showroom, omnichannel, retailer, channel, experience, customer,
behaviour, research, return, purchase
24
Customer
relationship
0.777
omnichannel, customer, shopping, experience, perceive, channel,
research, relationship, intention, consumer
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Topic
Number
Topic Tag
Topic
Percentage
Contribution
Keywords
4
Channel
management
0.776
product, store, consumer, channel, brand, retailer, customer,
manufacturer, sale, omnichannel
8
Consumer
behaviour
0.775
channel, retailer, customer, sale, behaviour, consumer, price, coupon,
research, soil
7
Retail strategy
0.775
customer, channel, store, price, retailer, sale, purchase, effect,
manufacturer, omnichannel
6
Shopping
experience
0.774
customer, integration, omnichannel, channel, experience, retailer,
shopping, perceive, store, cx
13
Channel strategy
0.773
customer, distribution, channel, store, product, company, technology,
framework, omnichannel, experience
10
Customer loyalty
0.773
bop, retailer, omnichannel, customer, channel, experience, loyalty,
integration, store, shopper
17
Experience
management
0.771
retailer, channel, customer, omnichannel, shopping, store, design,
brand, product, purchase
12
Purchase intention
0.769
retailer, omnichannel, store, price, technology, channel, shopping,
customer, strategy, intention
19
eCommerce
strategy
0.764
commerce, retailer, customer, experience, pricing, technology,
shopping, channel, lsq, strategy
9
Omnichannel retail
0.764
retailer, customer, store, omnichannel, experience, commerce,
return, channel, purchase, fashion
16
Omnichannel
operations
0.762
channel, customer, marketing, retailer, omni, fulfilment, omnichannel,
brand, store, consumer
18
Omnichannel
returns
0.755
customer, segment, store, omnichannel, return, information, product,
behaviour, experience, consumer
15
Customer
engagement
0.746
customer, omnichannel, channel, engagement, technology, user,
retailer, brand, information, integration
3.4. Clusters of topics
After listing all the topics and their percentage contributions, the authors analysed the distance between topics,
called ‘inter-topic distance’. Each bubble represents one topic, which is indicated with the number and name of
the table above. Finally, by analysing the keywords of each topic and the position in the chart, three clusters of
topics can be identified: (1) Company strategy; (2) Customer experience; (3) Omnichannel management.
The cluster identified as ‘company strategy’ contains the topics with the highest distance from other topics. In
fact, these themes are more related to high-level retail, marketing, or product strategy. Most topics related to
consumers have a very little inter-topic distance, and their position is also very close to omnichannel-related
topics. The two clusters of ‘omnichannel management’ and ‘customer experience’ are extremely close and
almost overlapping with each other. It can be stated that the two topics are part of an entire large topic, where
the boundaries between omnichannel management and customer experience are blurred. An omnichannel
strategy for retailers seems to be essential for companies that want to ensure a positive experience for their
customers. The topics of customer loyalty (6) and shopping experience (10) are overlapping with each other and
in between the cluster of customer experience and omnichannel management. This suggests that the paper
analysed by the authors often finds loyalty and shopping experience as two correlated topics. However, loyalty
is at the extreme of the chart, a factor that proves how this concept is still not investigated in relationship with
the omnichannel retail strategy, but rather with the shopping experience or the customer management strategy
in general. In addition, it can be observed how the topics in the company strategy cluster (topics 23, 3, 14, 17,
11) are the most prominent themes in the corpus of the analysed articles. None of these themes focuses on the
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consumer perspective. These five most prominent themes are mainly related to the internal organisational
aspects of a company, indicating that despite the increasing popularity in research that focuses on consumers,
the literature around omnichannel retail is still centred on business-related topics. Figure 7 showcases the
clusters of topics.
Figure 7
Inter-topic distance map
3.5. Most salient terms
The most salient terms by frequency were analysed to better understand the details of the topics identified in
the articles selected. The most salient term is ‘distribution’, followed by ‘integration’ and ‘loyalty’. Therefore, the
concept of loyalty is arising as the third most salient term among the articles selected. The terms ‘logistics’,
‘manufacturer’, and ‘return’ are also among the most salient terms, suggesting that several papers in the
literature still focus on company-centric and operational concepts, rather than customer-centric themes such as
loyalty. Figure 8 ranks the top-30 most salient terms by frequency.
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FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 113
Figure 8
Top-30 Most Salient Terms
4. Conclusions
This research had the objective to analyse the current literature that focuses on consumer loyalty in the field of
omnichannel retail. A systematic literature review was carried out with a qualitative and quantitative analysis.
The research methodology started with a chronological analysis of existing papers in the database Web of
Science. The chronological report showed an exponentially growing trend in the field of omnichannel retail
related to loyalty. To perform the SLR, the papers were filtered according to the PRISMA model, to only examine
relevant papers. After applying the filter criteria, 1480 articles were selected as the most relevant ones. The study
continues with the analysis of the content of the chosen papers with the LDA model. The LDA model was used
to perform topic modelling, in order to extract insights that would be difficult or impossible to identify manually
in a large dataset. This research method allowed the authors to identify the most important themes contained
in the corpus of articles about omnichannel retail and loyalty. The analysis reported results about keywords and
topics contained in the corpus. First of all, the most common keywords of the articles were identified: customer,
channel, omnichannel, and retailer. Then, the topics were examined to find the following details: number of
topics with the highest coherence, topic coherence ranking, topic percentage contribution ranking, clusters of
topics, and most salient terms. A number of 24 topics were analysed within the database, as this is the amount
of topics with the highest level of coherence. In terms of coherence, the main topics are channel integration
(topic 2), customer loyalty (topic 10), and channel strategy (topic 13). The topics that make the largest percentage
contribution in the dataset are shopping behaviour (topic 21), customer management (topic 22) and in-store
technology (topic 1). Subsequently, the topics were analysed altogether, to understand the correlation between
topics and to identify clusters of topics in an inter-topic distance map. Three clusters were identified: company
strategy, customer experience, and omnichannel management. The inter-topic distance map showed a higher
distance of the company strategy cluster from the other two clusters. On the other hand, the clusters of customer
experience and omnichannel management seem to be overlapping with each other, forming one large cluster
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FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
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where topics are really close to each other and even intersecting in many cases. Finally, the study shows the most
salient terms of the corpus: distribution, integration, and loyalty. Therefore, loyalty emerges among the topics
with the highest coherence and among the most salient terms. In the inter-topic distance map, loyalty is almost
at the extreme of the chart, showing an overlap with shopping experience, in the customer experience cluster,
but quite close to the omnichannel management cluster. Table 5 below summarises the main concepts that arise
from this paper.
Table 5
Key findings
Key metrics
Result
Observations
Most
popular
keywords
Customer
Channel
Omnichannel
Retailer
Loyalty is not listed among the keywords. This means that although
this topic is mentioned in the literature, it is not the central theme
of the articles.
Dominant
topics
Channel integration (T2)
Customer loyalty (T10)
Channel strategy (T13)
Two out of the three most dominant topics are related to the
concept of “channel”. This means that the majority of topics in this
field still deal with omnichannel retail from a company-centric
point of view.
Topics with
highest
percentage
contribution
Shopping behaviour (T21)
Customer management (T22)
In-store technology (T1)
The presence of in-store technology among these topics suggests
how technology is at the basis of omnichannel management. The
other two terms are related to the customer, suggesting that some
researchers are taking into consideration the customer experience
when discussing omnichannel retail.
Clusters of
topics
Company strategy
Customer experience
Omnichannel management
These clusters suggest the three main themes to which the topics
belong. Omnichannel management is therefore a result of a mix
between company-related topics and consumer-related subjects.
This finding is coherent with Rigby definition of omnichannel,
where he highlights two main concepts: the channel and the
customer.
Most salient
terms
Distribution
Integration
Loyalty
Logistics
Manufacturer
Return
The search query on Web of Science included omnichannel and
loyalty to find relevant papers. Therefore, it is normal to find
loyalty among the most salient terms. However, other terms
suggest that the focus of the omnichannel literature is still leaning
towards company-related topics such as distribution, integration,
logistics, etc.
References
Bauerová, R., & Braciníková, V. (2021). Customer’s Choice of Purchasing Channel: Do Channel Characteristic,
Brand, and Loyalty Matter When Shopping in Hybrid Retailers? Sustainability, 13(5), 2453.
https://doi.org/10.3390/su13052453
Beck, N., & Rygl, D. (2015). Categorization of multiple channel retailing in Multi-, Cross-, and Omni-Channel
Retailing for retailers and retailing. Journal of Retailing and Consumer Services, 27, 170–178.
https://doi.org/10.1016/j.jretconser.2015.08.001
ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea) - Revista Espacios – Vol. 44, Nº 09, Año 2023 • Nov-Dic
FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 115
Brakus, J. J., Schmitt, B. H., & Zarantonello, L. (2009). Brand Experience: What is It? How is it Measured? Does it
Affect Loyalty? Journal of Marketing, 73(3), 52–68. https://doi.org/10.1509/jmkg.73.3.052
Casidy, R., & Wymer, W. (2016). A risk worth taking: Perceived risk as moderator of satisfaction, loyalty, and
willingness-to-pay premium price. Journal of Retailing and Consumer Services, 32, 189–197.
https://doi.org/10.1016/j.jretconser.2016.06.014
Chang, Y. P., & Li, J. (2022). Seamless experience in the context of omnichannel shopping： scale development
and empirical validation. Journal of Retailing and Consumer Services, 64, 102800.
https://doi.org/10.1016/j.jretconser.2021.102800
Chaudhuri, A., & Holbrook, M. (2001). The Chain of Effects From Brand Trust and Brand Affect to Brand
Performance: The Role of Brand Loyalty. Journal of Marketing, 65, 81–93.
https://doi.org/10.1509/jmkg.65.2.81.18255
Christoforou, T., & Melanthiou, Y. (2019). The Practicable Aspect of the Omni-Channel Retailing Strategy and Its
Impact on Customer Loyalty. In A. Thrassou, D. Vrontis, Y. Weber, S. M. R. Shams, & E. Tsoukatos (Eds.),
The Synergy of Business Theory and Practice (pp. 239–260). Springer International Publishing.
https://doi.org/10.1007/978-3-030-17523-8_11
Cotarelo, M., Calderón, H., & Fayos, T. (2021). A further approach in omnichannel LSQ, satisfaction and
customer loyalty. International Journal of Retail & Distribution Management, 49(8), 1133–1153.
https://doi.org/10.1108/IJRDM-01-2020-0013
Cuesta-Valiño, P., Gutiérrez-Rodríguez, P., Núnez-Barriopedro, E., & García-Henche, B. (2023). Strategic
orientation towards digitization to improve supermarket loyalty in an omnichannel context. Journal of
Business Research, 156, 113475. https://doi.org/10.1016/j.jbusres.2022.113475
De Regt, A., Plangger, K., & Barnes, S. J. (2021). Virtual reality marketing and customer advocacy: Transforming
experiences from story-telling to story-doing. Journal of Business Research, 136, 513–522.
https://doi.org/10.1016/j.jbusres.2021.08.004
Failli Forzoni, B., Reyes-Menendez, A., & Herráez, B. (2022). Evaluating the Benefits of Omnichannel Retail: A
Systematic Literature Review Focused on Consumers (pp. 176–203). https://doi.org/10.4018/978-1-6684-
3430-7.ch010
Fang, J., Liu, H., Li, Y., & Cai, Z. (2021). Retaining customers with in-store mobile usage experience in omni-
channel retailing: The moderating effects of product information overload and alternative attractiveness.
Electronic Commerce Research and Applications, 46, 101028.
https://doi.org/10.1016/j.elerap.2020.101028
Flacandji, M., & Vlad, M. (2022). The relationship between retailer app use, perceived shopping value and
loyalty: The moderating role of deal proneness. International Journal of Retail & Distribution Management,
50(8/9), 981–995. https://doi.org/10.1108/IJRDM-10-2021-0484
Frasquet, M., Miquel, M. J., & Mollá, A. (2017). Complaining at the Store or Through Social Media: The
Influence of the Purchase Channel, Satisfaction, and Commitment. In F. J. Martínez-López, J. C. Gázquez-
Abad, K. L. Ailawadi, & M. J. Yagüe-Guillén (Eds.), Advances in National Brand and Private Label Marketing
(pp. 87–94). Springer International Publishing. https://doi.org/10.1007/978-3-319-59701-0_10
Fullerton, G. (2011). Creating advocates: The roles of satisfaction, trust and commitment. Journal of Retailing
and Consumer Services, 18, 92–100. https://doi.org/10.1016/j.jretconser.2010.10.003
ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea) - Revista Espacios – Vol. 44, Nº 09, Año 2023 • Nov-Dic
FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 116
Hänninen, M., Kwan, S. K., & Mitronen, L. (2021). From the store to omnichannel retail: Looking back over
three decades of research. The International Review of Retail, Distribution and Consumer Research, 31(1),
1–35. https://doi.org/10.1080/09593969.2020.1833961
Herhausen, D., Binder, J., Schoegel, M., & Herrmann, A. (2015). Integrating Bricks with Clicks: Retailer-Level and
Channel-Level Outcomes of Online–Offline Channel Integration. Journal of Retailing, 91(2), 309–325.
https://doi.org/10.1016/j.jretai.2014.12.009
Herhausen, D., Kleinlercher, K., Verhoef, P. C., Emrich, O., & Rudolph, T. (2019). Loyalty Formation for Different
Customer Journey Segments. Journal of Retailing, 95(3), 9–29.
https://doi.org/10.1016/j.jretai.2019.05.001
Hermes, A., & Riedl, R. (2021). Dimensions of Retail Customer Experience and Its Outcomes: A Literature
Review and Directions for Future Research. In F. F.-H. Nah & K. Siau (Eds.), HCI in Business, Government
and Organizations (Vol. 12783, pp. 71–89). Springer International Publishing. https://doi.org/10.1007/978-
3-030-77750-0_5
Homburg, C., Jozić, D., & Kuehnl, C. (2015). Customer experience management: Toward implementing an
evolving marketing concept. Journal of the Academy of Marketing Science, 45.
https://doi.org/10.1007/s11747-015-0460-7
Huré, E., Picot-Coupey, K., & Ackermann, C.-L. (2017). Understanding omni-channel shopping value: A mixed-
method study. Journal of Retailing and Consumer Services, 39, 314–330.
https://doi.org/10.1016/j.jretconser.2017.08.011
Ieva, M., & Ziliani, C. (2018a). Mapping touchpoint exposure in retailing: Implications for developing an
omnichannel customer experience. International Journal of Retail & Distribution Management, 46(3), 304–
322. https://doi.org/10.1108/IJRDM-04-2017-0097
Ieva, M., & Ziliani, C. (2018b). Mapping touchpoint exposure in retailing: Implications for developing an
omnichannel customer experience. International Journal of Retail & Distribution Management, 46.
https://doi.org/10.1108/IJRDM-04-2017-0097
Kang, J., Majer, M., & Kim, H.-J. (2019). Empirical Study of Omnichannel Purchasing Pattern with Real Customer
Data from Health and Lifestyle Company. Sustainability, 11(24), 7185.
https://doi.org/10.3390/su11247185
Kherwa, P., & Bansal, P. (2018). Topic Modeling: A Comprehensive Review. ICST Transactions on Scalable
Information Systems, 7, 159623. https://doi.org/10.4108/eai.13-7-2018.159623
Klede-Schnabel, W., & Bug, P. (n.d.). Customer Loyalty Programs in Fashion Retail – A Change from
Multichannel to Omnichannel.
Le, A. N. H., & Nguyen-Le, X.-D. (2021). A moderated mediating mechanism of omnichannel customer
experiences. International Journal of Retail & Distribution Management, 49(5), 595–615.
https://doi.org/10.1108/IJRDM-02-2020-0054
Li, R., & Li, Y. (n.d.). Cross-Channel Integration and Customer Retention in Omnichannel Retailing: The Role of
Retailer Image and Alternative Attractiveness.
Li, Y., Liu, H., Lim, E. T. K., Goh, J. M., Yang, F., & Lee, M. K. O. (2018). Customer’s reaction to cross-channel
integration in omnichannel retailing: The mediating roles of retailer uncertainty, identity attractiveness,
and switching costs. Decision Support Systems, 109, 50–60. https://doi.org/10.1016/j.dss.2017.12.010
ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea) - Revista Espacios – Vol. 44, Nº 09, Año 2023 • Nov-Dic
FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 117
Long, L. (2022). Effective first-party data collection in a privacy-first world. 7.
Marketing 5.0—Kotler Philip; Kartajaya Hermawan; Setiawan Iwan | Libro Hoepli 09/2021—HOEPLI.it. (n.d.).
www.hoepli.it. Retrieved 11 August 2023, from https://www.hoepli.it/libro/marketing-
50/9788836005567.html
Nah, F. F.-H., & Siau, K. (Eds.). (2021). HCI in Business, Government and Organizations: 8th International
Conference, HCIBGO 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event,
July 24–29, 2021, Proceedings (Vol. 12783). Springer International Publishing.
https://doi.org/10.1007/978-3-030-77750-0
Natarajan, T., & Veera Raghavan, D. R. (2023). How integrated store-service quality promotes omnichannel
shoppers’ word-of-mouth behaviors: The moderating role of perceived relationship investment and the
shopper’s perceived value. The TQM Journal. https://doi.org/10.1108/TQM-12-2022-0364
Naushan, H. (2020, December 4). Topic Modeling with Latent Dirichlet Allocation. Medium.
https://towardsdatascience.com/topic-modeling-with-latent-dirichlet-allocation-e7ff75290f8
Neslin, S. A. (2022). The omnichannel continuum: Integrating online and offline channels along the customer
journey. Journal of Retailing, 98(1), 111–132. https://doi.org/10.1016/j.jretai.2022.02.003
Norbert, B., & Rygl, D. (2015). Categorization of multiple channel retailing in Multi-, Cross-, and Omni-Channel
Retailing for retailers and retailing. Journal of Retailing and Consumer Services, 27, 170–178.
https://doi.org/10.1016/j.jretconser.2015.08.001
Omar, S., Mohsen, K., Tsimonis, G., Oozeerally, A., & Hsu, J.-H. (2021). M-commerce: The nexus between
mobile shopping service quality and loyalty. Journal of Retailing and Consumer Services, 60, 102468.
https://doi.org/10.1016/j.jretconser.2021.102468
Pagani, M., Racat, M., & Hofacker, C. F. (2019). Adding Voice to the Omnichannel and How that Affects Brand
Trust. Journal of Interactive Marketing, 48, 89–105. https://doi.org/10.1016/j.intmar.2019.05.002
Pangarkar, A., Arora, V., & Shukla, Y. (2022). Exploring phygital omnichannel luxury retailing for immersive
customer experience: The role of rapport and social engagement. Journal of Retailing and Consumer
Services, 68, 103001. https://doi.org/10.1016/j.jretconser.2022.103001
Picot-Coupey, K., Huré, E., & Piveteau, L. (2016). Channel design to enrich customers’ shopping experiences:
Synchronizing clicks with bricks in an omni-channel perspective - the Direct Optic case. International
Journal of Retail & Distribution Management, 44(3). https://doi.org/10.1108/IJRDM-04-2015-0056
Quach, S., Barari, M., Moudrý, D. V., & Quach, K. (2022). Service integration in omnichannel retailing and its
impact on customer experience. Journal of Retailing and Consumer Services, 65, 102267.
https://doi.org/10.1016/j.jretconser.2020.102267
Rahman, S. M., Carlson, J., Gudergan, S. P., Wetzels, M., & Grewal, D. (2022). Perceived Omnichannel Customer
Experience (OCX): Concept, measurement, and impact. Journal of Retailing, 98(4), 611–632.
https://doi.org/10.1016/j.jretai.2022.03.003
Retail 4.0. (n.d.). Electa Mondadori. Retrieved 11 August 2023, from
https://www.mondadorielecta.it/libri/retail-4-0-giuseppe-stigliano/
ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea) - Revista Espacios – Vol. 44, Nº 09, Año 2023 • Nov-Dic
FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 118
Reyes-Menendez, A., Palos-Sanchez, P. R., Saura, J. R., & Martin-Velicia, F. (2018a). Understanding the
Influence of Wireless Communications and Wi-Fi Access on Customer Loyalty: A Behavioral Model System.
Wireless Communications and Mobile Computing, 2018, 1–16. https://doi.org/10.1155/2018/3487398
Reyes-Menendez, A., Palos-Sanchez, P. R., Saura, J. R., & Martin-Velicia, F. (2018b). Understanding the
Influence of Wireless Communications and Wi-Fi Access on Customer Loyalty: A Behavioral Model System.
Wireless Communications and Mobile Computing, 2018, 1–16. https://doi.org/10.1155/2018/3487398
Salvietti, G., Ziliani, C., Teller, C., Ieva, M., & Ranfagni, S. (2022). Omnichannel retailing and post-pandemic
recovery: Building a research agenda. International Journal of Retail & Distribution Management, 50(8/9),
1156–1181. https://doi.org/10.1108/IJRDM-10-2021-0485
Saura, J., Reyes-Menendez, A., Matos, N., & Correia, M. (2021). Identifying Startups Business Opportunities
from UGC on Twitter Chatting: An Exploratory Analysis. Journal of Theoretical and Applied Electronic
Commerce Research, 16, 1929–1944. https://doi.org/10.3390/jtaer16060108
Sheth, J. N. (2021). Future of brick and mortar retailing: How will it survive and thrive? Journal of Strategic
Marketing, 29(7), 598–607. https://doi.org/10.1080/0965254X.2021.1891128
Song, H. G., & Jo, H. (2023). Understanding the Continuance Intention of Omnichannel: Combining TAM and
TPB. Sustainability, 15(4), 3039. https://doi.org/10.3390/su15043039
Souiden, N., Ladhari, R., & Chiadmi, N.-E. (2019). New trends in retailing and services. Journal of Retailing and
Consumer Services, 50, 286–288. https://doi.org/10.1016/j.jretconser.2018.07.023
Stieglitz, S., Mirbabaie, M., Ross, B., & Neuberger, C. (2018). Social media analytics – Challenges in topic
discovery, data collection, and data preparation. International Journal of Information Management, 39,
156–168. https://doi.org/10.1016/j.ijinfomgt.2017.12.002
Timoumi, A., Gangwar, M., & Mantrala, M. K. (2022). Cross-channel effects of omnichannel retail marketing
strategies: A review of extant data-driven research. Journal of Retailing, 98(1), 133–151.
https://doi.org/10.1016/j.jretai.2022.02.008
Tyrväinen, O., Karjaluoto, H., & Saarijärvi, H. (2020a). Personalization and hedonic motivation in creating
customer experiences and loyalty in omnichannel retail. Journal of Retailing and Consumer Services, 57,
102233. https://doi.org/10.1016/j.jretconser.2020.102233
Tyrväinen, O., Karjaluoto, H., & Saarijärvi, H. (2020b). Personalization and hedonic motivation in creating
customer experiences and loyalty in omnichannel retail. Journal of Retailing and Consumer Services, 57,
102233. https://doi.org/10.1016/j.jretconser.2020.102233
Urbaitytė, V., & Ulbinaitė, A. (2020, June 16). Framework for evaluating the relationship between the
omnichannel online sales approach and performance outcome in the case of niche products. 11th
International Scientific Conference „Business and Management 2020“, Vilnius Gediminas Technical
University, Lithuania. https://doi.org/10.3846/bm.2020.563
Webster, J., & Watson, R. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS
Quarterly, 26. https://doi.org/10.2307/4132319
Xie, C., Chiang, C.-Y., Xu, X., & Gong, Y. (2023). The impact of buy-online-and-return-in-store channel
integration on online and offline behavioral intentions: The role of offline store. Journal of Retailing and
Consumer Services, 72, 103227. https://doi.org/10.1016/j.jretconser.2022.103227
ISSN-L: 0798-1015 • eISSN: 2739-0071 (En línea) - Revista Espacios – Vol. 44, Nº 09, Año 2023 • Nov-Dic
FAILLI, Beatrice et al. «Customer loyalty in omnichannel retail: an AI-based literature review»
Pag. 119
Yao, P., Sabri, M. F., Osman, S., Zainudin, N., & Li, Y. (2023). Consumers’ Continued Intention to Use Online-to-
Offline (O2O) Services in Omnichannel Retail: Differences between To-Shop and To-Home Models.
Sustainability, 15(2), 945. https://doi.org/10.3390/su15020945
Yokoyama, N., Azuma, N., & Kim, W. (2023). The impact of e-retail usage on relative retail patronage formation.
International Journal of Retail & Distribution Management, 51(13), 16–32. https://doi.org/10.1108/IJRDM-
04-2022-0142
Ziliani, C., & Ieva, M. (2019). Loyalty Management: From Loyalty Programs to Omnichannel Customer
Experiences (1st edition). Routledge.
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