Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Review Article: 2022 Vol: 26 Issue: 3

Customer Experience and Its Outcome Measures: A Meta-Analytic Approach

Kishor Chandra Sahu, Aligarh Muslim University

Mohammed Naved Khan, Aligarh Muslim University

Krishna Das Gupta, Xavier Institute of Management

Citation Information: Chandra Sahu, K., Naved Khan, M., & Das Gupta, K. (2022). Customer experience and its outcome measures: a meta-analytic approach. Academy of Marketing Studies Journal, 26(3), 1-14.


Insight into the major customer experience outcomes can enable the retailers to design appropriate customer experience strategies. The purpose of the study is to find out the significant consequences of customer experience in a retail shopping environment. A systematic literature review was done to identify the relevant studies capturing outcome measures of customer experience. After careful screening, the shortlisted studies were coded. Statistical analysis was conducted on all of those to calculate the combined effect size by using the effect size metric of all the studies. A meta-analysis of all the studies with correlation coefficient as the effect size determined that customer satisfaction, purchase intention, customer loyalty, and brand equity are the significant consequences of customer experience. The study examined that the retail environment and culture moderate the strength of the relationships.


Customer Experience, Customer Satisfaction, Meta-Analysis, Retail, Systematic Review.


The Perspective of Experience: Central to Marketing

Building foundation for customer-centered culture and the improvement and innovation is important in creating the Customer Experience Return on Investment (CX ROI). Customer-centric businesses are 60% more profitable than non-customer-centric businesses, and brands that provide outstanding customer service generate 5.7 times more revenue than competitors who fall short (Morgan, 2020).

More than 30 years of study in experiential consumption, Consumer Experience (CX) has attracted a significant amount of interest among academics and practitioners. Scholars and marketers describe CX to be the crux for creating holistic customer value, achieving differentiation and sustainable competitive advantage. The gradual economic progression from agrarian to products to services design to experience provided a sound rationale for accentuating scholarly research in CX. The concept of marketing has matured since production and product orientation era in the 1950s and 1960s to a sales orientation (in the 1970s) and recently, to market and customer orientations, until it assumed a holistic, relational approach, involving all the company stakeholders. Post-modern society is all about the service sector attributable to indispensability in value creation and services dominant logic. The contemporary business focuses on building enduring relationships with customers and services that offer a perfect platform to achieve this bonding. Customer relationship is an outcome of customer satisfaction of experience rather than that of core services alone. According to Toffler, "We will become the first civilization in history to use highly advanced technology to manufacture more transient and, together, the most durable products: the human experience" because there is nothing left to buy for consumers other than what they already possess, and they are still wondering: "What can I try that I have not tried yet?". This depicts postindustrial society is the economy of experiences where customers will be increasingly seeking value in the form of tangible, durable, and co-created experiences.

In today's retailing environments the main objective of the retailers is to create an enriching experience. Retailers around the world have accepted the concept of CX and they are making marketing strategies to ensure the customers get a positive experience. Today's consumers need, not only satisfaction from the product characteristics but also experiences which are memorable. The consumers, who get a memorable experience, tend to share the experience with their peers, friends, or family members. This, in turn, affects the satisfaction and future behavioral intentions of the customers. Creating a unique experience for consumers gives a competitive advantage. From this, one can sense that it is very critical for a retailer to investigation into how the experience impacts the post-product consumption.

Recently the academicians and researchers have taken a deep interest in the impact of experiences on the outcome variables such as customer satisfaction, behavioral intentions. Since customer experience is a multi-dimensional construct, few studies have tried to measure the overall effect of CX on the post-purchase behavior and few other studies have considered the impact of different components of experience on consumer behavior. Though there have been many studies that focus on the customer experience, from a managerial perspective, an in-depth understanding of the effect of CX outcomes is desirable. The present study will address the two research questions: a) what are the critical outcomes of customer experience in the retail shopping environment? b) Do the outcomes differ in online and offline retail environments and culture?

After searching the extant literature authors have identified seventeen studies that consist of quantitative data for performing a meta-analysis. The common variables from these 39 studies are Customer Experience (CX), Customer Satisfaction (CSAT), Customer Loyalty (CLO), purchase intention (PI), and Brand Equity (BE). The study also investigates how the retail environments such as online and offline and the country culture such as eastern and western culture affects the strength of relationship between the CX and customer satisfaction, purchase intention, loyalty and brand equity.

The rest of the study is put forward in three sections. Section 1 shows the literature review for the customer experience and its consequence variables. Section 2 describes the methodology adopted for the analysis. The findings and the results of the meta-analysis are explained in section 3. The discussion of the results and its implications are described in the last section.

Literature Review

Customer Experience and Management

Customer experience is the response of the customers to direct or indirect contact with a firm. The various touch points are the contact points with the product or the service provided by the firm where the experience is collected. In the phenomenal growth of the digital retail in India (which is estimated to reach 175million in 2020) and in the ever-competitive retail market, customer experience has emerged as one of the important differentiators for the sustenance of a firm. This has attracted both the academia and industry for a deep dive into the customer-focused concept and practice. The importance of customer experience is highlighted in luxury consumption activities as well (Atwal & Wiliams, 2017). Practitioners have begun appraising Customer Experience Management (CEM) as one of the most promising management approaches for meeting marketing challenges. For customer experience is an important driver of commercial success and competitive advantage. There is a certain degree of unanimity concerning customer experience among academics and practitioners agree that focusing on customer experience is positive and can create a unique and sustainable advantage for any company over time.

Customer Experience: A Competitive Advantage

Research into customer experience has a long history. Since the last three decades, the study of CX has been an important research topic. Many researchers have approached CX from a different perspective. Hirsch attempted from a cultural industry perspective, whereas approached from the fantasy, imagery, and multi-sensory field. Experiences are perceived internally and very much is individual in nature for every customer and it requires direct involvement of the participant. Expanded this concept by introducing the Experience Economy. The experience economy is growing fast in the global market and the organizations and researchers must recognize this as the driving force for customer satisfaction.

The retail landscape is populated by the pure players and the multi-channel players, which forces the retailers to understand the customer experience across the channels. In a multi-channel context, the customer experience is a cumulative result of the interaction of the customer across channels. When companies look to develop a competitive advantage, they start focusing on customers. If we look at the present scenarios, as there are more and more contact points between a firm and the customers, there is a definite need to focus on the variety of experiences born from them.

With the fast-changing digital environment and the technologies converging, the firms are using technology to provide a smarter platform where the retailers and clients are connected to achieve better customer experience.

There have been subsequent development and contributions to customer experience research on concepts such as customer buying behavior, customer satisfaction, and loyalty, service quality, customer engagement among the few areas.

Extant research in the last two decades in customer experience, service experience, and brand experience has been carried out in versatile service domain testing interrelationships CX and its numerous consequences.

A study on the US airline customers suggests that the customer experience factors impact strongly on the service purchase frequency. An examination of Australian retail shoppers specifically on the internet-mediated or connected technology environment revealed that the customer experience has a positive direct relationship with customer satisfaction. Several authors have considered the effects of customer experience on customer satisfaction (Bhattacharya et al., 2019) purchase intention (Bleier et al., 2019; Bhattacharya et al., 2019) customer loyalty, and brand equity. Table 1 shows a summary of all the consequences of customer experience. It shows the key consequence variables: purchase intention, loyalty, customer satisfaction, brand equity, trust, and word of mouth. It shows that most of the studies are from USA and China.

Table 1
Publications (Outcomes Of Customer Experience)
Author Outcome Variables Country Year of Publication Name of the Journal
Bleiere Customer purchase intention USA 2019 Journal of Marketing
Bhattacharya Customer satisfaction, purchase intention India 2019 Journal of Global Marketing
Bustamante & Rubio Satisfaction Spain 2017 Journal of Service Management
Hepola & Karjaluoto Brand equity Finland 2017 Journal of Product & Brand Management

Theoretical Background and Research Hypotheses

Purchase intention

Behavioral intention is a reliable predictor of actual behaviour, according to the Theory of Reasoned Action, the Theory of Planned Behavior, and the Technology Acceptance Model. The total shopping experience influences online repurchase intention, which is defined as the "re-use of the online channel to buy from a certain store". The Theory of Reasoned Action (TRA) states that behavioral intentions formed through the attitude towards a behavior and subjective norms lead to the actual behavior given the availability of resources and opportunities. Based upon TRA, purchase intentions are often used to predict the actual behavior. Prior studies have identified a positive relationship between purchase intentions and purchase behavior. Five Virtual Experiential Marketing (VEM) elements (sense, interaction, pleasure, flow, community relationship) affect the customers' purchase intention from a website. The marketing experience develops a positive attitude that leads to purchase intention. Well supported by a study by Shim et al. (2001), the study claims that the five elements (VEM) appeal to the customer's emotions to create a desired response, such as strengthening his purchase intention.

Pleasant customer in-shop emotions such as excitement and joy can contribute to a positive in-store customer shopping experience. It has been found that the in-store emotions of customers influence the likelihood of future patronage and the emotions experienced affect customer choice and preferences. Customer's interactions with staff members, store atmospherics also affect the customer both cognitively and emotionally and lead to purchase intention.

Many researchers have studied on the effect of customer experience on the purchase intentions: Social presence of a website can increase purchase intentions, sensory appeal can affect purchase intentions, visual elements such as larger product images can increase purchase intentions. The outcome variable "online repurchase intention" is included by, who found evidence of a link between online buying experience, online shopping satisfaction, and online repurchase intention. Grounding on the above literature we can hypothesize that purchase intention is influenced by customer experience.

H1: There is a positive relationship between customer experience and purchase intention.

Customer satisfaction

Two key outcomes of CE that are of great interest to retail managers are satisfaction and loyalty. Drawing upon the two major theories, "cognitive-affect-behaviour" model and the "stimulus-organism response" model, it can be observed that experience elements influence customers' emotional states, such as satisfaction. The customer experience affects the constructs formed by the cognitive appraisal of the marketing offer, which leads to loyalty intention, according to the cognitive-affect-behavioral paradigm.

Consumer behavior is influenced by experience, which is not just another marketing idea. Consumer experience can be beneficial to both consumers and businesses. Satisfaction is an important outcome of experiences. The complete rating of the consumer experience is called satisfaction. Consumer satisfaction is positively correlated with the emotional consequence of consumption experiences, according to empirical research. Furthermore, consumers' hedonic values, which are obtained from pleasure-oriented consumption behaviors, have a higher impact on satisfaction.

If a brand creates an emotional response, it may result in satisfaction. Because experiences bring value and usefulness, the more a brand conjures many experience dimensions, the higher the consumer's satisfaction with the brand.

Smart customer experience is a subset of smart retailing that focuses on technology-mediated (e.g., connected technology such as the Internet of Things) retailing. Retailers understand the importance of smart customer experience in achieving high levels of customer satisfaction using smart retail technologies. Customer satisfaction is formed as a result of cumulative experiences with smart retail technologies. We anticipate that the implementation of smart retail technology will elicit smart customer experience, which will lead to increased customer satisfaction, based on previous studies. It was empirically tested in a physical retail environment that the in-store customer experience and satisfaction have strong positive and significant relationship and properly managing the in-store customer experience helps to achieve higher levels of customer satisfaction with the store. Based on the aforementioned literature, we can hypothesize that:

H2: Customer experience is positively related to customer satisfaction.

Customer loyalty

According to brand loyalty is an attitude that leads to consistent purchases of the brand over time. It denotes a repurchase index as well as the intent to continue and encourage. The experience might trigger a series of sensations that prompt a loyalty response from the customer. According to Cognitive-affect-behavior model; customer experience is a construct derived from cognitive evaluation of the marketing offer, in turn leads to loyalty intention. As discussed, experiences result from stimulations and lead to pleasurable outcomes, we expect customers to repeat these experience which is future-directed consumer loyalty.

Organizations aiming to increase customer loyalty and enhance their profitability acknowledge the relevance of positive customer experience has for achieving these goals. Because a service can be evaluated only after consumption, the prior experience with a service impacts significantly on brand choice. Therefore, high and lasting brand loyalty is developed through positive experience with a brand over a period of time. But, if the customers experience is negative, they may discontinue the product and service.

Authors in the past have studied the link between customer experience and loyalty including web-based environments and mobile environments. Although these researchers examined the effect of 'integrated' customer experience on loyalty, investigated the direct impact of each of the experience dimensions: cognitive, affective, sensory, behavioral and social on consumer loyalty. Thus, the study should test the hypothesis:

H3: Customer experience has a positive effect on loyalty.

Brand Equity

Brand equity is one of the most valuable assets associated with a company. According to existing research, brand equity is defined as the difference in effects between a branded and an unbranded product or the difference in customer response to a focal brand and an unbranded product. Loyalty, brand awareness, perceived quality, and brand associations are the four components of customer-based brand equity.

It is argued that experience increases greater memory with vivid and concrete information as a direct source of customer preferences. It is thought that consumer preferences and future decisions are heavily influenced by brand experience. The enhancement of consumers' behavioral intentions is one of the outcomes of brand experience.

Lately the research on brand experience has shifted the focus on the antecedents and consequences. Therefore, emphasized the importance to empirically establish that brand experiences can predict some of the important branding concepts such as brand attitude and brand equity. Drawing upon the theoretical foundations of TRA, found that brand equity significantly influence customer purchase intentions. The five senses of smell, sound, sight, taste, and touch make up a sensory brand experience. Brand-related stimuli elicit all of these feelings. Sensory experiences can help customers identify brands in their minds, which is a component of brand equity, and these sensory experiences can help customers develop brand associations, which is a component of brand equity. As a result, multisensory experiences can help to increase customer equity, which is the value of a customer to a firm. Based on the above discussions, we can hypothesize that

H4: Customer experience influences brand equity.

Moderating Variables

Customers from various countries and cultures have varying levels of success in gaining life experiences. In information systems research, culture plays a very important role. People belonging to eastern and western countries exhibit significantly dissimilar behavior. The knowledge, expertise, and skills about e-commerce differ across cultures. So, some factors might be more effective and relevance in one culture than that of the other (Hossain & Quaddus, 2012).

Similarly, customers' use of internet technology has an impact on how they might improve their purchasing experience. Both offline and online shopping with their experiential qualities are enjoyable by the consumers. But there are potential difference in the consumers’ perceptions about the shopping intentions and emotions under different retail environments such as online and offline environments. Therefore, the examination of CX outcomes in both culture and retail environments will facilitate their moderating effects.

The literature on customer experience suggests that it is a very critical aspect in today's retail business and the customer-focused factors which are the outcomes are directly impacted based on the orientation of the customer experience. The inconsistent results create confusion among the academicians, practitioners, and researchers. Therefore, this study attempts to identify the most critical consequential factors of the customer experience. A statistical technique called meta-analysis is used to find out the strength of relationships by integrating the previously conducted studies related to customer experience. It will help in finding out the common truth and the relationship which can be commonly held and applied.


We performed a systematic review to synthesize the past findings and carried out a meta-analysis to make deeper statistical assessment of past findings from the quantitative studies (Paul & Criado, 2020). The systematic review was performed and reported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA). The studies were selected in accordance with PRISMA and PICOS (population, intervention, comparison, outcome, study design). The studies included those where the participants or the respondents were drawn from a population who has purchased in a retail environment and were not given any intervention. Studies were not selected based on any comparison between the retail environments or any conditions. All the studies have at least reported correlations between the customer experience and its outcomes: customer satisfaction, purchase intention, loyalty, brand attitude, brand equity, word of mouth, and trust.

Collection and Coding of Studies

The authors thoroughly searched the research articles from prominent e-databases such as Emerald, EBSCO, SAGE, Taylor & Francis, Google Scholar, Science Direct, Scopus. In addition to that, the International conference proceedings were also searched. The keywords used for the search of articles were "Customer experience", "Service Experience", "Product experience", "Brand experience", "Consumer experience", "Consumption experience". To combine the terms for search, the boolean operator "AND" was used, which resulted in the fetching articles containing all the search terms. The journals from which the articles were drawn are The Service Industries Journal, Marketing Science, Journal of Marketing, Technological Forecasting & Social Change, Journal of Consumer Marketing, Journal of Retailing, Journal of Global Marketing, International Journal of Retail & Distribution Management, Journal of Services Marketing, Journal of Retailing and Consumer Services, The Service Industries Journal, Journal of Modeling in Management, International Journal of Retail & Distribution Management, European Journal of Marketing, International Journal of Information Management, and Journal of Travel & Tourism Marketing. All the articles published in the last 20 years were searched for the meta-analysis. The initial search result fetched a total of 242 articles.

In the next step, manual screening of the articles based on the title, keywords was done and the irrelevant articles were removed from the list of studies to be analyzed. The abstracts were read by two researchers and excluded the qualitative studies and did not exactly focus on customer experience. A list of 66 empirical research papers was shortlisted to classify the antecedents, consequences, and moderator variables.

In the next step, the full text of the shortlisted articles were analyzed for the following qualifying characteristics 1) the article that has studied quantitatively the relationship of customer experience construct with other constructs., 2) the sample size has been mentioned in the articles and 3) the articles must have mentioned either the path coefficient, or correlation coefficient or other statistics (e.g., t-value, mean, and standard deviation). The authors validated that the exclusion and removal of only the irrelevant articles have been done. Thus, out of those 66 research papers, 39 empirical studies were considered for the final study meta-analysis. The entire selection process is depicted in the PRISMA flow diagram Figure 1.

Figure 1: Prisma Flow Chart.

Coding Procedure and Features of Studies

Once the data collection was done, for each of the shortlisted articles, the author, title, source of the research paper, the publication year, the country, sample size, and correlation coefficients were collected. The empirical studies which involve multiple samples were treated as separate individual studies. The antecedents and consequence variables of customer experience were identified from each study. The criterion of a minimum of three studies on a particular construct was considered for meta-analysis. Thus the antecedents and consequences with less than three studies were rejected for the meta-analysis. Many constructs with similar definitions but different operationalization were grouped as a single construct. For example, service purchase frequency was combined with repurchase intention; convenience and ease of use were combined as one construct. Brand trust, brand attitude, and brand equity were categorized under one construct.

Studies are grouped based on the following relationships, 1) Customer experience-Purchase Intention, 2) Customer experience-customer satisfaction 3) Customer experience-customer loyalty 4) Customer experience-brand equity. Only these four relationships are formulated as customer satisfaction, purchase intention, customer loyalty, and brand equity were the only constructs that are the common consequential constructs across the studies we considered. Each of the related studies is coded based on sample size, correlation coefficient, country, and environment of study (online/offline).

The sample size is noted from the research papers as the number of active and valid responses received after the completion of the survey for that study. Effect size is a measurement of the strength of a particular relationship and it is commonly measured in terms of the correlation coefficient for each of the relationships under study. The studies are coded also based on the country of the respondents for the survey and the environment in which the survey research was done i.e., offline retail shopping or online retail shopping and culture. The tables Tables 2-5 corresponds to the coding of the 39 studies based on the above information for each of the relationships.

Table 2
Coding For Studies Of Cx-Pi Relationship
Sl No Study Name Sample Size Effect Size Country Environment
1 Bhattacharya et al. (2019) 607 0.759 India Online
2 Bleier et al. (2019) 10470 0.17 US Offline
Table 3
Coding For Studies Of Cx-Csat Relationship
Sl No Study Name Sample Size Effect Size Country Environment
1 Bhattacharya et al. (2019) 607 0.759 India Online
2 Bustamante & Rubio(2017) 800 0.7 Spain Offline

Table 2 consists of nine studies for the meta-analysis of CX-PI relationship have carried out two different samples one of size 576 and the other of 400 to generalize the study. Most of the studies are from China, Taiwan, UK, and the US among other countries. The studies were carried out almost in equal proportions of online and offline retail environments. Twenty studies are found to be on CX-CSAT suitable for the meta-analysis, eight of them were carried out offline and twelve were in the online setting. Table 3 mentions the coding of the CX-CSAT relationship. There were nineteen studies on the CX-Customer Loyalty relationship and the coding of the same has been listed in Table 4. The studies are from different countries and the studies conducted in offline settings found to have more effect sizes than those of the studies conducted in online settings. Table 5 consists of eight studies for the meta-analysis of the relationship between CX and brand equity. In addition to the coding of the shortlisted studies, Cronbach’s alpha coefficients for constructs were collected to check the reliability and the values were found more than 0.7, the recommended value.

Table 4
Coding For Studies Of Cx-Be Relationship
Sl No Study Name Sample Size Effect Size Country Environment
1 Hepola et al. (2017) 1385 0.252 Finland Online
Table 5
Results Of The Meta-Analysis
Relationship Combined effect size Lower limit Upper limit Q df I2 Strength p-value
CX-PI 0.457 0.199 0.656 491.603 7 93.57 Moderate 0.000
CX-CSAT 0.598 0.478 0.697 1201.731 19 94.57 Strong 0.000
CX-CLO 0.360 0.286 0.430 272.425 18 93.39 Moderate 0.000
CX-BE 0.512 0.329 0.658 261.073 7 97.32 Strong 0.000

Using CMA software, fail-safe N analysis was done to check the publication bias. The results were satisfactory and are shown in the Table 6. Since the fail-safe N value for each relationship is much more than the corresponding number of studies, it meant the publication bias doesn’t arise.

Table 6
 Fail Safe-N Values
Relationship Fail safe- N Value
CX-PI 1701
CX-CSAT 10274
CX-CLO 6049
CX-BE 1581

Statistical Analysis

A standardized measure of the strength of the observed effect is called effect size. Different studies have measured different variables using different scales of measurement and can be compared directly.

Though there are many measures proposed as effect size, the most common is Pearson's correlation coefficient, r, Cohen's d, and Odds Ratio (OR). Pearson's correlation coefficient, r, is a standardized covariance between two variables and is a measure of the magnitude of the relationship between two continuous variables. For our study, the correlation coefficient was used as the effect size (Ismagilova, 2020; Dwivedi, 2019). The higher the value of effect size, the higher is the strength of the relationship or presence of a phenomenon. The steps carried out to conduct the meta-analysis are as below.

1. The correlation coefficient, r, is first converted into a standard normal metric using Fisher's r-to-z transformation. Fisher's transformation is given by

Where, riis the correlation coefficient for ith study

2. Heterogeneity among the studies is tested by Q-statistic and I2 statistics. Q-statistic is a measure of sampling error, which is calculated as the weighted variance of the effect size metric.

3. Calculation of combined effect size 4. Assessing the statistical significance of the combined effect size.


Meta-analysis approach is a critical evaluation of the quantitative estimates of effect sizes. With the meta-analysis the present paper processes the consumer information at individual level and identifies the key consequences of CX and looks at the effect of moderators such as retail environments and culture on these relationships. The objective of this meta-analysis study is to find the common effect i.e., to see if the effect size is consistent from one study to another and if it is not consistent the technique identifies the reason for the variation. There are two statistical models for meta-analysis: fixed-effect model and the random-effects model. The fixed-effect model assumes that there is one true effect size for all the studies in the analysis and the differences in the observed effects are due to sampling error. According to the random-effect model, the effect size varies across the population. Because studies will differ in the mix of participants and the implementations; the different studies may have different effect sizes. This is the reason the random effect model was used for the calculation of the combined effect size. A meta-analysis was performed after the studies were coded for all the studies. Comprehensive meta-analysis 3.0 software was used to perform the meta-analysis. To analyze each relationship, effect size and sample size are needed. The correlation coefficient between the Customer experience and customer satisfaction, purchase intention, customer loyalty, and brand equity was chosen as effect size and a random model was selected to perform the analysis. Moreover, the random model balances the weight given to the studies such that no study dominates nor trivializes. Table 6 summarizes the results of the meta-analysis.

The results obtained are in terms of combined effect size at 95% confidence interval, Fisher's Z-score, Q statistics, I2 statistics, the degrees of freedom (df). Heterogeneity is typically checked in the meta-analysis with Q-statistics, I2 statistics, chi-square test. Q-statistics is a measure of the sampling error variance and the formula used for the same is as below.


i varies from 1 to k and k is the number of research studies, wi is the weight assigned to each study and ESi is the effective size of each study. I2 statistics is a measurement of total variation across the studies and it represents the real heterogeneity. I2 is calculated by the formula below.

Where, df is the degrees of freedom = k-1

The higher value of I2 for each relationship shows that there is a large amount of heterogeneity. The combined effect size was found for each relationship. For CX-PI(r =0.457, 95% CI =0.199–0.656), CX-CSAT(r =0.598, 95% CI =0.478–0.697), CX-CLO(r = 0.360, 95% CI = 0.286–0.430) and CX-BE (r = 0.512, 95% CI = 0.329–0.658). All the values show there is a positive influence of customer experience on all the impact variables. The effect sizes have been categorized into strong, moderate and weak if the value is 0.5, 0.3, and 0.1 respectively. Based on the results we can see the relationship CX-CSAT and CX-BE are strong. This shows that the study supports the proposed hypotheses H2 and H4. The result also shows that the relationships CX-PI and CX-CLO are moderate. From this, it is evident that the hypotheses H1 and H3 are supported.

The statistical significance of the results of the meta-analysis can be assessed by the pvalue and the robustness of the results can be measured from the fail-safe N value (Acar et al., 2017). The p-value for each of the relationships was found to be below 0.05 and the fail-safe N value for each of the relationships was found to be more than the number of studies. Thus the meta-analytic study is robust.

Subgroup Analysis

The researchers found that the extant studies were conducted in online and offline retail environments almost in equal proportions and in different countries across the world. To understand the heterogeneity of the sample studies, the role of retail environment and the country's culture was examined. Tables 7 & 8 list down the findings of the moderator analysis. The Q-statistic values show that both retail environment and culture moderate all the relationships between CX and its consequence variables. Both CX-PI and CX-CSAT relationships are stronger in online retail environment (Bhattacharya et al., 2019) than the offline retail environment. However, CX-BE relationship is stronger in offline retail environment. Loyalty is not much moderated by the retail environment. Similarly, western countries show stronger relationship for CX-PI, CX-CSAT, and CX-CLO.

Table 7
Moderating Effect Of Retail Environment
Retail environment Number of studies Combined effect size Factor Overall   Q-value p-value
Offline 2 0.342 Purchase Intention - 0.000
Online 6 0.516 Purchase Intention 491.603 0.000
Offline 9 0.588 Customer Satisfaction - 0.000
Online 11 0.614 Customer Satisfaction 1201.731 0.000
Offline 13 0.389 Customer Loyalty - 0.000
Online 6 0.357 Customer Loyalty 272.425 0.000
Offline 2 0.551 Brand Equity - 0.000
Online 6 0.397 Brand Equity 261.073 0.000

Managerial Implications

One of the prominent aspects of a retailer's strategy is to design the customer experience so that it creates value for both the customer and the firm. The result of this analysis will be a meta-analytic relational framework for customer experience outcomes that will answer our research questions listed above. Since our research focuses on the effective outcome constructs of the customer experience and the moderators, we focus on the aggregate results for moderators and outcome constructs that are the most affected by customer experience. Operationalization of the CX elements like cognitive, hedonic, utility and visual elements will directly impact its consequential factors. The findings will provide insights to the retail managers and enhance their convictions over these outcome variables. It will also help them to develop the right strategy for any specific relational weaknesses.

The study identifies that CSAT, CLO, PI, and BE are the most common outcome variables having the quantitative data for meta-analysis among all the other outcome variables of CX as mentioned in Table 8. After the synthesis of all the effect sizes of the studies, the meta-analysis calculated the combined effect size for the relationship CX-CSAT as 0.598. Similarly, for the other relationships, the combined effect sizes are calculated.

Table 8
Moderating Effect Of Country
Country   Culture Number of studies Combined effect size Factor Overall Q-value p-value
Eastern 5 0.438 Purchase Intention - 0.000
Western 3 0.576 Purchase Intention 491.603 0.000
Eastern 9 0.566 Customer Satisfaction - 0.000
Western 11 0.625 Customer Satisfaction 1201.731 0.000
Eastern 9 0.349 Customer Loyalty - 0.000
Western 10 0.406 Customer Loyalty 272.425 0.000
Eastern 4 0.482 Brand Equity - 0.000
Western 4 0.384 Brand Equity 261.073 0.000

The results of the meta-analysis show that the combined effect size is highest for the CX-CSAT followed by CX-BE relationship. But the combined effect sizes for the CX-CLO and CX-PI (Bhattacharya et al., 2019; Bleier et al., 2019) also show moderate strength of the relationship. The results suggest that retail and store managers need to emphasize more on the CSAT (Bhattacharya et al., 2019; Hepola et al., 2017) and BE. The result also shows the moderator effect on all the relationship. A subgroup analysis of the relationship suggests that some relationships are stronger in online and some are stronger in offline, some relationships are stronger in western culture than eastern culture. Hence, the marketers should design their strategy to create an experience by keeping the consequences in mind.

Theoretical Implications

The finding of the paper enhances the theoretical contribution with respect to CX, most specifically CX and its consequential variables. This study attempts to assess the purchase intention of the consumers because of the experience they gather during their purchase process. As customer experience is a multidimensional construct, the dimensional effect on the outcomes needs to be focused while making marketing strategies because different dimensions might have different levels of influence on consumers. The aspects of customer experience such as entertainment, educational, aesthetic help to attract customers.

According to, customer decision making is not sequential as they come across information stimuli simultaneously and make the purchase decision or repurchase decision. The study shows that the customer experience influences brand equity which echoes the findings of research by a proposed theory followed by empirical confirmation suggests that repurchase intention is an outcome of customer experience. A meta-analysis of the present study also shows the relationship to be significant. Similarly, customer loyalty and brand equity are outcomes of CX which is tested in the meta-analysis as well. Thus the study reaffirms the findings of the past studies (Hepola et al., 2017).


By using the meta-analysis approach, the present research has synthesized the results of previous studies on customer experience. In particular, the study examined the effect customer experience gained in the retail environment during their purchase on its outcome variables such as consumer satisfaction, repurchase intention, customer loyalty, and brand equity. Finally, the study also reveals that the role of the (offline/online) retail environment and culture is critical in the relationship between customer experience and its consequences. In online retail environment, CX is strongly related to customer satisfaction and purchase intention, whereas in offline environment, CX has a stronger relationship with brand equity. Similarly, CX has stronger relationship with purchase intention, satisfaction and loyalty in the western countries.


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Received: 05-Mar-2022, Manuscript No. AMSJ-22-11360; Editor assigned: 07-Mar-2022, PreQC No. AMSJ-22-11360(PQ); Reviewed: 21-Mar-2022, QC No. AMSJ-22-11360; Revised: 24-Mar-2022, Manuscript No. AMSJ-22-11360(R); Published: 28-Mar-2022

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