Influence of the Determinants of Online Customer Experience on Online Customer Satisfaction

Abstract

The role of online retailing is increasing with each passing day for any business and therefore offering value to the customer which in turn also yield benefit to the retailer and differentiate it from the competitors is an important task. By getting an idea of how customer perceive and evaluate the offerings, retailers may be able to influence the customers in that particular direction. This research paper aims in identifying the major factors or attributes that affect the customers, evaluating their overall experience while shopping on the digital platform and also their impact on online customer satisfaction. This study aims to explore the determinants of online customer experience of Indian shoppers and its effect on the satisfaction of the customers. For the purpose, 325 e-shoppers were surveyed through online mode using snow ball sampling technique. To achieve the objective, exploratory factor analysis was used and multiple regressions were applied. Furthermore, the findings suggest that economic value, customization, post-purchase experience and customer services are the major factors on which customers evaluate their overall online experience and satisfaction.

Keywords

Online customer experience post-purchase experience customer security online shopping

Introduction

With the advent of the internet and the World Wide Web, customers have changed the way of seeking and using information at their end (Rosenfeld & Morville, 2002). The internet has become a vital and significant place of business these days contrary to the earlier belief as a tool only for enhancing information (Porter & Michael, 2001). In today’s modern era, the internet is not only limited to mail, chat and information search but also used as a platform for shopping goods and services (Walsh & Godfrey, 2000). It has made almost everything just a click away from the customers.

The number of services being offered on the internet is increasing day by day as a result of rapid growth in business opportunities in this area, and online shopping has come forth as one of the most notable and eminent services accessible on the internet. Online retail provides an exorbitant benefit to both the customers and the businesses (Griffith & Palmer, 1999). With the help of online shopping, business houses have been able to reach and tap the customers from both the metro cities and remote areas at a considerably low cost (Leamer & Storper, 2014). Moreover, the inventory management cost is also declined remarkably through the e-retailing (Myers, 1984). However, it is not that the online shopping has benefited only the business houses. E-retailing offers a wide range of advantages to the customers as well. Customers are not required to visit the outlets physically for shopping; also the choice of products is very large in online shopping as compared with the limited choice being offered in the brick and mortar store (Reibstein, 2002). In the e-retailing shopping, the customer can visit any number of sites before coming to a final decision. Timing is never an issue with the internet as the customer can buy or search and compare for a product on different websites as per his/her wish at any time and day of the year (Smith, 2005).This also helps in saving time and energy of the customers. The internet user base of India stands at 460 million in the year 2017 (Economic Times, 2017). This figure is likely to reach about 635 million by the year 2021 (Economic Times, 2017). It is predicted that the e-commerce sector of India will rise from US$38.5 billion in 2017 to US$200 billion in 2026 (India Brand Equity Foundation [IBEF], 2018). By the mid of 2000, the Indian e-commerce market expanded to a total of US$19.5 billion (KPMG, 2018) from its emerging level. The IBEF (2018) stated that with increasing smartphones penetration, improving infrastructure, availability of cheap mobile phones, launching of the 4G network, digital India movement, increasing customers’ aspiration, etc. have lead India as one of the fastest growing e-commerce markets worldwide. However, despite growing at this rapid speed, the e-retail sector of India stands at only 1.5 per cent of the total retail sales including both organized and unorganized in the year 2017, indicating its enormous growth potential (CRISIL, 2018). Several studies in the past have focused on the service quality of online retail base on factors namely usability of the website, security, reliability, etc.; however, different literature recently indicates that customers evaluate any business house not just on the criteria of transaction process but also on overall perspective named ‘customer experience’. Palmer (2010) suggested that one of the important ways to attain competitive advantage is by effectively managing the experience of the customers. In this context, customer experience emerges as new area which motivated customer to adopt the digital platform for shopping. Moreover, a study by Oracle in the year 2011 stated that 89 per cent of the customer will start doing business with its competitor followed by a poor customer experience. Another study by Temkin in the year 2017 revealed that 22 per cent of the customers reduce their spending after a bad experience and around 19 per cent stopped doing business at all. Taking this into account the current study tries to find important factors that influence online customer experience, as customer experience is a strategic issue that needs to be understood by marketer in order to improve customer attraction. Furthermore, this sector still evolves and remains strong because of country-specific social reasons and technology-related problems. This research therefore seeks to understand new factors that affect the experience of Indian online customers.

Literature Review

An engaging customer experience is an important factor for success of any business. In the recent years, online customer experience has become the emphasis of service marketing researchers (Nambisan & Watt, 2011). The trigger for the move is a result of the evolution of e-commerce platforms (Kim, Shin, & Lee, 2009). The website portals have turned out to be more interactive and dynamic, offering a superior interface for the customers to explore the offerings. Customers’ online buying behaviour is affected by the great online customer experience (Bridges & Florsheim, 2008). Mosteller, Donthu, and Eroglu (2014) recognized the significance of online experience by recommending that further examination is expected to look at the impact of key factors on online customer experience. In the past, research has been carried out on several determinants such as determinants of personality, perception, experience, attitude and knowledge (Holsapple & Sasidharan, 2005; Walczuch & Lundgren, 2004). The main results seemed to be that consumer decides on a fairly sensible grounds to believe the e-retailer. Research concluded that the variables such as knowledge and experience play a critical role in e-commerce purchase. Parasuraman and Zinkhan (2002) in their study analysed different elements that determine online customer experience. These factors are customers’ perceptions for product, payment, delivery terms, services, risk, privacy, security, personalization, visual appeal, navigation, entertainment and enjoyment. Kim, Yang, and Jun (2004) has added some more dimensions by conducting a study on customers’ perceptions of online retailing service quality and their satisfaction. Customers’ views about the product, payment, delivery conditions, services, risk, privacy, security, personalization, visual appeal, navigation, entertainment and enjoyment were the determinants. This study reveals that the online retailers’ service quality and satisfaction of the consumers are highly correlated. Three measurements such as reliable response, attentiveness and ease of use influence the customers’ experience and satisfaction (Rod, Ashill, Shao, & Carruthers, 2009). Herhausen, Binder, Schoegel, and Herrmann (2015) advised online retailers to run integrated information systems that include both online and offline media. The importance of the aesthetics in e-commerce sites was examined by Tractinsky and Lowengart (2007) and they noticed that e-commerce site developer must consider classic as well as expressive aspects of the websites. The classical aspects were linked to a safe, smartly designed and user-friendly perception to use website (De Angeli, Sutcliffe, & Hartmann, 2006). The web visuals must be structured by concentrating on the product type and customer type which website targets (Wang, Minor, & Wei, 2011). Retailers of website should therefore adapt their web storage layout as per the qualities and need of consumer and brand. Customer experience is based on the cognitive, effective, mental, society and feeling responses on websites (Verhoef et al., 2009). These experiences are not generated just by the aspects that are controlled by the retailer but also by the issues that are away from retailers’ reach. In other words, customer experience on the website ranges from searching information to acquiring and post buying experiences on various online platforms (Wolfinbarger & Gilly, 2003). Rose, Clark, Samouel, and Hair (2012) have examined e-retailers’ mechanism to deliver better e-customer experience.

The cognitive experiential state constituted by speed of interaction via internet, problems of online, expertise and affective experiential state constituted by ease of use, customization, perceived control, connectedness, aesthetics and perceived benefits were studied to assess its effect on behavioural consequences viz online shopping satisfaction, trust and repurchase intention (Sutcliffe, Kurniawan, & Shin, 2006). Sahney, Shrivastava, and Bhimalingam (2008) examined the attitude of customers in Indian e-purchasing. They examined few issues such as reliability, safety, aesthetic appeal, continual improvement, overseas products access and services after purchase. Reliability was noticed to be the most valuable criteria of Indian e-retailers, preceded by product access and services after purchase (Petre, Minocha, & Roberts, 2006). A well-arranged website will enhance customer spirit and encourage them for browsing and navigation (Cai & Xu, 2011).

Research Gap

It is clearly evident from the literature review that the availability of literature in India on the subject of factors affecting online customer experience in e-retailing is sparse. Also, whatever studies (in India and abroad) have been conducted so far is not comprehensive in nature as either researchers have studied only one or the other determinants of the online customer experience. Moreover, the insight provided by the studies conducted (in India or abroad) is bounded in their significance when applied to Indian context due to the dissimilitude of business environment, thereby obviating the direct application of their findings in Indian context. Consequently, this indicates a conspicuous gap in the literature and provides a research opportunity that mainly focuses on differentiators based on experience of the customers to attain competitive advantage in the long run for the e-marketers.

Problem Statement

Retail market has been a lucrative field for industrialists and researchers for the past many decades. With the advent of technology, as various companies tried to expand their reach with the help of application-based platform, a new research area has grown significantly which tries to understand customer experience in online retail market.

The online retail market stood at US$11 billion in the year 2015 (Economic Times, 2017) which grew by 30 per cent in next fiscal year 2016 and the figure stood at US$14.5 billion (Economic Times, 2017). It was expected that Indian online retail market will grow at the same rate of 30 per cent till the year 2026 (Gupta, 2017). But as per the report of RedSeer Management Consultancy, the online retail market grew by 23 per cent and the overall market was valued at US$17.8 billion in the year 2017. A possible cause for this problem could be lack of assessment of customer experience on the part of researchers and marketers.

As per Forrestor research, 72 per cent of companies pay attention on betterment of customer experience. Another study by Fagan (2013) stated that 55 per cent of consumers would pay more for a better customer experience. A study by Oracle in the year 2011 stated that 89 per cent of the customer will start doing business with its competitor followed by a poor customer experience. Another study by Temkin in the year 2017 revealed that 22 per cent of the customers reduce their spending after a bad experience and around 19 per cent stopped doing business at all.

Thus, this research therefore attempts to explore factors affecting the e-retail experience of consumers and further assess the effect of online customer experience determinants on customer satisfaction.

Hypothesis Development

For website usability, the perception of customer is that the online shopping site should be user friendly and convenient to use. Novak and Hoffman (1996) suggested that website usability act as the main competitive advantage between online and traditional retail store setting. The bargaining power of the customer is more on the electronic platform because of the interactive website that offers huge interaction possibilities between customers and product/service providers. However, certain studies suggested that with increase in the shopping frequency of the customers, the website usability is not very significant in forming a positive experience as customers become familiar with the use. Moreover, customers cannot touch, smell or have any sensory feel of the product which may lead to low level of trust. Considering the review of literature, detailed in this section, this study finds that the website usability plays a significant role for the formation of positive customer experience. While studying the sample of undergraduate management graduate, Buda and Zhang (2000) found website usability gets discounted after some time as customer purchase frequency increases. Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 1: Website usability has a positive effect on online customer satisfaction.

Online shopping is known for the competitive pricing that they offer. Online shopping helps in saving not only money but also time and effort of the customers. All one need is an internet-enabled smartphone or laptop to access the online shopping portals. In the initial phase of online shopping, it was viewed through a utilitarian point of view by offering products at a competitive price. However,recent researches in the field of customer satisfaction suggested that not only functional benefits drive online customer satisfaction but also the increase in the experience customer have started seeking certain hedonic values (Hise & Szymanski, 2000). Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 2: Economic value has a positive effect on online customer satisfaction.

Customization in e-retailing, defined as ‘the ability of an e-retailer to tailor products, services, and the transactional environment to individual customers’ (Srinivasan et al., 2002). For this feature, the personal data of the customers are recorded and recommendations are made according to the profile of the individual customers. Various customers-related information are gathered and saved for the use of the customers during their next visit. Moynagh and Worsley (2002) suggested that through customization process customers get a feeling of personal service and care which in turn increases the satisfaction. While previous studies proposed customization as an important strategic tool of online retailing (Lee & Lin, 2005; Ribbink et al., 2004), very few researchers conducted studies focusing on customization in online settings. Considering the review of literature, this study finds that the customization plays a vital role in online shopping but there is dearth of availability of literature to understand the effect of customization on online customer satisfaction. Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 3: Customization has a positive effect on online customer satisfaction.

Security is the major concern for any customer whether they have shopped online or not (Rohm & Milne, 2000). According to U.S. FTC (2000), large numbers of website users are concerned about the privacy of information, acquisition and dissemination of their data. Consumers’ security concerns associated with online retailing have received limited attention despite their implications for e-commerce. Although some early research suggest that risk perceptions may play a minor role in the adoption of online shopping (Jarvenpaa & Todd, 1996–1997), several recent industry and government-related studies (e.g. Culnan & Armstrong, 1999) have deemed consumer security to be a primary obstacle to the future growth of online commerce. Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 4: Security has a positive effect on online customer satisfaction.

Post-purchase experience is one of the major parts of online customer experience. Post-purchase experience starts with the delivery of the product and ends with the final use/consumption of the delivered product. It is also one of the major contributing factors in developing customer satisfaction and thereby repurchases intention (Endo, Yang, & Park, 2012). In the online retail setting, post-purchase experience holds an important place as the customer at this stage only can actually touch and feel the product (Katawetawaraks & Wang, 2011). At this stage, the customer does the cognitive and affective processing of sensory information gathered from the online environment and subsequently forms an impression to store in the memory for use during the next purchase (Martin et al., 2015). In line with the thought of customer satisfaction, Collier and Bienstock (2006) have emphasized that providing various ways for customers to connect with the online vendor to get their help is essential for improving the quality of the online service operations. The post-purchase interactions between company and customers have significant impact on overall customer experience. Considering the review of literature, this study finds that the post-purchase experience plays a vital role in online shopping but there is dearth of availability of literature to understand the effect of post purchase on online customer satisfaction. Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 5: Post-purchase experience has a positive effect on online customer satisfaction.

Efficient customer grievances handling mechanism, good return and exchange policy, compensation to customers in case they incur any losses are some of the strategies adopted by e-retailers to increase the satisfaction of their customers (Karimov & Brengman, 2014). Considering the review of literature, this study finds that the customer service plays a vital role in online shopping but there is dearth of availability of literature to understand the effect of customer service on online customer satisfaction. Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 6: Customer service has a positive effect on online customer satisfaction.

Awareness of customer also acts as an antecedent to fulfilling online customer experience. People at present share link of the product they like or dislike on the social media platform with their peers, friends and relatives (Greenhow, 2011). They also read reviews and ratings given by other users of the product and make their purchase decision accordingly. Moreover, information of the product being mentioned on the website also help in making the purchase decision. However, there is dearth of availability of literature to understand the effect of customer awareness on online customer satisfaction. Hence, the research endeavours to frame below mentioned hypothesis for the study.

Hypothesis 7: Customer awareness has a positive effect on online customer satisfaction.

Research Methodology

Research Design

This study is exploratory cum descriptive in nature as far as research design is concerned. Exploratory research design has been used for secondary data. Afterwards, descriptive research design is followed for drawing conclusion from the obtained responses.

Sampling Design

Population: The population being considered for this study are the individual users aged 18 and above who regularly review the online shopping websites. The online portals for this study have been chosen on the basis of their popularity and higher usage by marketers and users.

Sample unit: Sample of our study includes the online shopper aged 18 and above of Varanasi.

Sampling method: Since the current study consists of the online shoppers who are only a small percentage of the entire population, therefore snowball sampling technique has been employed to collect the data.

Instrument and Data Collection

Coding: For the collection of required data, an online questionnaire was employed and sent to the respondents through links on the email. Close ended questions along with 7-point Likert scale was used for the statistical analysis. The coding of the Likert scale ranges from 1 to 7 where 1 denotes strongly disagree, 2 denotes disagree, 3 denotes slightly disagree, 4 stands for neutral, 5 represents slightly agree, 6 represents agree and 7 represents strongly agree.

Technique

In order to achieve the objective of this study, IBM SPSS Statistics 20 was utilized. Initially, descriptive statistics were utilized to obtain the characteristic of the sample being studied and watch the patterns of shoppers purchasing on digital platform in general. This was followed by exploratory principal components factor which was mainly done to examine hidden elements of customer experience on the online platform. Furthermore, reliability and validity were checked by employing Croanbach’s alpha.

Construct Measures

The vast majority of the selected constructs have been utilized in the past web-based business (Cheung et al., 2008; Filieri & McLeay, 2014; Park et al., 2007). The dependent variable was customer satisfaction and adopted by Cheung and Lee (2008) in online customer experience research. Factors for the measurement of construct were tested and developed by Filieri and McLeay (2014). For the test, all the seven items extracted were selected.

Result

This section presents results from factual investigation performed utilizing primary information received from the survey. To begin with, results from respondent’s profile are obtained, trailed by observations from exploratory principal component factor analysis.

Sample Characteristics

The total number of responses obtained from the survey after the elimination and filtration of incomplete data was 300. Out of this representation, the male respondents were higher in number (approximately 70 per cent) as compared with female respondents (approximately 30 per cent). The major part of the respondents belong to the age group of 25–35 (45 per cent) followed by 36–45 (26 per cent) and 46–55 (22 per cent).

Findings and Discussion

Under this section, the factors of online customer experience are discussed. Kaiser–Meyer–Olkin (KMO) test was done to check the sample adequacy and the KMO value was found to be 0.834 which proves that sample was adequate.

KMO and Bartlett’s Test
KMO measure of sampling adequacy		0.834
Bartlett’s Test of Sphericity	Approx. chi-square	5,892.984
	df	351
	Sig.	0

There was a high enough degree of correlation between variables in the data as the Bartlett’s test of sphericity stands at statistical significance of p < 0.001. This also confirms the appropriateness of factor analysis for the given data sample.

Reliability of the obtained data was assessed with the help of Cronbach’s alpha. In the present study, this value ranges from 0.824 to 0.937 (see Table 1) which shows that there is high reliability among the indicators.

Table 1.

Factor Loading and Croanbach’s Alpha

Construct	Item	Factor Loading
Website usability
Alpha=0.884	Easy to find the product on the website	0.850
Alpha=0.876	Appearance of the website is visually pleasing	0.837
Alpha=0.884	Availability of well-organized information on the website	0.821
Alpha=0.891	Convenient to use the website	0.807
Economic value
Alpha=0.883	Saves time and effort	0.883
Alpha=0.876	Provision of discounts and promotions	0.850
Alpha=0.880	Provision of rewards to loyal customers	0.844
Alpha=0.886	Products are competitively priced	0.837
Customization
Alpha=0.870	Option to share experience with others	0.904
Alpha=0.878	Storing of customer preferences and offering products based on those preferences	0.860
Alpha=0.891	Customize shopping pages according to preferences of the customers	0.826
Alpha=0.886	Option of interactive feature on the website	0.815
Security
Alpha=0.827	Proper delivery of products	0.881
Alpha=0.852	Safety during transaction process	0.877
Alpha=0.871	Product corresponds well to the description provided on the website	0.795
Alpha=0.865	Protection of personal information	0.753
Construct	Item	Factor Loading
Post-purchase experience
Alpha=0.812	Providing benefits of loyalty programmes	0.875
Alpha=0.813	Asking about the overall experience of the shopping	0.851
Alpha=0.854	Delivery of right product	0.795
Alpha=0.848	Taking reviews and ratings of the products	0.698
Customer service
Alpha=0.803	Good return and exchange policy	0.874
Alpha=0.804	Efficient way to get in touch with the company on the website	0.845
Alpha=0.843	Company’s effort to solve problems in case they occur	0.798
Alpha=0.841	Compensation to customer if they incur any loss	0.691
Customer awareness
Alpha=0.857	Option to share the link of the product on social network	0.932
Alpha=0.858	Opportunity to read reviews of the product from other customers	0.923
Alpha=0.942	Adequate information of the product for an informed purchase decision	0.801

Source: Authors’ own data derived after analysis of customer responses.

The principal components examination uncovered nearness of seven segments with eigenvalues surpassing 1. The distinguished components had the capacity to explain cumulative variance of 78.15 per cent. It is largely prescribed that the removed variables represent in any event 60 per cent of the change, a condition adequately supported in the present investigation (Malhotra & Birks, 2007). The main factor named ‘usability’ of the site represented 20.87 per cent of the total variance. It comprised of the navigation and user-friendliness aspect of the website. The second factor mirrored the financial aspect picked up by the customers amid their internet shopping knowledge. This factor was named ‘economic value’ and was measured through how competitively priced the products are on the website and what are the discounts available to the customers. The third factor namely ‘customization’ was related to the effect of customization and personalization on the site in web-based shopping experience. The things on this factor included qualities such as the chance to share information with others through social media; chance to interface with different clients inspired by an item through a blog or a network; availability of optimization of the webpage and offering products based on past searches of the customers. Fourth factor consists of customers’ view of security amid web-based shopping knowledge and included things that identify with assurance of debit/credit card and individual data, and safety amid exchanges process. The fifth factor constituted 5.89 per cent of the total variance and was labelled as ‘post-purchase experience’ of the customers. It was measured on the dimensions which included proper delivery of the product, providing benefits of the loyalty schemes and obtaining reviews and ratings by the customers. The sixth dimension incorporated into this measurement was arrangement of effective approaches to connect with the organization on the site; organization effort to take care of issues in the event if they happen and great return/trade strategy. This factor was labelled as ‘customer service’. The last factor was named ‘customer awareness’ and is associated with the informed purchase decision on the part of the customers. This learning could be acquired both from product reviews and detailed product description mentioned on the website by the e-retailers.

Test of model fit was done in order to ensure that the obtained scales were reliable. In this study, Croanbach’s alpha was deployed since it is the most popular method to measure the internal consistency of the obtained seven constructs. The general acceptability level lies in the range of 1–0 where 1 denotes perfect internal reliability and 0 denotes no internal reliability. The result obtained in the present study lies between 0.803 and 0.942 which suggest that the obtained factors gave an appropriate measure of the underlying construct being reflected here.

The descriptive statistics (Table 2) reveals that security of the customers with respect to personal information, card details, product performance and transaction safety emerges as the most important factors in deciding the experience of the customer on the online platform. Safety during the transaction process and product corresponding well are the major positive experience creator for online customer experience. The second most important factor is customer service followed by post-purchase experience of the customer.

The estimation of R, i.e. coefficient of correlation, was 0.974 which demonstrates the great level of forecast for the user satisfaction. R square segment demonstrates the R² value, additionally called as the coefficient of determination; in other words, the difference in the dependent variable can be clarified by the assumption about independent variables. The estimation of R² = 0.948 implies 94.8 per cent of the variability in case of dependent variable, i.e. customer satisfaction is explained by independent variables (see Table 3).

In Table 4, the overall regression model is checked and analysed whether the model is a good fit or not for the data. It is clearly illustrated that the considered independent variables (statistically significant) predict the dependent variable, i.e. customer satisfaction, F (7, 292) = 764.881, p < 0.05. Therefore, we can conclude that the above mentioned model for regression is a good fit for the data.

Table 2.

Descriptive Statistics

	N	Minimum	Maximum	Mean	Std. Deviation
website_usability	300	1.00	7.00	4.3392	1.65332
Economic_value	300	1.00	7.00	4.4525	1.63458
Customization	300	1.00	7.00	4.4508	1.55147
Security	300	1.75	7.00	5.1542	1.28170
post_purchase_experience	300	1.75	7.00	4.9025	1.39377
customer_service	300	1.75	7.00	4.9833	1.36155
customer_awareness	300	1.00	7.00	4.1156	2.01259
Valid N (list-wise)	300

Source: Authors’ own data derived after analysis of customer responses.

Table 3.

Model Summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	0.974^a	0.948	0.947	1.34365

Source: Authors’ own data derived after analysis of customer responses.

^a Predictors: (Constant), customer_awareness, customer_service, security, post_purchase_experience, customization, Economic_value, website_usability.

Table 4.

ANOVAa

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	9,666.347	7	1,380.907	764.881	0^b
	Residual	527.173	292	1.805
	Total	10,193.520	299

Source: Authors’ own data derived after analysis of customer responses.

Dependent variable: sat_COMP.

Predictors: (Constant), customer_awareness, customer_service, security, post_purchase_experience, customization, Economic_value, website_usability.

Estimated Model Coefficient

The general equation of coefficients predicts customer satisfaction from economic value, customization, post-purchase experience and customer service. Customer satisfaction = −1.273 + (2.920*economic) + (0.124*customization) + (0.135*post-purchase experience) + (1.035*customer service). This unstandardized coefficient depicts the extent of variation of dependent variable with any change in independent variable.

Statistical Significance of Independent Variables

If we test the independent variables separately, it shows the statistical significance relationship of four variables, namely economic value, customization, post-purchase experience and customer service. If p < 0.05, we could say that the coefficients are statistically significant. The t value and p value are denoted in column as T and Sig., respectively.

To test the hypothesis, statistical measure of stepwise multiple regressions was chosen. Table 5 shows that independent variable, i.e., economic value, customization, post-purchase experience and customer service are significantly defining the dependent variable, i.e. customer satisfaction (R² = 0.948, adjusted R² = 0.947, F = 764.881, p < 0.05, df = 7).

Table 5.

Coefficientsa

Model B		Unstandardized Coefficients		Standardized Coefficients	T	Sig.
Model B		Std. Error	Beta			Sig.
1	(Constant)	−1.273	0.522		−2.440	0.015
	website_usability	−0.033	0.062	−0.009	−0.543	0.588
	Economic_value	2.920	0.057	0.817	51.133	0
	Customization	0.124	0.058	0.032	2.139	0.033
	Security	0.017	0.068	0.004	0.244	0.807
	post_purchase_experience	0.135	0.067	0.031	2.020	0.044
	customer_service	1.035	0.068	0.241	15.198	0
	customer_awareness	−0.017	0.045	−0.006	−0.389	0.698

Source: Authors’ own data derived after analysis of customer responses.

^aDependent variable: satisfaction.

Therefore, it is fair to conclude that customer satisfaction in online customer experience significantly depends upon on how the factors of online customer experience are improving on these parameters. The strongest determinant of the customer satisfaction in online customer experience is economic value (beta = 0.817, p < 0.05), followed by customer service (beta = 0.241, p < 0.05), customization (beta = 0.032, p < 0.05), post-purchase experience (beta = 0.031, p < 0.05). The other three independent variables, namely website usability, security and customer awareness, show statistically insignificant. The result supports four elements of research proposition. Therefore, hypotheses 2, 3, 5 and 6 have been accepted. Hence it can be concluded that on the online customer experience platform, greater the importance given to economic value, post-purchase experience, customer service and customization, the more satisfied will be the customers.

Theoretical Contribution

In this era of digital competitiveness, it is essential to explore the determinants that influence online customer experience. It is also essential to understand their impact on customer satisfaction so that researchers can understand the significance of the underline factors. On the basis of the above study, it was found that economic value, post-purchase experience, customer service and customization are the most prominent determinants of experience formation. This study not only provides us with an insight of various factors of online customer experience but we also try to understand the influence of the aforesaid factors in creating a satisfied user base. The result of this study provides us with preliminary evidence of influence of experience of customer on user satisfaction through various determinants that are economic value, post-purchase experience, customer service and customization. Economic value emerged has the most influential determinant of customer satisfaction on digitally mediated platform followed by customer service and post-purchase experience which lead to a satisfied customer.

Implication from Marketer View

Based on the findings of the survey, outlined implications from marketer perspective have been mentioned.

Customer service: The present investigation demonstrates that a standout among the most ideal approaches to guarantee positive customer experience is by giving high level of services to its customers. Brisk and effective reaction to client questions should be deployed by the e-retailers and should also adopt methods for taking care of issues happening on the site immediately and proficiently. It is generally assumed that the shoppers will shop out of the conventional shopping hours on the online platform due to availability of 24 × 7 shopping services; therefore, response to problems of the customers should also not be bounded by time. Moreover, customer relationship management (CRM) should be employed in order to ensure that customer can reach to the organization anytime through any media such as phone, emails, etc.

User interface: Online retailers need to concentrate on making the websites that are anything but difficult to explore, efficient, organized well and easy for a layman to operate. Additionally, online retailers need to think about the feel of the sites and their visual intrigue in order to appeal their customers.

Post-purchase experience: Post-purchase experience came out to be the important determinant of online experience, hence it become important for an e-marketer to focus on this part of the transaction process. Unsynchronized supply chain between the online and offline mode pays way for delayed and incorrect delivery of merchandise. To avoid this situation, e-retailers should utilize data frameworks and management information system (MIS) which incorporate the different business tasks and give successful correspondence between business capacities. E-retailers also need to ensure that the benefits of the loyalty programmes and other rewards are given to the customers on time.

Security: Since security has been observed as the most significant part in formation of the online customer experience, online retailers need to work in making secure web-based shopping experience for buyers. Strategies such as high level of encryption along with digital signature can be employed to achieve secured transactions (Kim, Yang, & Jun, 2004).

Conclusion and Future Research Directions

In the e-commerce era, customer experience has gained a tremendous significance and so it is essential to understand the determinants that affect the reach of online customer experience. Although there are several determinants that influence customer experience, on the basis of the studies it was found that source economic value, customization, customer service and post-purchase experience are the most prominent determinants of online customer experience influence. This study provides us with an insight of various factors of positive customer experience which influence customer shopping on the digital platform. It also helps in determining the variables that lead to more customer satisfaction on the digital platform.

Although this study was conducted carefully but certain limitations were unavoidable due to accessibility of different techniques. First and foremost, the construct customer experience itself is very wide; hence, it was not possible to touch every aspect of the same as it would require too lengthy and cumbersome questionnaire and an extensive time for its exploration. Second, this study cannot be generalized for the whole population of the country as it includes online shoppers from Varanasi district only. As far as the future scope is concerned, it is advised to investigate every aspect of online customer experience in isolation. Areas such as social and affection related to customer experience have been least enquired about; therefore, attempts should be made to conduct studies in these areas.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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