review

66 3D... IBA Journal of Management & Leadership

What Lies Beneath: The Untapped Potential of

Retail Marketing using Online Platform A Case Study of Goa, India

Siddhi Gadekar, Subhash Pillai, Jick Castanha, Goa University, India Indrawati, Telkom University and Ruey Feng Chen, Hsing Wu University, Taiwan R.O.C

3D... IBA JoUrNAl of MANAgEMENt & lEADErShIp Vol:12 n Issue:1 n July-December, 2020

Abstract

Purpose of study – The purpose of the study was to investigate customer’s perception towards the online shopping in Goa where the entire work is broken in to three main issues, namely, identifying who the customers are, what motivates / influences the customers, and are the customers happy or not.

Research methodology – Data was collected using structured questionnaire from 313 respondents using snowball sampling. Respondents demographic profile was analysed using Chi-Square test. Exploratory Factor Analysis (EFA) was used to identify the factors influencing the online buying behaviour. These influencing factors were subsequently tested along with respondent’s demographic characteristics using mean analysis to see if there is any difference exists. Finally, to measure the level of satisfaction of online buyers Importance - Performance Analysis (IPA) was carried out.

Result – The result of Chi-Square test revealed that gender doesn’t have any influence across demographic variables while making online shopping. Six factors were identified that influence the purchase intension of online

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customers, namely, user friendliness, promptness, risk related, convenience, security related, and trustworthiness. Moreover, for majority of factors there exists significant difference when these are analysed across demographic characteristics. The satisfaction level indicates that 21 variables out of 22 have positive gap and also 19 statements out of 22 are significant. Thus, the overall result of satisfaction level reveals that the customers are happy with the services quality as well as the security features provided by the online retailers.

Managerial implications – The online market (e-commerce) segment of the retail industry in India is going to see a tough competition in the coming years, so the need of the hour is to have well developed strategic plan for maintaining and upgrading the quality by online retailers. To meet the future potential of e-commerce in India, stakeholders should strive for innovative approaches through their value chain by providing custom assortments, targeted marketing, local language content, online-over-offline (OOO) infrastructure, and above all fool-proof security measures for all payments and transaction.

Keywords: Customer Satisfaction, E-Commerce, Retail Marketing, Risk Perception, Service Quality, Goa.

1. Introduction Online shopping or commonly termed as E-commerce is a form of electronic commerce which allows customer to buy goods or services directly from a seller over the internet hosted by various intermediary’s portals by using different website, which then will be promptly delivered to the customer’s address through authorised courier agents. The development of internet and communication technology has transformed the online shopping drastically and added a new dimension to the traditional mode of retail shopping. The increasing use of internet by younger generation in India is creating large opportunities for online retailers. India (461 million users) is the second largest online market behind China (765 million users) but ahead of US (244 million users), which is expected to increase to 635.8 million during the next two years’ time (IAMAI, 2017; Statistica, 2019; Wikipedia, 2019). Companies now prefer E-commerce platform for efficiently marketing their products to the customers.

In the present globalised economy, the internet is primarily a source of Information,

Communication, and Entertainment (may be termed as ICE age 2 which will transform the Indian business), which resulted in various forms of online business transactions. India is fastest growing e-commerce market worldwide and have exponential growth of e-commerce traders as well as e- commerce customers due to absence of e-commerce laws and low entry barriers, which give advantage to the e-commerce customers as they have wide range of choices (PwC 2014a). India can build shared prosperity for its 1.34 billion citizens by transforming the way the economy creates value if corporate India (specially e-commerce traders and government) addresses key societal needs and whole heartedly supporting the vibrant entrepreneurial sector. This all depends on efficient and effective partnership with government for developing new and novel approaches for capturing the untapped potential of e-commerce segment (PwC 2014b).

2. Purpose of the Study In India, the internet base users are around 566 million, making India the second largest online market after China but ahead of US. It

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is estimated that Indian market will reach to 635.8 million internet users by the year 2021 (IAMAI, 2017; Statistica, 2019; Wikipedia, 2019). The annual spending power of Indian consumers have been increasing, it is projected to be more than $1 trillion by 2022, along with the Indian middle class with increased purchasing power to be the largest segment of the population, with an average age of 29 years with just over 0.4 as the dependency ratio (PwC, 2014a; 2014b; 2015; 2019), which will result in around 70.7% of them becoming internet users and also potential online buyers. This being the case, there are no studies carried out on assessing the service quality assessment of the online customers in India in general and Goa in particular, where the entire work is broken in to three main issues, namely, identifying who the customers are, what motivates / influences the customers, and are the customers happy or not, which makes the present study unique which may fill the research gap that may be useful for various stakeholders, namely, academic institutions, government, retail entrepreneurs, online service providers, and also the general public.

3. Literature Review 3.1 Customer profiling Demographic characteristics of customers influences the buying behaviour, hence every marketer tries to identify who the customers are as the first and foremost component of their marketing strategy, in other words, the very essence of the Segmentation, Targeting and Positioning (STP) process. Many studies carried out identified which demographic variables influences the buying behaviour of online costumers. The study by Pereira (1998) identified that individual with moderate education will resist to change whereas an individual with advance education will challenge existing norms and show less resistance to change. Studies showed that person who are well educated and belongs to high income household are the early adopters of online shopping (Bellman et al., 1999; Chen et al., 2002). Thus, more the higher

education will lead to greater acceptance of new technologies used for shopping at the electronic malls.

Studies reveled that male prefer online shopping as they find it pleasing and convenient as compared to female (Davis et al., 2012; Basahih, 2013). They also found that person having proficiency in English language will prefer e-shopping. Contradictory to above studies, Park et al. (2009) revealed that compared to males, females search more product information including customer reviews and prefer using an assistant agent more while shopping online and it was supported by the Swilley and Goldsmith (2013) which concluded that there is no difference between male and female customers in terms of shopping online. Both genders are likely to shop online but, women were almost twice more likely to shop than men. Different customers have different mind sets towards the service quality they receive from online shopping, hence it becomes important to study the demographic characteristic of the customers and to check if there exist any variations among customers with respect to their demographic characteristics. For this purpose, following research question (RQ1) and related hypothesis has been formulated (H1);

RQ1: Is it possible to identify the demographic profile of online shopping customers in state of Goa?

H1: There is no significant difference exists between Male and Female with respect to Location, Age, Education, Marital status, Income and Occupation.

3.2 Factors influencing purchase intension of online customers Every customer buys products and services based on various factors, technically may be called as motivational factors like quality, price, appearance, delivery, attitude of sales person, and above all safety and security aspect. These same factors influence and molds the perception of customers in favour

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or against a product or service, hence the need for identifying these factors which influences the purchase intention of online customers. Belanger et al. (2002) identified that most of respondents do not trust web merchants, hence not in favour of online shopping. This security issue was studied by Limbu et al. (2011) stated online businesses should ensure the security of the transactions, provide a secure server, additional layers of security inbuilt in multiple payment options and guarantee against credit/debit card fraud. The online platform must be user-friendly in such way that the website should allow customer to interact with it to receive tailored information (Kim & Stoel, 2004). Even, Jasur and Haliyana (2015) concluded website quality is not the only determining factors that could increase consumer purchasing intention, but also other qualities like good customer service, efficient product distribution and positive reviews from customers also play an important role.

There are some internal factors which marketers have full control and also external factors where the marketers are finding it difficult to influence or motivate the customers. Benedict and Ruyter (2004) stated that customer’s attitudes toward online shopping and their intention to shop online are not only affected by ease of use, usefulness and enjoyment, but also by exogenous factors like consumer traits, situational factors, product characteristics, previous online shopping experiences, and trust in online shopping. Similarly, Kim and Lim (2001) also stated the factors of entertainment, convenience, and information quality and speed plays important role. Reliability with respect to steady performance over time, availability of website for usage, speed and download time, accessibility, consumer privacy, payment, delivery/offline fulfillment also plays an important role in buying behaviour. Since there are many factors which influences the buying behaviour of customer towards online shopping, it is crucial that one must study what are the important factors which influences or motivates the customers buying

behaviour, hence following research questions (RQ2 and RQ3) and related hypothesis (H2) has been formulated.

RQ2: What are the factors that influence the online shopping behaviour of the customers?

RQ3: Is there any difference in factors considered by online buyers across demographic profile?

H2: There is no significant difference exists between factors with respect to demographic variables.

3.3 Customer Satisfaction The ultimate aim of every marketer is to ensure that the needs of the customers are satisfied by providing quality goods and services so as to retain the customer base and creating ultimate customer loyalty. Satisfaction has been interpreted as a process or an outcome where customers compare performance with expectations and decide about confirmation or disconfirmation (Oliver & Desarbo, 1988). When it comes to online business, Kim and Lim (2001) focused on the attributes of the Business-to-Consumer websites and observed that consumer’s Internet shopping satisfaction is influenced by information quality, speed, reliability and entertainment. They also recommended that by adding entertainment factor with good information may leads to increase in customer satisfaction. Yang et al. (2003) studied about service quality and revealed that predominant service attributes leading to consumer satisfaction are responsiveness, convenience, credibility, reliability and ease of use.

Cho and Park (2001) even proposed Electronic Commerce User-consumer Satisfaction Index (ECUSI) instrument which reflects consumer satisfaction, user information satisfaction and electronic commerce. ECUSI consists of ten factors i.e. product information, additional information services, delivery time and charge, consumer services, product merchandising, ease of use, purchase result and delivery, site design, payment methods

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and purchasing process. All these factors will lead to customer satisfaction. Similarly, McKinney et al. (2002) also identified nine key constructs (relevance, timeliness, reliability, scope, perceived usefulness, access, usability, navigation, interactivity) for analyzing Web- customer satisfaction.

Khan et al. (2015) identified seven factors which will affect customer satisfaction to repurchase intention, namely, three types of risk factors (delivery, product and financial) and four other factors (return policy, convenience, price and product information). In any industry consumer satisfaction is very important, and if customers are not satisfied with the product and services offered by the company, they will shift and company will run into losses. Thus, identifying the particular services customers are not happy with and investing the proper resources to improve them is an urgent need in order to retain the customers. Hence, attempt is made to understand the satisfaction level of online customers. For this purpose, the following research question (RQ4) and related hypothesis (H3) was developed. RQ4: Is it possible to identify the level of

satisfaction of customers who prefer online shopping?

H3: There is no significant difference between what customers perceived and experienced with respect to services offered by online retailers.

4. Methodology The purpose of the study was to investigate customer’s perception towards the online shopping in Goa. The survey was carried out from November 2017 to March 2018 using a structured questionnaire distributed among 350 respondents, using snowball sampling, of which useable questionnaire was only 313 having a response rate of 89%. The questionnaires were divided into three sections, the first section to find out who the customers are, the second section to find out what motivates / influences the customers and the third section deals with satisfaction level of online buyers towards e-shopping.

Five-point Likert scale has been used, where 1 indicated strongly disagree and 5 indicates strongly agree. In order to analyse the result chi-square, Exploratory Factor Analysis (EFA), mean test, t-test, f-test and Importance Performance Analysis (IPA) was used.

5. Data Analysis and Discussion The following section will try to find the answers for the research questions proposed in earlier sections.

5.1 Who the customers are? A cross tabulation of customer’s demographic variables is performed taking their gender as controlling variable to see if there exists any significant difference among the male and female customers across the state of Goa when it comes to online purchase.

Exhibit 1 shows demographic profile of 313 respondents of which 144 were males and 169 were females. It indicates that majority of the respondents belong to North Goa (84% male and 89.9% female), which is similar to the result identified by Swilley and Goldsmith (2013) where no significant difference was found with respect to gender. In both the cases of male and female, age profile indicates the majority falls under 20-29 years of age (69.4% are Male and 71.6% are Female), which is equal to the average age 29 of Indian population. Majority of the respondents are having college education, of which 55.6% are male and 49.1% are female which is identical with respect to the result identified by Pereira (1998) and Chen et al. (2002). With respect to marital status, majority of respondents are coming under unmarried category, namely 88.9% are male and 87% are female, which also indicates the purchasing power available with the youngsters because of low dependency ratio (Chen et al. 2002). Majority of the respondents falls under the category of middle and lower income category (85.4% are male and 88.2% are female). One of the limitation of the study is that with respect to the occupation, majority of the respondents are students (78.5% are male and 76.9% are female), which may be rectified in the subsequent studies in future.

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Exhibit 1: Demographic Profile of Customers (N=313)

Demographic Characteristics Gender (%) χ2 value

(p value)Male Female

Location North Goa 84.0 89.9 2.439

(0.118)South Goa 16.0 10.1

Age

Up to 20 19.4 20.1

1.932 (0.748)

20 – 29 69.4 71.6

30 – 39 7.6 4.7

40 – 49 1.4 2.4

50 and Above 2.1 1.2

Education

Up to 10th 0.7 2.4

2.248 (0.489)

Up to 12th 14.6 17.2

Graduation 55.6 49.1

Post-Graduation 29.2 31.4

Marital Status Married 11.8 13.0 0.265

(0.607)Unmarried 88.9 87.0

Income

Less than Rs.1 Lakh 70.1 67.5 2.466

(0.481)Rs.1 Lakh – Rs.3 Lakhs 15.3 20.7

Rs.3 Lakhs – Rs.5 Lakhs 7.6 7.7

More than Rs.5 Lakhs 6.9 4.1

Occupation

Student 78.5 76.9

2.309 (0.679)

Profession 2.1 3.0

Service 16.0 16.6

Business 3.5 2.4

Housewife 0 1.2

Source: Primary data * Significant at 0.05

As it can be seen from Exhibit 1, the p-value is greater than 0.05 for all demographic variables, the formulated hypothesis (H1) of RQ1 that “There is no significant difference exists between Male and Female with respect to Location, Age, Education, Marital status, Income and Occupation” is accepted, stating demographic variables of customers do not have any influence while preferring online

shopping, which is a clear indication that technology is easily assessed by everyone making our life simpler than earlier days, due to which irrespective of age, gender, education and income every customer prefer e-shopping which contradicts the earlier studies and provide valuable insight to the e-commerce players which will help them in product marketing and also in product promotion.

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5.2 What factors motivates / influences the customers? To find out various motivational / influential factors, Factor analysis was carried out shown in Exhibits 2 which reveals that 24 statements are getting reduced in to six (6) factors having

an Eigen value cut off at 1 which explain 57.85% of the total variance. Reliability using Cronbach’s alpha gave a satisfactory result (α= 0.770), which is acceptable. KMO measure of Sampling Adequacy showed 0.710 which indicates that data is sufficient for exploratory factor analysis.

Exhibit 2: Factor influencing online purchase behavior

Factor Analysis (α =0.770, n=24) F1 F2 F3 F4 F5 F6 F1- User Friendly (α =0.855)

1. Simplicity of language 0.783 2. Easy to browse and compare 0.781 3. Quick confirmation of orders 0.714 4. Language and information content 0.709 5. Easy to search the product 0.696 6. Well- designed webpage 0.678 7. Quick transaction 0.625 8. Instruction on website 0.537

F2 - Promptness (α =0.689) 9. Exchange system 0.754 10. Quick restocking of products 0.719 11. Delivery is on time 0.654 12. Query replies 0.498

F3 - Risk Related (α =0.710) 13. Risky online payment methods 0.773 14. Delayed delivery 0.723 15. Fake online shopping sites 0.706 16. Undisclosed shipping/ delivery charges 0.666

F4 - Convenience (α =0.688) 17. Time consuming in processing a transaction 0.780 18. Complicated website 0.771 19. Lengthy process in placing an order 0.653

F5 - Security Factor (α =0.520) 20. Proper information is not provided 0.743 21. Lack of security in transaction 0.629 22. Non-disclosure of exact price 0.552

F6 - Trustworthiness (α =0.425) 23. False information about the product 0.740 24. Misuse of personal details 0.633

Source: Author’s own compilation based on primary data

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Among the 24 variables, most critical variable customers consider as the most influential one is “Simplicity of language” (1st statement of the factor user friendly - F1) with a loading factor of 0.783, which is similar to the result of Kim & Stoel (2004) and Basahih (2013). This may be due to the fact that the language used in online platform / website is simple and easily understood. This may be because of the fact that knowledge of English (read and speak) among the people is in the state of Goa is very high, hence understanding English from the online platforms are easy for the customers. These six (6) identified motivational / influential factors identified are similar to earlier studies, namely, F1: User Friendly (Kim and Lim, 2001; Kim & Stoel, 2004; Benedict and Ruyter, 2004), F2: Promptness (Jasur and Haliyana, 2015), F3: Risk related (Belanger et al., 2002), F4: Convenience (Kim and Lim, 2001; Benedict and Ruyter, 2004), F5: Security Related (Limbu et al., 2011), and F6: Trustworthiness (Kim and Lim, 2001).

5.3 Does the motivational / influencing factors have relation to demography? From the six (6) motivational / influential factors identified, mean test has been carried out across demographic variables to identify whether there is any significant difference between factors affecting the usage of online shopping across demographic profile of the customers. Exhibits 3 indicates the result of means test. With respect to F1: User Friendly, it can be noted that there isno significant

difference between demographic profile and User friendly factor. In case of F2: Promptness, there exists a significant association between the factor and Age. Individuals above 40 years will consider this factor while doing online shopping, which is similar to the result of Bellman et al., 1999. With respect to F3: Risk Related, there exists a significant relationship between factor and Income and location. People residing in North Goa having high income are more alert about the risk factor while shopping online, similar to the result of Bellman et al., 1999. In case of F4: Convenience, there is a significant difference between factor and occupation. Online shopping saves the time of employed people, hence they prefer online shopping which is also similar to the result of Bellman et al., 1999. With respect to F5: Security factor, demographic variables of age, income and occupation found to be significant similar to the result of Pereira, 1998; Bellman et al., 1999; and Chen et al., 2002. And finally in the case of F6: Trustworthiness, there exists a significant difference between occupation and location. The more the customers are educated and employed, the more will be their concern for trustworthiness. Hence the formulated hypothesis H2 for RQ3; There is no significant difference exists between factors with respect to demographic variables; is rejected with an exception of gender, education and marital status. It can be concluded that all the six factors are critical while shopping online, hence e-commerce players must consider upgrading their services in tune with all these factors.

Exhibit 3: Mean Analysis (t-test and F-test – p value of six Factors)

Demographic Variables F1 F2 F3 F4 F5 F6 Gender 0.84 0.07 0.99 0.83 0.60 0.37 Age 0.98 0.01* 0.07 0.34 0.02* 0.12 Education 0.09 0.62 0.54 0.89 0.19 0.45 Income 0.14 0.51 0.03* 0.09 0.03* 0.61 Occupation 0.29 0.29 0.49 0.00* 0.02* 0.03* Location 0.24 0.24 0.01* 0.08 0.88 0.02* Marital Status 0.59 0.34 0.26 0.44 0.86 0.25

Source: Primary data * Significant at 0.05

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Variables

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(P )

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Q ua

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1. Online shopping is Convenient 3.24 3.48 0.24 .003* C B 2. Ease of finding products 3.38 3.94 0.56 .000* B A 3. Trying something new 3.10 3.57 0.47 .000* C A 4. Quality of the product 3.19 3.97 0.78 .000* A A 5. Prices offered 3.49 3.80 0.31 .000* B B 6. Ease of comparison 3.34 3.75 0.41 .000* B A 7. Offers/Discounted prices 3.47 3.70 0.23 .003* B B 8. Products not available offline 3.59 3.82 0.23 .002* B B 9. No need to deal with salesman 3.59 3.84 0.25 .000* B B 10. Known or famous brand name 3.60 3.85 0.25 .001* B B 11. Assurance of on-time delivery 3.42 3.82 0.40 .000* B A 12. Ease of return and refund 3.36 3.74 0.38 .000* B A 13. Customer service 3.33 3.73 0.40 .000* B A 14. Privacy and security 3.45 3.74 0.29 .000* B B

R is

k Pe

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tio n

15. Judge quality online 3.22 3.36 0.14 .137 C B 16. Misuse of personal information 3.07 3.36 0.29 .001* C A 17. Fear of misuse of credit card 3.08 3.26 0.18 .014* C B 18. Risk of ‘Fake Stores’ 3.20 3.39 0.19 .035* C B 19. Fear of on time delivery after payment 3.25 3.55 0.30 .000* C A 20. Lack Of Full Cost Disclosure 3.18 3.39 0.21 .007* C B 21. Fake Online Reviews 3.42 3.32 -0.10 .208 D B 22. Performance of the product 3.25 3.37 0.12 .143 C B

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Exhibit 4: Importance Performance Analysis

5.4. Are the customers happy? Finally, the customer satisfaction level based on the two dimensions, namely, service quality and the risk perception of online buyers towards online shopping is analysed using IPA, both the original (Martilla & James, 1997) and modified (Abalo et al. 2007 and Chen, 2014) versions. Us- ing 22 variables in the form of statements (14 of them on service quality dimension and 8 of them on risk perception dimension) respondents were asked to rate for the importance they gave before online shopping (expectations) and the perform- ance derived (experiences) after online shopping with respect to the two dimensions. The overall reliability statistics for the service quality and risk perception was found to be within the ac- ceptable limit. The result of original and modified IPA is shown in Exhibits 4 in tabular (where variables marked

as ‘A’ shows unsatisfactory level). Of the total 22 variables, only 1 is in Quadrant A (concentrate here); 11 are in Quadrant B (keep up the good work); 9 in Quadrant C (low priority) and 1 in Quadrant D (potential overkill). This result is a good indicator that service quality and risk perception variables are giving online customers complete satisfaction, except for only one variable ‘quality of the product (4th variable under service quality dimension). This is very critical as physical checking and ensuring of quality in online is not possible. Many a time this problem is resolved by ‘ease of return and refund’ (12th variable under service quality dimension). Except ‘quality of the product’ variable, rest all 21 variables are having positive gaps, which clearly indicates that the customers who does online shopping are happy and satisfied with the service quality dimensions and risk perception dimensions.

Source: Author’s own compilation based on primary data *Significant at 0.05

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When it comes to modified IPA result (last column named ‘Diagonal’ of Exhibit 4), it can be seen that the variables falling under unsatisfactory category is increasing from one (1) to nine (9), which is a clear indication of not so good service quality and risk perception dimension among the online customers. Thus, e-commerce enterprises must put concentrated efforts to improve their online services so that those nine (9) variables will be moving away from the upper region (unsatisfactory) and lower region (satisfactory). When the probability values are considered, of the 22 variables, 19 are statistically significant having p-value is less than 0.05. This led to the conclusion that the formulated hypothesis (H3) of RQ4, “There is no significant difference between what customers perceived and experienced with respect to services offered by online retailers”, is rejected, because the performance values are more than the importance values, clearly indicating the customers are satisfied with their online shopping. Though, Customers are satisfied with the services provided by the online retailers, the one variable named ‘quality of product’ is falling under Quadrant A, proves that since there is absence of personal contact between buyer and seller, seller tends to sells the low quality goods by using online website. Even though customer gets product at lower price, the quality of the product is being compromised. With respect to gap between importance and performance, ‘fake online review’ variable has negative gap, which clearly indicates that company in order to clear its stock, they tend to promote it by making fake online reviews about the product.

This result of dissatisfaction among customers in the state of Goa with respect to other service industries reveals that there is high level of dissatisfaction among the customers with respect to entertainment industry (Castanha et al, 2017), banking sector (Dsouza, et al, 2018), and also in telecommunication industry (Goankar et al, 2018). But in the present study of e-commerce, the result is a good indication since 21 out of 22 variables are showing

positive gaps, which indicates a good sign of satisfaction level among the online buyers. Even though online buyers are satisfied

with the services but it will be too difficult to retain them if company continues to sell low quality products. Thus, the selfishness behaviour among the entrepreneur need to be curtailed and they should work on improving the quality of services thereby leading to customer satisfaction or else new players will capture all the market share by providing quality services to the existing customers whereby customers derive full satisfaction leading to complete customer loyalty.

6. Conclusion, Implications and Limitations 6.1 Conclusion Internet technology in India has been growing at very fact speed, due to which many companies started selling their products to customers by using online platforms. India being a largest country of having high customer base it becomes very important to study about the services offered by the online retailers and Goa in particular being a smallest state in India having somewhat similar to western culture, assessing the Goan customer perspective with respect to online shopping and also the satisfaction level of customers make this study special. Even though data is not normally distributed, chi-square test is applied to check the association which indicates all demographic variables are Insignificant with respect to Gender. This can be further studied by normally distribution of sample. Six factors were identified that influence the purchase intension of buyer while shopping online. Moreover, for majority of factors there exists significant difference between all six factors across demographic profile, which states that there exists a significant relationship between each of factor and demographic variables. IPA result showed that customers are happy with the services provided by the online retailers.

6.2 Managerial Implication The findings of the study have practical implications. Since customers are satisfied

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with the services provided by the e-retailers, it will be tough for new and existing local entrepreneurs to cope up with this competition. Hence they must take their business online by creating their own website so that they can promote their product online and also increase their profit. E-retailers must provide language translators on their website so that customer can read the product information and reviews in their own language which will help them to make their purchase decision. In online shopping physical presence of buyer and seller is absence so in such case seller shouldn’t try to cheat the customer by selling low quality goods or by promoting their product by using fake online reviews as most of the customers purchase the product after reading the previous reviews. If seller try to adopt these fake marketing techniques then it will be impossible for them to retain their customer as customers are too cautious about the quality of the product, when it comes to offline or online shopping. The online market (e-commerce) segment of the retail industry in India is going to see a tough competition in the coming years, so the need of the hour is to have well developed strategic plan for maintaining and upgrading the quality by online retailers. To meet the future potential of e-commerce in India, stakeholders should strive for innovative approaches through their value chain by providing custom assortments, targeted marketing, local language content, online-over-offline (OOO) infrastructure, and above all fool-proof security measures for all payments and transaction.

6.3 Limitations and Scope for further research The present study has few limitations which are discussed. The data was collected using snowball sampling technique which is not normally distributed. Thus, use of random sampling may give better and appropriate results which will help in generalization of the study findings. Along with this study, one can also extend the study towards assessing the perception of customers in developed countries, thereby will give insight if e-retailers differentiate its customers and their services

based on the development of the country and its standard of living. Even studying pricing and marketing strategy followed by them will provide good insight. To the best knowledge of the author, no study has been carried out to trace the potential of Retail Marketing using Online platform in Goa, along with studying the satisfaction level of customer using IPA, which make the present study unique. This study provides valuable information to the online retail marketers to increase their services standards, which will help them to retain its customers and also attract the new customers by using proper marketing strategies.

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