Pacific B usiness R eview I nternational
A Refereed Monthly International Journal of Management Indexed With THOMSON REUTERS(ESCI)
|
Dr Gouranga Patra Assistant Professor & Academic Coordinator School of Management Adamas University Barasat- Barrackpore Road Kolkata-700126 Contact No.:- 9051057134 E-mail:- gourangapatra@rediffmail.com |
Shoppers’ behavior is changing in a very fast and rapid mode. Marketing are not like a value delivery process, it is the value delivery on click i.e. one click shopping process. In India though it is a very childhood stage but the growth level is very high in comparison to other mode. It is very challenging task in front of marketers to develop a strong perceived value about the online buying which will turn into the online consumers’ satisfaction and adaptation. In the present study the researcher is trying to access the level of satisfaction of online buyers and what are basic entities of satisfaction which may help the online marketers for better customer services. The study confined Barasat city of west Bengal. 100 responses have considered for final analysis. The data has been analyzed by applying ANOVA technique. The result highlights that some of the factors are very much important in front of consumers’. These are product quality, financial security, merchandise planning, mode of payment and website design. The study gives strong indication to the marketer that to capture the semi urban area there is need to develop strong proposition on these particular issue and which are issue have a direct relation of online buying satisfaction of the shopper.
Keywords- E-Shopper, Online buying, E- marketers, Customer satisfaction, Digitalization.
Digital universe in India is doubling in size every two years and will multiply nine-fold between 2014 and 2020. As per ASSOCHAM, the value of Indian e-commerce market in 2012 was $8.5 billion and $16 billion in 2013 and it is estimated to be $56 billion in 2023. This is an estimation made by the marketer. But in the year 2023 the scenario will change in drastic mode because of the policy taken by Indian government. After the implementation of demonetization and GST it is clear signal to the market that the applications of digital transactions of Indian consumers’ are increasing. Not only this, government has taken so many initiatives for the people to encourage them and support them to adopt digitalization process. Online shopping or e-shopping is a form of electronic commerce which allows consumers to directly buy goods or services from a seller over the Internet using a web browser. Alternative names are: e-web-store, e-shop, e-store, Internet shop, web-shop, web-store, online store, online storefront and virtual store. Mobile commerce (or m-commerce) describes purchasing from an online retailer's mobile optimized online site or app. As the world get into the twenty-first century, the business approach of companies and manufacturer has changed due to the advent of the Internet with its rapid attributes (Ainin & Noor Ismawati, 2003). Usage of the Internet also computer devices, smart phones like emails and even social network websites like Face book, LinkedIn or Twitter has become an essential daily need for many people (Raad, Yeassen, Alam, Zaidan, & Zaidan, 2010). To reap the benefit of the Internet usage, numerous activities have been already undertaken in many firms and businesses for enhancing their official websites; also, some have thought about providing certain tools to speed up the profit of their business using the Internet and online communication. The emergence of e-commerce, which provides a new and effective way for businesses and customers in terms of performing online transactions through the electronic environment, especially the Internet (Adam, Bednall, & Featherstone, 2011; Anderson, 2007; Berthon, Pitt, Plangger, & Shapiro, 2012; Chan, Cheng, & Hsien, 2011; G.J. Dehkordi, Rezvani, Salehi, Eghtebasi, & HasanAbadi, 2012; El-Gohary, 2010; Genre, 2008; Hamill, 1997) has occurred as the result of these changes. Furthermore, some other firms are seeking to increase their return using e-marketing aspects. The overall internet penetration numbers and the diversity of Indian consumer has had a major impact on digital marketing and advertising trends and the overall adoption services in India. It is estimated that the rise in total number of internets users in India to over 550 Millions in 2018. It also depicts the urban/rural divide, wherein we see the number of rural internet users increasing upto 40 percent by the year. If we look at the key areas of the contribution of internet to GDP, the most important among them being e-commerce products, online content, and advertisements and classifieds. It is estimated that internet’s contribution to GDP is to set to grow at 23 percent compared to overall GDP growth of 13 percent. If we see the percentage break-up of all media segments, comparing 2016 numbers and the estimated figures of 2020. It is quite evident that TV will rule the media segments and it share will increase further in the coming years. We look at similar industry wise classification of Indian media and the entertainment sector, this time, in terms of absolute and growth numbers. Overall advertising revenues in 2014 grew at a growth rate of 14.2 percent over 2013 to reach Rs 414 billion. It is interesting to see that while digital advertising has the highest growth percentage of more than 44 percent (2014 over 2013), those numbers are projected to grow at around 30 percent (in terms of CAGR 2014-2019).
Solomon, 1998 in his study “Consumer behavior is the study of the processes involved when an individual selects, purchases, uses or disposes of products, services, ideas, or experiences to satisfy needs and desires”. In view for the Internet to spread out as a retail channel, it is imperative to realize the consumer’s mind-set, intention and conduct in light of the online buying practice: i.e., why they employ or falter to use it for purchasing? Consumer attitudes seem to have a significant influence on this decision. Schiffman, Scherman, & Long, (2003) in his study researched that “yet individual attitudes do not, by themselves, influence one’s intention and/or behavior. Instead that intention or behavior is a result of a variety of attitudes that the consumer has about a variety of issues relevant to the situation at hand, in this case online buying. Over time the Internet buyer, once considered the innovator or early adopter, has changed. Sultan and Henrichs (2000) in his study concluded that the consumer’s willingness to and preference for adopting the Internet as his or her shopping medium was also positively related to income, household size, and innovativeness. Vijay, Sai. T. & Balaji, M. S. (2009), revealed that Consumers, all over the world, are increasingly shifting from the crowded stores to the one-click online shopping format. However, in spite of the convenience offered, online shopping is far from being the most preferred form of shopping in India.
Saprikis, Vaggelis et al. (2010) analyzed the perceptions of Greek university Student’s on online shopping in terms of demographic profile, expectations of online stores, advantages and problems related to online purchases. He found that there were lot of differences regarding online purchases due to the various consumers’ characteristics and the types of products and services. The study concludes that adopters were having higher expectations from e- marketers on issues related to privacy policy and risk. The differences found were related to their particular perceptions on advantages and problems of online shopping.
Syed et al. (2008) analyzed that there were four key factors which influenced the young consumers’ perceptions towards online shopping. They found that those factors were website design, website reliability, customer service and privacy. They also discussed that there was no difference among the perceptions of various races towards online shopping in Malaysia. The most consistent factor that influenced buyer’s behavior towards online shopping was found to be Trust. E-retailers need to add trust and reliability which is everything for the buyers. Asakawa and Okano (2007) analyzed the factors influencing consumers’ perception of online shopping and explained how this perception affects their online-shopping behavior. From the research, they found that those factors were convenience, anxiety regarding security and poor navigation. He found that convenience had a positive influence on online shopping whereas anxiety regarding security and poor navigation had a negative influence. Shergill and Chen.(2005), discussed the relationship between the factors affecting the buyers’ behavior towards online shopping and the type of online buyers. They also investigated the different perceptions of different types of online buyers towards the online shopping. They found website design, website reliability, website customer service and website security or privacy were the factors which were influencing their buying behavior of different people. This research also found the different perceptions and evaluation criteria of the four types of online buyers; i.e., trial, occasional, frequent and regular online buyers. Adrita Goswami et.al (2013), Studied “Customer Satisfaction towards Online Shopping with Special Reference to Teenage Group of Jorhat Town” study concludes that online customers are satisfied. This research explicitly indicates that online marketer should give more importance on price factor and after sale factor. In this competition era all the online marketers should have to concentrate on the customer’s satisfaction to retain the existing customers and have to offer new scheme day by day to attract the new customers. Alam and Yasim (2010) reported that that website design, reliability, product variety and delivery performances are the four key factors influencing consumers’ satisfaction of online shopping. Ahn et al. (2004); Lee and Joshi (2007); found that delivery performance has significant influence on customer satisfaction. Vyas and Srinivas (2002), in their paper stated that majority of the internet users were having positive attitude towards online buying of products/services. There exists a need for developing awareness about consumers’ rights and cyber laws. They also emphasized on better distribution system for online products. Article published by Business Today (2007), the article provides information on the 10 best online stores in India. It cites that the "Personal Shopper" tool of Style Feeder Company helps one to shop and narrow down purchases. The Thread less. COM Company offers an online community-centered apparel store. The comparison shopping site of PriceForSure.COM company offers presents online catalogs, video uploads, live- Web television, and auction capabilities. One study conducted by Jones, Christie, Soyoung Kim(2009), on “Influences of retail brand trust, off-line patronage, clothing involvement and website quality on online apparel shopping intention”, this study examines the influence of retail brand trust, off-line patronage, clothing involvement, and website quality on online apparel shopping intention for young female US consumers. Retail brand trust, off-line patronage, clothing involvement and two factors of website quality were found to significantly influence online apparel shopping intention. Off-line patronage was the strongest predictor of online shopping intention. Implications for multi-channel apparel retailers were discussed based on these findings.
There are lots of researches, discussions and debates going on about the online marketing and its different issues. From the literature review it gives us indication that marketers are trying to find out the most effectives factors which are influencing consumers’ satisfaction. There are also some other factors consumers’ consider not to adopt online buying. Apart from these two is one area which need to develop that is trust and reliability of the marketers who provides information through their website. On the basis of the above thought in the present study we are also trying to find out these issues in this particular region i.e. Barasat city of West Bengal.
Market is very dynamic in nature; it changes in a very rapid mode. Consumers are also very much time conscious and quality conscious rather than price. If we look into the young generation of India there is no such significant differentiation between the outer world in terms of preferences and buying behavior. In this context it is an emerging issue in front of marketers to understand the perception and satisfaction level of consumers towards online marketing in the different sphere of countries. In this context the present study consider a place i.e. Barasat city of Kolkata. This is city have a smell of urban culture but the traditional outlook and also commercially sound. For the study we consider the whole Barasat city. The inner thought of the study to know the impact and involvement of young people about the trends and perception of the online marketing and their satisfaction level. It will give us a strong signal about the development of online marketing of this area. The study also helps the marketer to know the satisfaction level of semi urban consumers’ towards online buying and also help them to strengthen the factors which are the reason of satisfaction.
Objective of the study:
The major objective of the study is to find out the preference level of consumers on online marketing, and their level of satisfaction towards online purchasing in this particular region of West Bengal.
The study most focuses on consumers’ trends and satisfaction level towards e marketing. The study considers those factors which are related to consumer satisfaction. Secondary data is important to give a general view but to know the real situation we need the help of primary data. As a result the study design the questionnaire mainly close ended. One hundred data have been considered for the analysis. The data have been collected by using random sampling method. Minimum precautions have been taken care for the collection of data, i.e. respondents have minimum level of online purchasing exposure. Face to face and mail responses have been considered for analysis. The data has been measured by 5 point likert scale. The time period of the data collection was three month. Data have been collected from the different place of Barasat market, where maximum retail outlet situated, and also three universities, situated at Barasat. For the analysis of the data we used correlation to find out internal association among variables, ANOVA and Turkey HSD test.
In the study, the data has been collected based on some basic parameter to know the weighted of the respondents. These are age wise (18-25 years, 25-35 years, 35-45 years), spending pattern of the respondents ( Rs 10000-20000 per year, 20001-50000, more than 50000) and gender wise. The data has been analyzed by help of SPSS.
Mechanism of the study:
The present study is an attempt to find out the consumer preference level towards the selection of online channel (site) and their satisfaction level. There so many components measure the consumers’ satisfaction. In the research we were trying to assess the overall satisfaction level of the respondents in this particular region. From the geographic characteristics this is location comes under the mix of rural and urban. People have traditional outlook. As a result they have limited level of exposure about online purchasing. Other drawback, that online marketers are not covering this place because of location. Therefore, in the present study, the researcher considers some important parameter of consumer satisfaction which is used by other study. These are product quality, product delivery (related to distribution process, timing), merchandise planning (availability and variety of merchandise available for online buying), financial security (authentication of transaction), mode of payment (payment process and mechanism), site design (website design based on usability, accessibility), promotional system (contact point to spread the promotional related information).
Data Analysis and Interpretation:
Table no-1
Consumer preferences on online marketing site
|
Site preference |
Number |
Preference frequency |
Non preference frequency |
|
Flipcart |
100 |
83 |
17 |
|
Snapdeal |
100 |
33 |
67 |
|
Amazon |
100 |
71 |
29 |
|
Irctc |
100 |
21 |
79 |
|
Jabong |
100 |
09 |
91 |
(Source- primary data)
In the present study we noted the respondent responses on preference level of online marketing site for shopping. It is observed that this particular are consumers’ preference level are higher in Flipcart (frequency-83%), Amazon (frequency-71%) and Snapdeal (frequency-33%). But other marketing site, preference levels are low. It is clear that this is the area are not much exposed by the different online marketer. It could have a good result if all players put their step for development of consumer awareness. There is a need of more promotion to develop the consumer interest about the online marketing.
Table no-2
Consumers’ preferences on online product purchase
|
Product preference |
Number |
Preference frequency |
Non preference frequency |
|
Electronics |
100 |
61 |
39 |
|
Grocery |
100 |
4 |
96 |
|
Books |
100 |
37 |
63 |
|
Clothes |
100 |
56 |
44 |
|
Cosmetics |
100 |
24 |
76 |
(Source- primary data)
The above table highlighted the purchasing pattern of different categories of products through online of the consumers’ in this region. It came from the data that consumers’ are preferring more electronic related goods and clothes item. But there is very less interest of the consumer towards the purchasing of cosmetic related product. It is a debatable topics and the result show that involvement level of female consumers’ are less towards purchasing of online product in comparison to men. This may be the reason of level of information processing towards cosmetics product by the online marketer are low.
Table no-3
Pearson Correlation among different factors of satisfaction
|
Product quality |
Product delivery |
Merchandise planning |
Financial security |
Mode of payment |
Site design |
Promotional design |
||
|
Product quality |
Pearson Correlation |
1 |
.174 |
.257* |
.456** |
.037 |
.666** |
-.029 |
|
Sig. (2-tailed) |
.087 |
.011 |
.000 |
.717 |
.000 |
.775 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
|
|
Product delivery |
Pearson Correlation |
.174 |
1 |
.051 |
.482** |
.015 |
.055 |
.203* |
|
Sig. (2-tailed) |
.087 |
.619 |
.000 |
.882 |
.592 |
.045 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
|
|
Merchandise planning |
Pearson Correlation |
.257* |
.051 |
1 |
.103 |
.233* |
.578** |
.229* |
|
Sig. (2-tailed) |
.011 |
.619 |
.313 |
.021 |
.000 |
.023 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
|
|
Financial security |
Pearson Correlation |
.456** |
.282** |
.103 |
1 |
.174 |
.281** |
.421** |
|
Sig. (2-tailed) |
.000 |
.005 |
.313 |
.086 |
.005 |
.000 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
|
|
Mode of payment |
Pearson Correlation |
.037 |
.015 |
.233* |
.174 |
1 |
.198 |
.088 |
|
Sig. (2-tailed) |
.717 |
.882 |
.021 |
.086 |
.051 |
.387 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
|
|
Site design |
Pearson Correlation |
.258* |
.055 |
.578** |
.681** |
.198 |
1 |
.093 |
|
Sig. (2-tailed) |
.010 |
.592 |
.000 |
.000 |
.051 |
.364 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
|
|
Promotion design |
Pearson Correlation |
-.029 |
.203* |
.631* |
.421** |
.088 |
.093 |
1 |
|
Sig. (2-tailed) |
.775 |
.045 |
.000 |
.000 |
.387 |
.364 |
||
|
N |
98 |
98 |
98 |
98 |
98 |
98 |
98 |
We have done the correlation analysis to know the association among the variables. In the research the researcher have considered seven different types of components which are indicates of consumer satisfaction about the online buying in general. When compare with product quality, it is observed that product quality is strongly associated with financial security and site design. Which indicates that quality concept and high quality relates to high price is a matter of fact in front of consumers’. Visualization of the product through online site helps the consumers’ to develop a strong proposition on quality related issue. In the next stage product delivery is partially associated with financial security and merchandise planning. Merchandise planning has positive correlation with site design and promotional design. Financial security has positively correlated with product quality and promotional design. Site design is strongly associated with product quality and financial security. Promotional design is strongly associate with merchandise planning and financial security. In this regards it comes all the variables are strongly associated with each other. But out of the above fact, it reveals that product quality, financial security and site design have an important role to shape the online buyers satisfaction level.
Table No-4
|
ANOVA- AGE WISE |
||||||
|
Sum of Squares |
Df |
Mean Square |
F |
Sig. |
||
|
Product quality |
Between Groups |
1.778 |
2 |
.889 |
2.997 |
.055 |
|
Within Groups |
28.181 |
98 |
.297 |
|||
|
Total |
29.959 |
100 |
||||
|
Product delivery |
Between Groups |
3.105 |
2 |
1.553 |
1.956 |
.147 |
|
Within Groups |
75.395 |
98 |
.794 |
|||
|
Total |
78.500 |
100 |
||||
|
Merchandise planning |
Between Groups |
.757 |
2 |
.379 |
.558 |
.574 |
|
Within Groups |
64.437 |
98 |
.678 |
|||
|
Total |
65.194 |
100 |
||||
|
Financial security |
Between Groups |
4.715 |
2 |
2.358 |
4.737 |
.011 |
|
Within Groups |
47.285 |
98 |
.498 |
|||
|
Total |
52.000 |
100 |
||||
|
Mode of payment |
Between Groups |
.193 |
2 |
.097 |
.145 |
.865 |
|
Within Groups |
63.123 |
98 |
.664 |
|||
|
Total |
63.316 |
100 |
||||
|
Site design |
Between Groups |
4.654 |
2 |
2.327 |
5.127 |
.008 |
|
Within Groups |
43.112 |
98 |
.454 |
|||
|
Total |
47.765 |
100 |
||||
|
Promotion design |
Between Groups |
5.729 |
2 |
2.865 |
4.034 |
.021 |
|
Within Groups |
67.465 |
98 |
.710 |
|||
|
Total |
73.194 |
100 |
||||
One way between group analysis of variance was conducted to explore the impact of age on different factors of satisfaction. The above table indicates that there are significant difference between means of the factors of satisfaction like product quality (F= 2.997, P<0.05), Financial security (F= 4.737, P<0.011), Site design (F=5.127, P<0.008) and Promotional design (F=4.034, P<0.021) with the different age group of respondents. But there are no difference observed on the other factors of satisfaction like mode of payment, merchandise planning and product delivery. From the results it is clear the different age group have different level of expression on the satisfaction level of online purchase of the consumers in this region. The data also states that these are the factors play an important role in developing the satisfaction level of consumers’ about their buying thorough online.
Table no-5
Post hoc
|
Multiple Comparisons |
|||||||
|
Tukey HSD |
|||||||
|
Dependent Variable |
(I) age |
(J) age |
Mean Difference (I-J) |
Std. Error |
Sig. |
95% Confidence Interval |
|
|
Lower Bound |
Upper Bound |
||||||
|
Product quality |
18-25 |
25-35 |
.219 |
.143 |
.281 |
-.12 |
.56 |
|
35-45 |
-.181 |
.132 |
.360 |
-.50 |
.13 |
||
|
25-35 |
18-25 |
-.219 |
.143 |
.281 |
-.56 |
.12 |
|
|
35-45 |
-.400* |
.163 |
.042 |
-.79 |
-.01 |
||
|
35-45 |
18-25 |
.181 |
.132 |
.360 |
-.13 |
.50 |
|
|
25-35 |
.400* |
.163 |
.042 |
.01 |
.79 |
||
|
Financial security |
18-25 |
25-35 |
.438 |
.185 |
.052 |
.00 |
.88 |
|
35-45 |
-.202 |
.171 |
.467 |
-.61 |
.21 |
||
|
25-35 |
18-25 |
-.438 |
.185 |
.052 |
-.88 |
.00 |
|
|
35-45 |
-.640* |
.212 |
.009 |
-1.14 |
-.14 |
||
|
35-45 |
18-25 |
.202 |
.171 |
.467 |
-.21 |
.61 |
|
|
25-35 |
.640* |
.212 |
.009 |
.14 |
1.14 |
||
|
Site design |
18-25 |
25-35 |
.470* |
.177 |
.025 |
.05 |
.89 |
|
35-45 |
-.150 |
.163 |
.630 |
-.54 |
.24 |
||
|
25-35 |
18-25 |
-.470* |
.177 |
.025 |
-.89 |
-.05 |
|
|
35-45 |
-.620* |
.202 |
.008 |
-1.10 |
-.14 |
||
|
35-45 |
18-25 |
.150 |
.163 |
.630 |
-.24 |
.54 |
|
|
25-35 |
.620* |
.202 |
.008 |
.14 |
1.10 |
||
|
Promotion design |
18-25 |
25-35 |
.467 |
.221 |
.093 |
-.06 |
.99 |
|
35-45 |
-.243 |
.204 |
.463 |
-.73 |
.24 |
||
|
25-35 |
18-25 |
-.467 |
.221 |
.093 |
-.99 |
.06 |
|
|
35-45 |
-.710* |
.253 |
.016 |
-1.31 |
-.11 |
||
|
35-45 |
18-25 |
.243 |
.204 |
.463 |
-.24 |
.73 |
|
|
25-35 |
.710* |
.253 |
.016 |
.11 |
1.31 |
||
On the basis of ANOVA results, we have analyzed post hoc test to find out the impact of one group with another group of respondents based on different level of age group. In ANOVA table we found significant difference between different levels of age group on product quality related issue. It is observed that age group 25-35 years and age group 35-45 year are statistically significant difference but no significant with 18-25 years. When we examine in respect of 35-45 years, it shows significant difference with 25-35 year. But the age group 18-25 years score has no association with other two level of age.
Online consumer have identified that financial security is also a part of satisfaction. As ANOVA result shows the significant mean difference between different levels of age. From the post hoc test it clears that age group 18-25 and age group 25-35 are statically significant difference on financial security. The other side age group 25-35 and age group 35-45 are also statistically significant. But no difference observed between age group 18-25 and 35-45 on the financial security related issues.
There is significant mean difference between different level of age and consumers satisfaction on site design of online product. But we cross examine the result it shows that age group 18-25 and age group 25-35, age group 25-35 and age group 35-35 are statistically significant. But there is no positive association between the age group 18-25 and 35-45, which is not significant. That indicates site design is an important component of consumer satisfaction.
Online marketers also emphasize about their promotional strategy and that reflect in their promotional contents design. Customers select their product in online by the visual display and all the benefit related information they get from the respective online marketers. So deliberation of proper promotional information helps the consumers’ to clear their information, to persuade them about the product and brand and to remind them. When we analyzed the result it is observed that there is a significant different in the age group of 25-35 and 35-45 on the promotional issue. Nut no difference observed in between the age group of 18-25 and 25-35.
Table no-6
|
ANOVA- BUYING CAPACITY |
||||||
|
Sum of Squares |
Df |
Mean Square |
F |
Sig. |
||
|
Product quality |
Between Groups |
2.369 |
2 |
1.185 |
4.079 |
.020 |
|
Within Groups |
27.590 |
98 |
.290 |
|||
|
Total |
29.959 |
100 |
||||
|
Product delivery |
Between Groups |
4.266 |
2 |
2.133 |
2.729 |
.070 |
|
Within Groups |
74.234 |
98 |
.781 |
|||
|
Total |
78.500 |
100 |
||||
|
Merchandise planning |
Between Groups |
9.768 |
2 |
4.884 |
8.371 |
.000 |
|
Within Groups |
55.426 |
98 |
.583 |
|||
|
Total |
65.194 |
100 |
||||
|
Financial security |
Between Groups |
2.635 |
2 |
1.318 |
2.536 |
.085 |
|
Within Groups |
49.365 |
98 |
.520 |
|||
|
Total |
52.000 |
100 |
||||
|
Mode of payment |
Between Groups |
4.096 |
2 |
2.048 |
3.286 |
.042 |
|
Within Groups |
59.220 |
98 |
.623 |
|||
|
Total |
63.316 |
100 |
||||
|
Site design |
Between Groups |
10.491 |
2 |
5.245 |
13.368 |
.000 |
|
Within Groups |
37.275 |
98 |
.392 |
|||
|
Total |
47.765 |
100 |
||||
|
Promotion design |
Between Groups |
2.095 |
2 |
1.048 |
1.400 |
.252 |
|
Within Groups |
71.099 |
98 |
.748 |
|||
|
Total |
73.194 |
100 |
||||
The other angle of the study is to judge the satisfaction level of online buyers based on their buying pattern. In general sense it is very essential part of the online marketer to segment the customer based on classification of users. This helps the marketer to design their product, price, quality as well as development of all these as and when required. As a result of that they can retain more numbers of customers. We analyzed the different level of buying patterns of respondents with different factors of level of satisfaction. It is observed from the result that product quality (F= 4.079, P<0.05), merchandise planning (F= 8.371, P<0.05), mode of payment (F=3.286, P<0.05) and site design (F=13.368, P<0.05) have a significant different in the different level of buying pattern. But the site design and merchandise planning are very strong association with the buying pattern of the respondents. It is very clear signal of the online marketers that to develop a strong customer association, there is a need to develop product quality, proper merchandise planning and site design. When we look into the other components of satisfaction, the result shows that product delivery and financial security are not significant difference but partially associated with different level of buying pattern (here P=.0.07 and 0.80 which is higher than 0.05).
Table no-7
POST HOC
|
Multiple Comparisons |
|||||||
|
Tukey HSD |
|||||||
|
Dependent Variable |
(I) v2 |
(J) v2 |
Mean Difference (I-J) |
Std. Error |
Sig. |
95% Confidence Interval |
|
|
Lower Bound |
Upper Bound |
||||||
|
Product quality |
Low buying |
M Buying |
.103 |
.121 |
.672 |
-.18 |
.39 |
|
L Buying |
-.333 |
.152 |
.078 |
-.70 |
.03 |
||
|
M buying |
Low buying |
-.103 |
.121 |
.672 |
-.39 |
.18 |
|
|
L buying |
-.436* |
.154 |
.015 |
-.80 |
-.07 |
||
|
L buying |
Low buying |
.333 |
.152 |
.078 |
-.03 |
.70 |
|
|
M buying |
.436* |
.154 |
.015 |
.07 |
.80 |
||
|
Merchandise planning |
Low buying |
M Buying |
.440* |
.171 |
.031 |
.03 |
.85 |
|
L Buying |
-.419 |
.216 |
.134 |
-.93 |
.10 |
||
|
M buying |
Low buying |
-.440* |
.171 |
.031 |
-.85 |
-.03 |
|
|
L buying |
-.859* |
.218 |
.000 |
-1.38 |
-.34 |
||
|
L buying |
Low buying |
.419 |
.216 |
.134 |
-.10 |
.93 |
|
|
M buying |
.859* |
.218 |
.000 |
.34 |
1.38 |
||
|
Mode of payment |
Low buying |
M Buying |
.368 |
.177 |
.098 |
-.05 |
.79 |
|
L Buying |
-.127 |
.223 |
.836 |
-.66 |
.40 |
||
|
M buying |
Low buying |
-.368 |
.177 |
.098 |
-.79 |
.05 |
|
|
L buying |
-.496 |
.225 |
.076 |
-1.03 |
.04 |
||
|
L buying |
Low buying |
.127 |
.223 |
.836 |
-.40 |
.66 |
|
|
M buying |
.496 |
.225 |
.076 |
-.04 |
1.03 |
||
|
Site design |
Low buying |
M Buying |
.500* |
.140 |
.002 |
.17 |
.83 |
|
L Buying |
-.367 |
.177 |
.101 |
-.79 |
.05 |
||
|
M buying |
Low buying |
-.500* |
.140 |
.002 |
-.83 |
-.17 |
|
|
L buying |
-.868* |
.178 |
.000 |
-1.29 |
-.44 |
||
|
L buying |
Low buying |
.367 |
.177 |
.101 |
-.05 |
.79 |
|
|
M buying |
.868* |
.178 |
.000 |
.44 |
1.29 |
||
|
*. The mean difference is significant at the 0.05 level. |
|||||||
The post hoc test has been conducted of all these variables of consumer satisfaction but in the ANOVA table some of the variables are statistically significant. Here we kept that variable to find out their internal relationship. We examine that on the product quality related issue low buying capacity consumer are not statistically significant between medium buying consumer and high buying pattern consumers’. There is significant difference between medium buying patterns (Rs 20000-50000 per year) with high buying pattern (more than Rs 50000 per year) and partially difference between high buying patterns with low buying capacity.
When we try to analyze the difference in respect of merchandise planning wit buying pattern, it is observed that there are very strong statistically significant difference between low buying pattern and medium buying pattern and medium buying pattern with high buying habits. We did not find any difference between low buying capacities with high buying capacity.
On the transaction related issues like consumers’ satisfaction of mode of payment on online purchase are being considered here. From the analysis, it is observed there is no such statistically significant difference observed with the different buying pattern of the respondents. Except cases like medium buying pattern and high buying habit group are partially associated. But in the ANOVA result there is significant mean difference between different levels of buying pattern and mode of payment.
As we know that site design is an important aspect of online consumer. Because in online, there is no touch and feel concepts applied. Consumers’ select the product from the website visualization. The Post Hoc results also support this thought. It is seen that there is strong statistically difference between low buying habit consumer and medium buying habit consumer and other are medium buying pattern respondents and high buying respondents. But no significant difference observed between low and high.
The study has been conducted to know the preference and satisfaction level of the consumers’ in this region. As the online marketing concepts are growing in very faster mode, in this juncture it is important to know the consumers’ mental thought of this kind of place. The study considered the factors which are most basic component for understanding the consumers’ satisfaction about online buying. The study shows that Snapdeal, Flipcart and Amazon are the most preferable online marketing site are in a position to fulfill consumers’ desire. In terms of buying preferences, it indicates that clothes, cosmetics and book are more in percentage rather than other item. This simple result indicates that the developments of consumers thought towards online marketing have been started. In this paradigm it is very much important task of the online marketer to know the consumer interest which may develop long term commitment on online buying.
Correlation analysis indicates the bonding or association between the variable and it shows that the different factors of satisfaction are associated with each other. From the ANOVA techniques it is clear that product quality and delivery are strongly associated with the gender. Different age groups of respondents are very much conscious about product quality and financial security and promotional design (like age group 25-35 and 35-45) but age group 18-25 are little bit casual in this matter but all are aware about product visualization through website, that is why site design is an important issue. This result gives a strong signal of marketer because in online marketing age groups are crucial factor to segment the market. This result revealed that product quality, financial security and promotional design are important parameter for online buyers. It connects with buying capacity of different level of age groups. It differ them from offline buying process. But to attract young and also other age customers, there is a need of web site development which may develop consumer thought process towards online product. But when the study examines the result based on the spending pattern, it shows that medium and large buying capacity consumers’ put their strong opinion on product quality, merchandise planning and website design. Regarding website design low spending capacity people have strong association. Overall the study indicate that to increase the satisfaction level of online buyers there is need to develop the strong proposition on quality of product, merchandise planning (that mean variety of merchandise), financial security (transaction related difficulties) and website design (in terms of access and easy to handle).
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