Primary Research Objective4
Secondary Research Objectives4
DISCRIMINANT WITH CLUSTER ANALYSIS5
Annexure 1a: Agglomeration Schedule for Cluster Analysis5
Annexure 1b: Correlation Matrix for Factor Analysis5
Annexure 1c: ANOVA Table for Regression Analysis5
Annexure 2a: Questionnaire for Exploratory Research5
Annexure 2b: Final Questionnaire5
The project focused on finding out the Online Buying Behaviour of consumers between the age group of 18-30 years. The stated objective of the study was further broken down to secondary objectives which aimed at finding information regarding the popular product categories, frequency of purchases, average spending, factors affecting buying decision process etc.
The exploratory research was carried out with 27 respondents with a set of 10 open ended questions. The exploratory findings helped us in determining the key factors which needed to be further explored for research. The secondary research was taken from sources like Indian Journal of Management Technology, Zinnov LLC, and ACNielson. The questionnaire designed had 9 questions and was administered to 106 respondents. Each of the questions was designed to satisfy at least one of the secondary objectives of the research. The response format was of a mixed variety which also helped in better determination of outcomes.
Post data reduction, Cross tabulation was used for analyzing the causal relationship between different pairs of factors. ANOVA was also applied to a pair of factors.
The Regression Analysis between the dependent variable “Average Amount spent per purchase made online” and the independent variables of Frequency of Purchase of products and services online, owning a Credit Card, Marital Status, Education and Age, was done. The regression model did not give any significant correlation between the factors and the Dependent Variable. Although there is a strong interdependence between a few variables yet when taken collectively they do not show high correlation.
Then, Cluster Analysis was done on the data and based on the responses; we could divide the respondents in three clearly distinct groups. We named them: Confident Online Buyer, Unsure surfer and Mall Shopper. We also performed Discriminant with Cluster Analysis to predict cluster membership of consumers based on their attitude towards online shopping.
We performed Factor Analysis to find the major factors. We could identify six factors: Value for Money, Trust, Connected and Up to date, Problems Faced, and Traditionalism.
India has the world’s 4th largest Internet user base, which crossed the 100 million mark recently. Better connectivity, booming economy and higher spending power helped the Indian e-commerce market revenues to cross $500 million with a CAGR of 103% over last 4 years. This may not be a significant number, averaging to only around $5 per user per year.
With the above background in mind, this research has been conducted to gain an insight into the online buying behaviour of consumers. The objective is to explore the factors which influence online purchase, the psychographic profile of the consumer groups and understanding the buying decision process.
Our findings should help an Internet Marketer to determine the product/service categories to be introduced or to be used for marketing for a specific segment of consumers. This would also allow them to add or remove services/features which are important in the buying decision process. This study however does not aim to identify newer areas to introduce new services, nor should it be used to...