Brand Cart-ism: Analyzing the Impact of Shopping Carts on Consumer Preferences and Purchase Behavior in E-commerce Platforms

Abstract

The present study examines the shopping cart behavior on the leading e-commerce websites to understand the customer preferences and the volume of shopping as well as the pattern of purchase. Enumerating from mock data of seven popular brands – Amazon, Flipkart, Zepto, Zomato, Swiggy, Ajio, and Snapdeal, we studied cart usage metrics like that of average cart value, abandonment rate, and conversion rate. Information was gathered during simulated user sessions and consumers’ surveys with a view of mining for behavioral and attitudinal insights. Descriptive statistics, correlation, regression, ANOVA, cluster analysis, and principal component analyses was used to discover the relationship between cart features and the outputs of shopping. Results indicate that there are major platform differences achieved between Amazon and Zepto which showed higher conversion rates also providing higher values of cart but the abandonment of cart was negative to repeat purchases. Regression models had shown that average cart value and conversion rate have been primary predictors of volume of shopping. Differential shopper segmentation was achieved through cluster analysis but the complex behaviors were simplified to revealing factors through the use of PCA. These findings bring out the importance of shopping carts in determining consumer choices and efficacy of the platform and the insight is practical to e-commerce marketers and developers.