A Large-Scale Study of Online Shopping Behavior

TL;DR

This large-scale study analyzes how Internet browsing habits relate to online shopping behavior, revealing predictive patterns and surprising insights about consumer effort and loyalty across Amazon and Walmart.

Contribution

It provides the first extensive analysis linking browsing habits to online shopping behavior using data from over 88,000 users.

Findings

Browsing behavior predicts purchase patterns.

Expensive products do not require more effort.

Loyal users spend less time shopping.

Abstract

The continuous growth of electronic commerce has stimulated great interest in studying online consumer behavior. Given the significant growth in online shopping, better understanding of customers allows better marketing strategies to be designed. While studies of online shopping attitude are widespread in the literature, studies of browsing habits differences in relation to online shopping are scarce. This research performs a large scale study of the relationship between Internet browsing habits of users and their online shopping behavior. Towards this end, we analyze data of 88,637 users who have bought more in total half a milion products from the retailer sites Amazon and Walmart. Our results indicate that even coarse-grained Internet browsing behavior has predictive power in terms of what users will buy online. Furthermore, we discover both surprising (e.g., "expensive products do not come with more effort in terms of purchase") and expected (e.g., "the more loyal a user is to an online shop, the less effort they spend shopping") facts. Given the lack of large-scale studies linking online browsing and online shopping behavior, we believe that this work is of general interest to people working in related areas.