Analyzing the Browsing Basket: A Latent Interests-Based Segmentation Tool

The increasing importance of online distribution channels is paralleled by a rising interest in gaining insights into the customer journey to online purchases. In this paper we propose an easy-to-implement two-step procedure that enables online marketing managers to disentangle the complex interrelationships hidden behind observed Internet browsing behavior across websites. Utilizing the procedure allows managers to gain a better understanding why Internet users are visiting their website(s) and how these visits are related to purchases. In the first step, the procedure uncovers latent interests underlying online users’ browsing behavior. In the second step, we segment the online users based on their uncovered latent interests. This way, online marketers may understand how segment-specific combinations of latent interests are linked to purchase behavior. We apply the procedure to ComScore clickstream data across 472 websites. We show that there is considerable heterogeneity among online users both regarding online browsing habits, combinations of latent interests, and their conversion into online purchases. For example, some users are interested in apparel and travel service opposed to users who are interested in entertainment tickets. Our empirical analysis confirms that a relatively small fraction of online users realize 70% of online spending. In addition, we detect substantial segment-specific differences of shopping behavior across categories, the most important product categories being apparel as well as food & beverages. Our descriptive perspective comes up with surprising associations among the websites which can be interesting for online marketers.