Selling vs. Profiling: Optimizing the Offer Set in Web-Based Personalization
Mookerjee, Vijay S.
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We study the problem of optimally choosing the composition of the offer set for firms engaging in web-based personalization. A firm can offer items or links that are targeted for immediate sales based on what is already known about a customer's profile. Alternatively, the firm can offer items directed at learning a customer's preferences. This, in turn, can help the firm make improved recommendations for the remainder of the engagement period with the customer. An important decision problem faced by a profit maximizing firm is what proportion of the offer set should be targeted toward immediate sales and what proportion toward learning the customer's profile. We study the problem as an optimal control model, and characterize the solution. Our findings can help firms decide how to vary the size and composition of the offer set during the course of a customer's engagement period with the firm. The benefits of the proposed approach are illustrated for different patterns of engagement, including the length of the engagement period, uncertainty in the length of the period, and the frequency of the customer's visits to the firm. We also study the scenario where the firm optimizes the size of the offer set during the planning horizon. One of the most important insights of this study is that frequent visits to the firm's website are extremely important for an e-tailing firm even though the customer may not always buy products during these visits.