Customer Retention under Imperfect Information

I study why many firms face low retention rates among new customers. In particular, I examine whether customer churn at the firm level after a single product experience is solely driven by heterogeneous preferences or is affected by incomplete information about the products. I use a long panel of individual-level ticket purchases from a major U.S. symphony center for which 60% of first-time customers do not return after a single visit. The data exhibit patterns consistent with consumer learning and incomplete information about underlying values of concerts at the ticket purchase stage. Descriptive analyses show that imperfect information and learning spillover jointly cause customer attrition. First, many customers attend concerts with a low match value due to their incomplete information. Second, a low match value at the initial visit leads to high attrition rate at the symphony center level, which suggests that the initial visit experience creates strong learning spillovers by affecting a customer's expectations about all future concerts. To explore marketing strategies to reduce customer attrition, I develop a structural model that incorporates the learning spillovers and incomplete information. Through counterfactual analyses, I analyze both a policy that offers high-value concerts to first-time customers and a policy that offers targeted marketing to second-time customers after their initial visit. The results emphasize the importance of introductory marketing to new customers.