Product Returns, Customer Segmentation, and Dynamic Pricing in the Online Retail Market

Abstract

Online retailers can adopt generous return policies to entice customers to buy and try new products. In this article, we focus on the learning aspect of product returns and show how an online retailer can utilize returns to segment customers based on their individual valuations of a product. We derive the optimal dynamic pricing strategy, including a potential fee for product returns (restocking fee), which balances the benefits from effective customer segmentation and the costs associated with product returns. Strategic customers, who understand that their return decisions affect future prices, may choose to return the product even when their valuations exceed the initial price. To curb strategic returns, which compromise the effective segmentation of customers, it is optimal for the retailer to reduce the initial price of the product and charge a higher fee for returns. We also identify conditions so that it is optimal for a retailer to overcharge customers for product returns (i.e., the return fee exceeds the actual cost of a return). This allows the retailer to extract surplus from customers who have low product valuations and return the product, and is therefore a form of price discrimination.