Perceived Risk, Product Returns, and Optimal Resource Allocation: Evidence from a Field Experiment

Abstract

Relatively few retailers include metrics such as product returns in their customer selection and optimal resource allocation algorithms when measuring and maximizing customer value. Even when they do include this metric, increases in product return behavior are usually considered merely an economic cost that must be managed by decreasing the marketing resource allocations toward the customers making the returns. However, recent research has suggested that satisfactory product return experiences can actually benefit firms by lowering the customer's perceived risk of current and future purchases. To better understand the role of this perceived risk in the firm–customer exchange process, the authors conduct a large-scale customer selection and optimal resource allocation field experiment with 26,000 customers from an online retailer over six months. They find that the firm is able to increase both its short-and long-term profits when accounting for the perceived risk related to product returns in addition to managing product return costs. Furthermore, the authors find that by including this risk, rather than simply implementing traditional customer lifetime value–based models generically, the firm can target more profitable customers.