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

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 needs to be managed by decreasing the marketing resource allocations toward the customers making the returns. However, recent research suggests 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, we conducted a large-scale customer selection and optimal resource allocation field experiment with 26,000 customers over 6 months from an online retailer. We found that the firm is able to increase both its shortand long-term profits when accounting for the perceived risk related to product returns, in addition to managing product return costs. Further, we found that by including this risk, rather than simply implementing traditional CLV-based models generically, the firm can target more profitable customers.