By studying consumers’ transaction patterns and tailoring return policies accordingly, companies can prevent a major drain on profits while increasing engagement with loyal customers.
For a century, L.L. Bean had an extremely liberal product-return policy, with no time limit and no receipt requirement. You could get a full refund for boots purchased decades ago. But many people abused the policy, returning products fished from dumpsters or bought used on eBay. Over the past five years, worthless returns cost L.L. Bean $50 million per year. That amounts to roughly 30% of the company’s annual profits.1
So in February 2018, the company established a new policy that limits all product returns to one year from the date of purchase. The change led to bad publicity, a class-action lawsuit, and vows from once-loyal customers to stop shopping at L.L. Bean because they felt unfairly penalized for the actions of others. Some of those customers say L.L. Bean is no longer special and has become just another store.2
L.L. Bean is not alone. Best Buy, REI, Lands’ End, and Costco have instituted return restrictions such as restocking fees, shorter time limits, and requirements for the original receipt.3 Some retailers still have more liberal policies, but they are becoming rare.4
Regardless of how generous or restrictive companies are when it comes to returns, they tend to apply a one-size-fits-all approach to their entire customer base. They ignore wide variations in individuals’ behaviors, lumping loyal, compliant customers in with those who game the system.
Yet new tools and technologies make it possible to segment customers and impose strict return policies only on those whose past behavior warrants it. We recently analyzed customer data for a large, high-end U.S. retailer and identified transactional patterns that indicate which people are most likely to abuse return policies. Though highly accurate for the company we studied, our predictive model is unique to that retailer; in another setting, other factors might be identified — or the same ones might be weighted differently. Still, the overall approach to identifying and managing the people most likely to abuse return policies is broadly instructive, so we are sharing it here to help retailers manage returns profitably while delivering a positive customer experience.
Finding the Most- and Least-Profitable Customers
Returns are big business. In 2017, consumers returned $351 billion worth of purchased products. (Our analysis shows that if the hypothetical Consumer Returns Inc.