Returning products has become standard practice for consumers, and a significant "pain point" for retailers. The authors contend that returns can be harnessed to increase profits. This requires retailers to manage the interweaving dynamics of product returns and purchase. The strategy is to co-manage a virtuous cycle whereby current returns increase future purchases, and a vicious cycle whereby current returns increase future returns. Marketing executes the strategy. It generates purchases. The returns that follow impose a direct cost due to the vicious cycle. However, the virtuous cycle of returns can offset this, enabling the retailer to “free-ride” returns by optimizing its marketing. The approach follows the Decision Support System (DSS) paradigm by combining a conceptual model, a statistical model, data, and optimization. A core construct is a stock variable tracking consumers’ memory of return experiences. This drives both the virtuous and vicious cycles. The authors optimize marketing spend accounting for Return Stock. The best results are when dynamics are included in both the statistical and optimization models. Results suggests managers should avoid strict return policies aimed at eliminating returns. Instead, they should design policies that optimally balance the long-term benefits and costs of returns
Free-Riding Product Returns to Drive Profits
Valentini, Sara
2025
Abstract
Returning products has become standard practice for consumers, and a significant "pain point" for retailers. The authors contend that returns can be harnessed to increase profits. This requires retailers to manage the interweaving dynamics of product returns and purchase. The strategy is to co-manage a virtuous cycle whereby current returns increase future purchases, and a vicious cycle whereby current returns increase future returns. Marketing executes the strategy. It generates purchases. The returns that follow impose a direct cost due to the vicious cycle. However, the virtuous cycle of returns can offset this, enabling the retailer to “free-ride” returns by optimizing its marketing. The approach follows the Decision Support System (DSS) paradigm by combining a conceptual model, a statistical model, data, and optimization. A core construct is a stock variable tracking consumers’ memory of return experiences. This drives both the virtuous and vicious cycles. The authors optimize marketing spend accounting for Return Stock. The best results are when dynamics are included in both the statistical and optimization models. Results suggests managers should avoid strict return policies aimed at eliminating returns. Instead, they should design policies that optimally balance the long-term benefits and costs of returnsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


