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.

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Publication Details

Journal
Journal of Economics & Management Strategy
Published
2025-01-29
DOI
https://doi.org/10.1111/jems.12627
Citations
2
Primary Topic
Consumer Market Behavior and Pricing
Type
article
Field-Weighted Citation Impact
4.15
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article

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

Veikko Thiele, Konstantinos Serfes, Julia Otte
2 citations
Journal of Economics & Management Strategy
Consumer Market Behavior and Pricing
4.15
article

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

Veikko Thiele, Konstantinos Serfes, Julia Otte
article en
2 citations

Abstract

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.

Journal of Economics & Management StrategyVol. 34(4)
Queen's University (CA), Drexel University (US)
Openalex Percentile: Top 8%
Consumer Market Behavior and Pricing
4.15
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Product Returns, Customer Segmentation, and Dynamic Pricing in the Online Retail Market — Veikko Thiele, Konstantinos Serfes, et al. · Journal of Economics & Management Strategy (2025) | TGRS Research Map | TGRS