The return of a product is often one of a series of transactions that a consumer undertakes in search of a good. Recognizing this, we analyze returns as part of a product search process: on returning a product, consumers may immediately purchase an alternative one, which they may later replace with another product, and so on, until they either ultimately keep their last purchase (Keep outcome) or not (No-keep outcome). We call such a sequence of transactions a product return episode. In this work, we study consumer Keep and return abuse behavior using episodic metrics. Using data from a consumer electronics retailer, we show that analysis of product returns with episodic metrics provides insights that differ from, and go beyond, analyses with commonly used transactional metrics. We find that although higher average price and larger store assortment at a subcategory level both tend to increase the return probability, they also increase the probability of keeping a product at the end of an episode, which points to profit-improving opportunities for retailers by allowing returns and tracking episodes. We also find that episodic metrics are useful for identifying return abuse.
All Science Journal Classification (ASJC) codes
- Business and International Management
- Modeling and Simulation
- Management Science and Operations Research