Estimating Substitution and Basket Effects in Retail Stores: Implications for Assortment Planning

Abstract

Many retailers are reducing store footprint and downsizing their assortments accordingly to improve store productivity. Some of the revenue for items removed from the assortment may be recouped by substitution, but also some of the revenue for items kept in the assortment may be lost due to basket abandonment. For a practical setting where baskets may contain any subset of items from thousands of products, estimating both substitution and basket effects is a challenge. To address this, we develop a demand model that combines a multinomial logit (MNL) model to estimate substitution within a subcategory and a purchase-incidence model to estimate basket retention. Using transaction and product availability data from 12 stores of an office supplies retail chain that were dramatically downsized from large- to small-format stores, we show that (i) storewide basket effects are substantial (our model with basket effects predicts out-of-sample transactions with mean absolute percent error (MAPE) of only 7% compared with 22% for a model with only substitution effects), (ii) poor service level can significantly exacerbate lost profit due to abandoned baskets at these stores, and (iii) consideration of the basket effect in assortment selection for the small stores can significantly improve basket retention and increase profits (by up to 16%) at these stores. This paper was accepted by Vishal Gaur, operations management.