Implementing Retail Category Management: a Model-Based Approach to Setting Optimal Markups

Abstract

This study proposes a model-based approach for implementing retail category management (CM) with a focus on markup decisions. We construct a Bayesian econometric model that offers a comprehensive portrait of own-and cross-price effects on sales of individual brands in a category, as well as price reactions driven by their manufacturers' price setting behavior. We then derive optimal retail markups of individual brands within a product category by maximizing a retailer's total category profit over a finite time horizon and illustrate the application of the approach using store-level weekly sales data of toothbrushes. Our empirical results indicate that markups on large-share brands should have been higher than in the current practice. In addition, retailers can achieve higher cat-egory profits without increases in their overall category sales, but rather by driving reductions in the wholesale prices. We discuss the managerial implications of our approach for retailers and other channel partners.