A Model-Based Approach to Setting Optimal Retail Markups

summary This study provides a model-based approach for implementing retail category management with a focus on markup decisions. We develop a reduced form Bayesian econometric model that captures price and sales variation for a retail chain. Based on this model, we derive the optimal retail markups on individual brands within a product category by maximizing the total category profit over a finite time horizon in a Bayesian framework. We demonstrate our approach using store-level weekly sales data from a retail chain. Our empirical findings indicate that, contrary to common practice in the retail industry, markups on high share brands could well be greater. We also find that category profit can be increased by driving down wholesale prices via competitive force, without an increase in overall category demand. We discuss the implications of our approach for retailers and other channel partners. .