Optimizing SKU Selection for Promotional Display Space at Grocery Retailers

Abstract

Promotional displays, such as end-of-aisle displays, provide a stimulus for discretionary and incremental sales at grocery stores, offering a powerful yet affordable tool to boost profit. In this study, we examine a store manager's choice of which stock-keeping units (SKUs) from a given category to assign to a promotional display space. While the academic literature and retail software solution providers offer a variety of optimization solutions for the assortment optimization problem, there is very little guidance for retailers on how to optimally determine when and what products to place on their promotional display space. Consequently, retailers often default to simple heuristics, which are typically suboptimal from a profit maximization standpoint, when making this decision. Thus, there is a need for a decision support tool to facilitate the product selection for promotional display space. Using a grocery store sales transaction dataset, we demonstrate how to measure the incremental lift in sales of placing a particular SKU on promotional display space. Our optimization model includes the incremental lifts (from the estimation method) combined with the estimated base-sales rates and profit margins of each SKU so that the profit-maximizing SKU can be chosen for a promotional display space for each week of the year. Placing a SKU on promotional display can result in a significant lift in sales. For example, the estimated average display effect (i.e., sales lift) for the beer category across all SKUs and all weeks is 27\%, which makes promotional display a very effective tool for stimulating incremental product sales. Overall, our methodology results in at least 1.6X improvement in incremental profit when compared to a common industry benchmark. We also test our methodology on two additional product categories and demonstrate that it performs equally well across product categories. Our work provides an easy-to-implement, promotional display SKU-selection methodology that includes both an estimation and an optimization model. Our estimation model can handle an extensive and complex product assortment and accounts for important aspects of promotional activities such as the cannibalization of the inner aisle sales as well as halo effects. Our optimization model is flexible enough to consider practical aspects such as common business rules that restrict the selection of the same SKU over a consecutive set of weeks, display-related changeover costs and slotting fees offered by the manufacturers. Overall, our study underscores the importance of making effective promotional display decisions.