The distribution of retail gross margin: analysis and implications

Abstract

ABSTRACT Prior research on retail sales distributions finds both product concentration and long tails. However, gross margin dollars (rather than sales dollars) are critical drivers of retail financial performance, especially in sectors characterized by short product cycles and declining average selling prices. The paper is the first to use sku level data to estimate both sales and margin distributions for an office supply/technology retailer. We calculate Lorenz curves, Gini coefficients, and Pareto curves for in-store, on-line, and omni-channels. The estimated distribution of gross margin dollars is less skewed than the sales distribution; that is, more of the margin dollars are in the middle of the distribution. Significant differences in sales and margin distributions are found in store, online, and omnichannel products. These differences are only partially explained by price architecture and by private label merchandise. We analyze the decile distributions of sales and margin across channels and develop a classification matrix with implications for merchandise planning. Because merchandise strategies often focus on best sellers and managing long tails, the paper highlights opportunities for increasing profitability by emphasizing the middle of the margin distribution.