Fundamental Basket Size Patterns and Their Relation to Retailer Performance

Abstract

This paper uses a sample of approximately 60,000 US households to document fundamental basket size patterns across a range of retailer types (e.g. grocery stores, convenience stores, and warehouse clubs), and studies them in relation to retailer performance metrics (unit sales and dollar revenue). This research examines 1) how patterns in basket size (distribution, means, and medians) differ by retailer type, and 2) how the Pareto principle extends to shopping baskets across different retail types. The results show that basket size patterns in retailers are predictable. Shoppers purchase more items on average in retailers that offer a greater variety of items, and the distribution of basket sizes follows the Poisson lognormal model. The results also show that the largest 20% of shopping baskets on average generate 50% of unit sales, and 40% of dollar revenue. These patterns provide marketing academics with more knowledge about how people behave when they go shopping, and set additional benchmarks of what patterns can be expected on a basket-level. This research also offers support to marketing practitioners by showing the importance of different shopping basket characteristics (e.g. frequency of light buyers), which can guide more informed decision making to better manage their brands