Creating cluster‐specific purchase profiles from point‐of‐sale scanner data and geodemographic clusters: improving category management at a major US grocery chain

Abstract

AbstractIn the retail grocery industry, category management is the process of managing categories of products for greater profitability and customer value. Category management is a data‐driven process and, as a result, can benefit from point‐of‐sale (POS) scanner data. This paper describes the results of a one‐year project that shows how to use POS scanner data and geodemographic clusters to improve the practice of category management at Price Chopper, a large US grocery chain. The paper demonstrates how to merge POS scanner data with geodemographic clusters to create detailed purchase profiles that provide valuable information to category managers. It also discusses the trials and tribulations of using scanner data and provides several findings as implications (eg store‐specific promotions should be more effective than chain‐wide promotions for stores servicing a small number of geodemographic clusters with distinct shopping profiles) that supermarket managers can immediately use to improve existing promotional strategies. The paper's contents should be relevant to academicians and practitioners interested in improving the practice of category management in the UK, USA, Western Europe and Australia. Copyright © 2004 Henry Stewart Publications.