Clustering Stores of Retailers via Consumer Behavior
These days most retailers define clusters of stores and set different prices in the clusters, since it is not yet attractive to define store-by-store prices due to optimization and operational issues. However, retailers define clusters of stores solely based on local competition. Existing clusters of stores could be further broken down and price management decisions could be adjusted accordingly by using consumer behavior. Therefore, the price elasticity is used which is a reflection of consumer behavior. In this way the retailer enables itself to set different prices in smaller clusters of stores in order to attain higher revenue and profit. This research provides a clustering solution that defines clusters of stores based on price elasticities. This clustering solution proves potential with a projected increase in revenue of 0.36% and a projected increase in profit of 0.76% by using data of one of the major supermarket chains in the Netherlands.