Shopper segmentation and store clustering
A $34 billion grocery retailer with 7 different banner brands needed a better way to segment their shoppers into meaningful behavioral and purchasing segments.
A ‘one size fits all’ approach created misaligned shopping experience, higher shrink and out-of-stock conditions, and overall volume and market share declines. Although the retailer had core shopper data and research, they lacked a sound analytical approach to define actionable segments and store clusters.
The retailer also needed to develop store clusters to better operationalize merchandising decisions to drive improved sales and margin performance.
Developed an analytical framework to combine consumer research, shopper loyalty data, purchasing trends, and need / wants into cohesive segmentation model for the retailer’s nationwide banners and stores.
Executed a detailed statistical analysis of the segments data to develop clear store clusters focused on product preferences and ‘real world’ consumer purchasing behaviors - without creating unnecessary in-store operating complexity.
Collaborated with Merchandising and Marketing teams to implement the segments and clusters in their key workflows, created enterprise-wide training and communication materials, and guided suppliers in support of the new product alignment strategy.
Improved sales within ‘cluster aligned’ categories from 1.2% to over 8% with no material increase in shrink.
Reduced fresh shrink by 75 to 230 basis points (depending on the category).
Improved cluster-specific shelf space and product allocations to drive a better return on $1.1 billion store remodel investments.