By tracking the individual behavior of each shopper, identify the customer keys of entry & sequences of choices in the category. Based on this, build the customer decision tree, down to the consumer need unit level (group of products addressing the same consumer need)
Based on an in-depth understanding of the customer decision tree and the cross-purchasing level between groups of products, define the optimal merchandising sequence of a category, i.e the order in which sub-categories / product families must be presented to the client
Based on a multi-criteria analysis (client profiles, sales profiles, seasonality…), identify the right short list of stores to run a test , as well as the control stores, against which the performance of the test must be measured. Run the test performance analysis and draw the right conclusions along a comprehensive set of KPIs (total sales, penetration, focus on specific client groups…)
Run a thorough analysis of a network of stores along a wide set of criteria (sales structure profile, shopper profile, price sensitivity, promotional sensitivity, seasonality…), measure variabilities and extract one or several angles of store clustering. Adapt category strategies (on assortment, promotions, pricing..) to each cluster.
For each store, analyze the sales and profit performance of each linear meter / square meter, liaise it with the client performance and define a space reallocation plan that optimize sales and/or profit, while respecting several operational constraints and/or commercial principles.