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Retail & Consumer Goods
Local assortment personalization & dynamic pricing
Client · Food retailer · 1,200 stores
A personalization platform combining loyalty data, local competition and category dynamics — adding 1.8 points of gross margin on pilot categories.
01
Challenge
- National-level assortment, poorly adapted to local socio-demographic specificities.
- Uniform pricing strategy generating margin loss on low-competition zones and share loss on competitive ones.
- Underused customer data (loyalty, basket) siloed between marketing, category management and operations.
- No unified tool for category managers — work was done in Excel.
02
Solution
- Customer Data Platform unifying loyalty, basket, web/app navigation and geomarketing data.
- Store × category clustering identifying 14 catchment-area archetypes.
- Bayesian price-elasticity engine recommending prices by SKU × store under margin and price-image constraints.
- Self-service app for category managers — simulation, validation and deployment to checkout system.
03
Business impact
- +1.8 pt gross margin on pilot categories (grocery, fresh, beverages).
- +4.2% revenue on stores adopting personalized assortment.
- −30% time spent by category managers on repetitive tasks.
- National rollout in 18 months; 200+ business users on the platform.
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