Assortment Optimization & Attribute Modeling

The world's largest beer company's category management and retail team had no data-driven approach to optimize their assortment mix or identify which product attributes drove incrementality. Understanding of which product attributes drove volume, revenue, and profit was limited, and there was no ability to predict the potential performance of future products before launch.

Cloverpop developed a multi-attribute model quantifying the incremental contribution of product attributes across the Beer category. A simulator tool was built to assess the potential performance of future products based on attributes, and a data-driven assortment strategy was created combining assortment, space allocation, and item selection.

Results

• 3.5% sales uplift

• 4% margin impact

• 3 national retail banners optimized

Assortment decisions became data-driven, with clear visibility into which attributes drove volume, revenue, and profit across 3 national retail banners. Attribute-based assortment optimization delivered 3.5% sales uplift and 4% margin impact, with a simulator tool enabling future product performance prediction before launch.