Assortment Optimization Use Case

Catalyst doesn't hand the planner another top-down forecast. It lets buyers work at the SKU-Store/Channel level, determining optimal purchase quantities and prices needed to satisfy True Demand before the season begins. The Recommendation First System compares planned assortment against demand and surfaces the divergences that matter, with marketing inputs folded in before the commitment is made. A conversational interface lets the planner run quantified what-ifs — shift units from group A to B, flex price on this SKU — and see the revenue impact. A Semantic Knowledge Graph ties structured sales data to unstructured context, and continuous learning sharpens next season's recommendations. The buy goes out at SKU-Store precision, not store-group averages.