Case Study: Grocery Store achieves up to 30% higher incremental sales with Kinaxis (Rubikloud)

Grocery Store - Customer Case Study

Rubikloud (a Kinaxis company) worked with a grocery retailer to tackle the combinatorial challenge of weekly promotion planning: deciding the best products, weeks, mechanics and placements while measuring cross-category effects, ROI and inventory needs across millions of forecast possibilities and many business constraints. The goal was to move from manual, time-consuming planning to data-driven, strategic promotion decisions that drive measurable financial impact.

By ingesting internal and external data and applying AI demand forecasting plus constraint-based optimization, Rubikloud generated optimized promotion calendars and candidate plans. The automated solution increased revenue 3–5%, raised incremental sales for selected items by 30%, cut planning time by 50%, reduced excess inventory/stockout costs by 30%, rationalized SKUs by 14% and delivered 45% higher incremental dollars per item.