Case Study: Leading Fresh Food Grocer reduces perishable waste and improves fresh-category forecast accuracy by 7% with Kinaxis (Rubikloud AI Demand Forecasting)

Leading Fresh Food Grocer - Customer Case Study

Rubikloud, a Kinaxis company, applied AI demand forecasting to help a grocery customer struggling with perishable shrink caused by promotion-driven cannibalization. The customer was seeing heavy losses—often 25–30%—in fresh salads and packaged meats due to overstocking when highly cannibalistic brands ran promotions.

Rubikloud’s Price & Promotion Manager models cross-product effects and time‑sensitive promotions at the SKU‑store level to prevent over-forecasting and reduce waste. The solution improved forecast accuracy (+7% in a key fresh category), cut perishable loss, and delivered an estimated $39M benefit based on a +1.2% full-chain accuracy gain.