Case Study
A major grocery retailer spanning Asia and the Middle East transformed its demand forecasting capabilities with Impact Analytics ForecastSmart, an AI-native forecasting solution. Facing forecasting inaccuracies across Brick & Mortar, Marketplace (Q-commerce), and Food App channels, and complex categories like Ambient Frozen, Chill, and Café, the retailer needed a smarter, scalable approach.
By implementing ForecastSmart™, the retailer improved forecast accuracy, reduced manual efforts, and optimized replenishment decisions. Automated forecasting considered seasonality, SKU recency, weather patterns, and even ‘break to sell’ logic for hospitality items, ultimately reducing lost sales by nearly 30% and increasing gross margin uplift by up to 3%.
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