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Lenta automates demand forecasting with DSLab AI technology
In a fiercely competitive battlefield of grocery retail, getting demand forecasting right is more important than ever. Order too much, and you accumulate overstock; order too little, and you lose sales and customers. Artificial intelligence, however, gives a fresh perspective on how to strike a balance and predict demand as accurate as possible.
Lenta is one of the largest retail chains in Russia and the country's second largest hypermarket chain with 14.4 million active loyal customers. To improve its demand prediction process, Lenta collaborated with DSLab. In a matter of months, DSLab delivered a solution: an AI-based predictive model that accounts for more than 600 parameters and forecasts demand for each stock keeping unit (SKU), including those on sales promotion, on a store level.
The result? +13% growth rate in prediction accuracy compared to the existing solution, fully automated demand forecasting system, and maintaining high levels of on-shelf availability and turnover. To learn more about AI-based demand prediction, our approach and how this can benefit your business, download the case study below.
Discover how Lenta automates demand prediction with DSLab AI technology