Retail demand prediction using machine learning enables businesses to analyse large volumes of data, identify complex demand patterns, and generate accurate forecasts at SKU, store, and channel level. By incorporating factors such as promotions, pricing, seasonality, and external signals, machine learning models continuously improve over time and adapt to changing conditions. This approach supports more precise replenishment planning, reduces stock imbalances, and helps align inventory with real customer demand across increasingly complex retail environments.
