Demand forecasting: Using machine learning to predict retail sales

#artificialintelligence 

Too many items and too few items are both scenarios that are bad for business. Massive incremental profit can be unlocked by retailers managing orders and inventory effectively. But as this requires the processing of data for a huge number of stock keeping units (SKUs), which often include perishable goods and items that are ordered daily, it is also a significant challenge. Retailers used to rely solely on the data from previous years to predict future sales (and therefore manage their inventory), but this method is only useful up to a point. However, machine learning has now evolved to the stage that it can provide accurate predictive models using different signals based on how they influence purchases.

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