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Otto reduces the rate of product returns by predicting sales for the next three months with 90% accuracy using machine learning to understand consumer preferences
janhavi
Jan. 31, 2019
Summary:
Otto, the German e-commerce giant, saved millions of Euros by accurately predicting customer demand and using it to plan inventory. They were looking to reduce losses caused by product returns and found that customers prefer to receive all the items in one shipping, within two days. The only way they could do this was by predicting which items would be sold next month accurately. Otto's solution has been able to predict demand with 90% accuracy.
Problem:
Otto was losing millions of Euros every year in shipping costs due to customers returning products frequently.