Otto was losing millions of Euros every year in shipping costs due to customers returning products frequently.
"Otto discovered that the rates of return is higher for products for which the shipping time is more than two days and when there are multiple shipments. Applying Blue Yonder''s deep-learning algorithm, around 3bn past transactions and 200 variables (such as past sales, searches on Otto’s site and weather information) were analysed to predict what customers will buy a week before they order. The AI system predicts with 90% accuracy what will be sold within 30 days—that Otto allows it automatically to purchase around 200,000 items in a variety of products, colors and sizes that the machine orders a month from third-party brands with no human intervention. Customers get their items sooner, which improves retention over time, and the technology also benefits the environment, because fewer packages get dispatched to begin with, or sent back."
Blue Yonder''s deep-learning algorithm
"Around 3bn past transactions and 200 variables (such as past sales, searches on Otto’s site and weather information)" "Delivers probabilistic forecasts based on hundreds of different variables including weather, promotions, and holidays. This allows the business strategy to automate millions of daily replenishment decisions across products and stores."
According to the company: * 90% accuracy in predicting products that will be sold within the next 30 days enabling Inventory optimisation * Inventory surplus is reduced by 20% * Number of returns are reduced by more than 2M