This retail machine learning use case can use purchase data to predict inventory needs in real-time. These algorithms can provide a daily dashboard of suggested orders to a purchasing manager based on the day of the week, the season, nearby events, social media data, and past customer behavior. In scenarios where the e-commerce platform does not manage inventories directly, we have built similar solutions to predict if an item a user is purchasing may be out of stock. As shown in this machine learning use case in retail, a predictive model leverages historical data such as past stockout events, demand, price, and stock level for each product. Go ahead and start using EdrawMax to create beautiful use case diagrams for your organization.
