Online prediction. This is when your ML system is used to serve real-time predictions, based on online requests from the operational systems and apps. In contrast to offline prediction, in online recommendations you need the current context of the customer who's using your application, along with historical information, to make the prediction. This context includes information such as date time, page views, funnels, items viewed, items in the basket, items removed from the basket, customer device, and device location.