tampatra @ stock.adobe.com
A machine-learning software that ships items to the geographical area near the final destination, predicting when an end-user will be placing an order. Products are normally stored closer to potential customers for faster shipping, or the final destination can be defined en-route, eliminating the need for secondary storage.
A forecasting model, real-time smart home data, and public data sources, such as product trends on social media or news stories, predict where an item would need to be shipped based on previous purchasing activity. Identifying both the quantitative rise in interest in a topic and the context of that interest enables the system to make predictions about which fads could boom.