Having racked up a victory in the game-show arena, Watson is moving on. It has already been applied to clinical decision support for healthcare, with a focus on treating lung cancer. Now, it's venturing into the world of retail. Introduced in November of 2015, the Watson Trend App is turning its computing power to the identification of buying trends in three key areas of retail: consumer electronics, toys, and health and fitness. With its ability to understand natural language, the app monitors the sentiments of tens of millions of online conversations, drawing on some 10,000 sources across popular social media sites. And it goes beyond merely identifying sales trends to reveal why and how consumers are buying. (It has already predicted the initial success of the Apple Watch, Star Wars-themed Lego sets and a high-tech version of Barbie.) On this episode, we speak with Watson Trend App product strategist Justin Norwood, who explains how it works today, and how it might be deployed in future to create personal interactions between consumers and their favorite brands. We also learn how the app could help retailers and consumer-goods manufacturers to devise more accurate demand forecasts. Hosted by Bob Bowman, Managing Editor of SupplyChainBrain.

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Show notes:

An IBM whitepaper on “Demand Signal Repository for Consumer Products.”

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