Earlier this week, IBM launched IBM Watson Trend, the latest deployment of the supercomputer’s technology.

The service harnesses Watson’s deep learning abilities to identify and report the most desirable retail products, based on the voluminous data stream from social media services, product reviews, and blog posts. When located, Watson will run sentiment analysis to determine how people really feel about their new smartphones, cameras, TVs, headphones, Lego sets, tablets, and more to identify what the most popular and most recommended products are, just in time for the holiday season.

IBM is really excited about this technology. Currently, the application, available on the website and also on iOS devices, supports the top 100 products across three categories: technology and consumer electronics, toys, and health and fitness.

Each product receives a trend score at the end of each day. Here’s how it works, according to IBM:

“The Trend Score is a number between 0 and 100 that indicates the strength of a trend and takes into account a variety of factors from tens of millions of online conversations. Perhaps similar to your high school teacher, Watson grades on a curve so the top trend each day receives a Trend Score of 100 and all other trends receive a score relative to the top trend. For each trend, the app displays the past three months of the daily Trend Score and forecasts the Trend Score for the next three weeks.”

The company released the product on Wednesday, also releasing a YouTube video that has garnered slightly more than 8,000 views.

The application is currently projecting the Apple Watch, a variety of big-screen TVs, top of the line digital cameras, Star Wars Lego sets, PlayStation 4’s, and anything having to do with Minecraft, Call of Duty, or Skylanders as popular this holiday season.