The buzz around consumer-grade artificial intelligence continues to grow. The latest example is IBM Watson Trend, a new way for consumers to understand the top shopping trends of the holiday season. Using a mix of machine learning, sentiment analysis, keyword analytics and natural language analysis, IBM Watson Trend tracks the top 100 selling items across three popular categories: consumer electronics, toys and health & fitness.
On the surface, most of what IBM Watson Trend is reporting as a “trend” is relatively obvious and probably doesn’t require a supercomputer. For example, the top three products in the consumer electronics category so far are the Apple Watch, Samsung TVs and Sony TVs. (The Samsung Gear VR, alas, didn’t even show up in the top 10, despite selling out on Amazon and Best Buy.) In the “toys” category, where the three leading trends are Star Wars LEGOs, LEGO Friends, and LEGO City, there’s also not much new.
This leads to the inevitable question: How do the shopping insights from IBM Watson differ from what’s already available on the market? By now, you’ve probably read more than a few articles about what products are set to fly off the shelves starting this Black Friday. And, yes, many of them inevitably mention the Apple Watch or “Star Wars.” So what’s the big deal about using AI to predict shopping trends?
Date: November 24, 2015
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