IBM CEO Ginni Rometty took the Watson story on the road yesterday when she addressed a crowd of 35.000 at the National Retail Federation's 103rd Annual Convention and EXPO in New York City. Like almost every tech CEO who has stood on a stage in the past thirty-six months, she opened with the “social, mobile, big data, cloud” mantra, calling data the “next generation's natural resource."
But as she spoke, it became clear that Rometty had something to offer that other CEO’s did not, IBM Watson, the technology that beat Ken Jennings at Jeopardy. Until recently many of us have thought of Watson as an Encyclopedia and Search Engine on steroids, but it’s actually much more than that.
What a Wonder
Constellation Research’s founder R "Ray" Wang pegs IBM’s wonder child as “a culmination of artificial intelligence, natural language processing, dynamic learning, and hypothesis generation to take vast quantities of data to make better decisions. “ We’d add collaborator to his definition.
We say this because Rometty described Watson’s abilities to act as an online shopping concierge during her talk, meaning that it could actually hold a conversation much the way a personal shopper can. Take, for example, an individual who plans to go camping in Patagonia and logs on to North Face to gear-up.
The “conversation” wouldn’t be that different from what happens in a physical store, the concierge might ask the shopper a little bit about her/himself and what he/she might looking for. Watson would then show him/her some things he/she might enjoy or need. In the case of someone who is about to go winter camping, Watson could suggest a sleeping bag for frigid weather. The shopper would be able to tell Watson things like “I think I’d be too warm in that” and then a new suggestion would be made.
It sure beats shopping on most of today’s retail sites that aren’t much more than on-line catalogs from which you can electronically order.
It’s important to note that Watson doesn’t come “out of the box” knowing how to do this. North Face’s Watson is being trained and implemented by Fluid, a company whose products and services promises to turn shoppers into customers.
Last week, during Watson’s unveiling, Fluid’s CEO Kent Deverell presented a real life example of how today’s online shopping experience doesn’t come close to what you get in a store. He was trying to help his son purchase some equipment on line, they read and read product descriptions, they comparison shopped to find a great price, and, after hours of exploration, they walked away from their computers without buying a thing. Instead they jumped in the car and went to REI.
Why? Because they had questions and the only experts they had to consult with were themselves. (Yelp isn’t interactive). There were no possibilities for warm fuzzies or even a confirmation that they were making a choice with which they’d be satisfied.
Watson is Not Siri for Business
Though we haven’t heard anyone from IBM shout from the roof tops “Watson is not Siri for Business,” trust us, Watson is not Siri for business.
Siri can’t make recommendations on which medical devices should be purchased based on the outcomes and value they provide. Siri is unlikely to be able to provide answers based on an individual’s situation, preferences, abilities and so on. Given some time and training, Watson can do all this and more.
Answers a Search Engine Can’t
It’s ironic, but Travelocity founder, Terry Jones, uses travel agents when he plans his own vacations. He says that he has found that conversations with experts are needed because they can introduce him to experiences that today’s travel sites can’t. Take a recent trip that Jones took to France as an example. Jones’ travel agent knew that he was a cooking enthusiast, and as a result, was able to hook him up with an opportunity to work side-by-side with a one-star Michelin chef. A travel site wouldn’t have known to put that kind of offer in front of him.
Watson, with some training and some data would.
And if Jones was no longer interested in cooking and now liked cycling, his travel agent might have introduced him to a trip that follows the route of the Tour de France. Watson with some time, data, and training should be able to do so as well.
IBM's Biggest Watson Challenge?
To let its spawn into the wild solo. IBM is wise to form a new division around Watson, to fund it with 1 billion dollars and to give developers the space and incubation they need to build apps and solutions around it. There is not a better place in the world to do this than New York City’s hip Silicon Alley- home of ZocDoc, Tumblr, Etsy, FourSquare …
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