May 10, 2016 | Written by: Greg Girard
Categorized: eCommerce & Merchandising
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I admit it: I’ve whiled away many a beautiful early April New England weekend watching the Masters. Some moments never fade from memory, like Jack’s come-from-behind 1986 victory with son Jackie carrying the bag, Tiger’s slow-motion chip-in on 16 from behind the green on a Sunday afternoon, and Faldo’s win over a collapsing Norman. The golf tournament’s TV ads are not generally memorable, nothing like the annual round of newsworthy Super Bowl ads, but one ad during this year’s Masters jumped out at me. Full disclosure: I am a retail industry analyst focused on advanced analytics, cognitive computing included. From that angle the IBM ad featuring Todd Spaletto, President of The North Face, caught my fancy. Ok, I’m also a huge Bob Dylan fan, and the ad featuring him remains my all-time favorite IBM Watson ad.
Mr. Spaletto described how his company is using IBM Watson on its website to help shoppers select apparel that best suits their needs. I’ve tried it. You just enter a natural language statement and/or question. “I’m going hiking in the mountains outside Flagstaff, Arizona, next fall. What kind of jacket should I buy?” You could type that or use a voice-to-text service just as well. The Watson-powered e-Commerce site returns a curated list of jackets with comments explaining how each one was selected (in this case, the list was based on typical fall weather patterns in those mountains and the needs of a hiker). That hints at next-generation human machine interfaces. Meanwhile, The North Face reports that this gambit is already delighting customers and selling merchandise. It’s bringing store associate-like guidance to the online world at scale.
I’m looking forward to Amplify 2016, in particular the privilege of introducing a session titled Unleashing the Collaborative Power of IBM Shopper Insights for Retailers and Vendors, led by Irwin Chiu and Sungjai Lee. Shopper Insights is engineered to use advanced analytics to reveal behaviors of shoppers in key segments and to detect the roles and effects of purchased items in building each shopper’s transaction basket. Shopper Insights takes it a little further to model shopper responses to various promotions, price changes, what new products to introduce, and other events.
I’m also interested in seeing IBM’s progress on the journey to cognitive commerce on the B2B side of the house. Cognitive capabilities, basically machines that understand, reason, and learn in a human-like fashion, can augment the performance of existing commerce technologies and systems or enable new technologies and systems to automate today’s manual decisions, actions, and processes (see IDC Analyst Connection paper, sponsored by IBM). For example, ingesting torrents of economic news and social media streams and understanding the implications of social, commercial, weather, and political events on customers’ sales and investment plans can reduce errors in demand and sales forecasting. That’s an excellent example of how cognitive computing could augment an existing B2B commerce process.
How’s that possible? Well, a very good definition of cognitive software suggests how: Cognitive software supports human decision-making with more accuracy, confidence, speed, and agility based on broader and deeper bodies of evidence applied to a more comprehensive view of pertinent conditions without bias.
That vision remains aspirational. How long? I’d wager it won’t be as long as we had to wait between Jack’s final two victories at the Masters. How long is that? For that answer, you’ll have to use Google.