Wednesday, January 27, 2016

Retail's Cognitive Recap - NRF 2016

Cognitive computing made its grand entrance at NRF?s BIG show 2016. Between the rise of machine learning and IBM Watson opening up its services in the cloud, some interesting companies have emerged. At NRF, retail got its first taste of the best cognitive technologies on the market. Here are some highlights.

Take a step back. What exactly is cognitive?

Cognitive computing is a new class of machines that learn like we do???by reading stuff and asking questions, continuously improving from feedback. So what does this mean for commerce? Think of it as Spotify for Shopping.

I?m a big Spotify fan and I listen to music constantly. What I love about Spotify is that it subtly learns my preferences in the background, listens to my feedback, and then tunes radio stations accordingly and provides me with a weekly playlist of personalized song recommendations. So why can?t we have that same experience with online shopping?

Why is it that a retailer website or mobile app can?t understand my preferences as I shop, and, when I?m filtering through 3,000 women?s tops at a department store, pull out the ones that I would actually like? Part of the answer lies in the data. A lot of information about your preferences is visual, locked inside the images. How do you respond to a certain look? The color, cut, fit, details, print, length, risqueness, or conservativeness. Other nuggets of wisdom are locked in the user reviews. If a woman complains about the color or quality of the dress, or if she raves about how great it looks, that is going to influence my decision to buy that same dress.

We call this information unstructured data. Your machine can?t speak English. It can?t read through user reviews and provide you with the CliffsNotes. It can?t extract multi structured or dark data. And it certainly can?t weave all that information together in the context of a customer, and pull from the catalog a curated set of products specific to her tastes.

So how do you solve for this complexity? You need cognitive technology. Cognitive emerged as a major theme of NRF, but with so many companies dropping buzz words???like AI, cognitive, machine learning, insights???how do you sift through the noise? The trick is that a lot of individual services can be built on top of Watson or using other machine learning algorithms and NLP capabilities, but they tend to have a very specific focus. I?m going to solve for natural language search, or I?m going to solve for better recommendations by building on top of my existing collaborative filtering model. And then you?re left with a slightly better search and recommendation engine, but they don?t talk to each other. And you have to work with multiple vendors to enable all the individual features and keep them updated.

The best solutions can provide a holistic view of your shopper, not just enable enhanced individual features. What retailers really need is a digital brain behind their enterprise architecture and all digital platforms. When we?re talking about millions of users as your customer base, and a constant stream of new products arriving to your store and website, how do you keep up without constantly having to reprogram your search and recommendation engines, and keep your site relevant? The answer lies in leveraging a system that is capable of updating itself.

Following NRF 2016, we expect to see a massive uptake in cognitive technology in commerce, as retailers incorporate personalization 2.0 into their long-term strategy and pave the way for tomorrow?s digital shopping assistant.

Want to learn more about our CognitiveCommerce(?) suite? CognitiveCommerce plugs a digital brain behind a retailer?s mobile app or commerce site and delivers shopping advice and various micro-experiences powered by a unique shopper profile. Email Sales@CognitiveScale.com to request a demo.

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