Latest posts by Kalsi (see all)
- Who Else Wants to Know the Mystery Behind Sentiment Analysis? - June 23, 2019
- 5 Real Examples of Artificial Intelligence - October 4, 2018
- Everything you wanted to know about AWS IoT - March 7, 2017
Facebook recently announced a rather scenically named system, Big Sur, designed around Nvidia’s Tesla compute cards aimed at helping their neural networks, and obviously machine learning, become faster and more versatile. They are, of course, not alone. IBM Watson has similar visions as does Microsoft. Big Data and analytics have long staked claim to the holiday shopping season, but I sense that this 2015 holiday shopping season the real big winner will be Machine Learning.
Watson will tell you what’s on with the holiday shopping list
The big gun in the Machine Learning camp is the aforementioned IBM Watson. Sometimes I think that Watson is like that kid in class who was good at sports and played a mean guitar all while acing his class tests – almost insufferably good at everything he does. After winning “Jeopardy” and laying claim to being the best diagnostician in the world Watson is now showing off “IBM Watson Trend”. This tries to answer that greatest of all holiday shopping questions, “What should I buy her (or him) for Christmas?”. IBM Watson Trend trawled through millions of online conversations as well as more structured data from over 10,000 sources to come up with the top 100 things people want to buy in categories like Consumer Electronics, Toys and Health & Fitness.
This is, of course, not voodoo but a sophisticated mix of social listening, sentiment analysis, keyword and natural language analytics and perhaps just that little bit of voodoo. The trends themselves are not startling – you knew that Apple Watches, Samsung TVs, and Sony TVs would be top of the list. What is truly path breaking is the insight available to marketers and organizations. A great example is what IBM published as a “story behind the trend” of how Nikon cameras made it to a recent Top 10 list. Watson was able to show that the buyers were people who owned smartphone cameras and were looking to up their photography cred by upgrading. The online chatter that led Watson to this conclusion is an amazing data point for those looking to craft a compelling message or offer for Nikon cameras.
Amazon, as always, will be amazing
With so much of today’s holiday shopping happening online, 40% of all sales according to Ipsos, it’s not surprising that Machine Learning is making an impact here. Online eCommerce retailers pursue one goal above most others – a personalized customer experience. The truth is that most sites carry the same products and a steeper discount is just a click away. eCommerce retailers believe that a personalized site experience with specific recommendations, social connects and relevant reviews tailored to the preferences of each individual shopper are key to increasing stickiness and ultimately sales.
You almost expect that for anything to do with online retail Amazon would be the driving force – and you would be right in this case. Amazon is leveraging machine learning to make the experience much more personal towards this goal. It seems they pull in data from the social profiles of the shoppers and make allowances for the recommendations they may have received from their friends over these channels. Shoppers get the information they need, in many cases even before they know they need it and this helps them make better and faster buying decisions. Amazon is also leveraging machine learning for making price comparisons across other online retailers so their customers can get the best prices possible – not a mean feat when you consider the millions of products and the hundreds of potential retailers to compare with.
Are you being served?
Ok, so the retailer with vision has leveraged Machine Learning and looks set to reap the benefits. How about using Machine Learning to improve service delivery? That looks set to happen soon too. Zendesk already has a tool waiting in the wings that will apply machine learning and big data analytics to customer service. Organizations are already looking at Machine Learning to help their service delivery by training new additions to the team, especially temp workers who come onboard in the busy season. Team members are able to respond better and faster as the intelligence in the system helps them make the right choices to service requests and situations. The number of transactions is high, orders are all rush-rush and tempers run high – any available mechanism to empower the people responsible for service delivery is like an early (or late) Christmas present to any retailer!
I am convinced that Machine Learning is only slated to become more and more mainstream. The good news, for me at least, is that I am not alone. Wasn’t it Bill Gates who said, “A breakthrough in machine learning would be worth ten Microsofts.” I sense that breakthrough may be just over the holiday horizon.