How can artificial intelligence today play a role in changing ecommerce, moving beyond customer segmentation strategy and simplifying the work of ecommerce marketers to help them achieve the best possible results? We took a look to find out.
The Ecommerce Industry Today
The ecommerce industry today is worth close to 1.9 trillion dollars. E-commerce sites have now been around for over 20 years, (amazon started their first online bookstore in 1995) but these platforms have never been as big as they are now. With changing times, tides and technology ecommerce has grown to be present across devices and product niches. As ecommerce platforms grew, customer segmentation strategy became the thing create better engagement. This is based on the fact that you need to first understand a customer’s age, gender, demographic and more before you communicate with them. Today, it’s all about using artificial intelligence to enhance your customer segmentation using other factors like metadata, semantic analysis, collaborative filtering and predictive recommendations to increase conversions and grow your platform.
Sidenote: If you don’t know what a customer segmentation strategy is or aren’t using it yet, get on that asap.
Artificial Intelligence for Ecommerce
So how can artificial intelligence help you get to know your very real customers better and optimize your ecommerce platform to cater to them in a personalized, 1:1 way to encourage sales and conversions? Here are some of the many ways AI can do not just that, but also revolutionize your ecommerce experience altogether.
Personal Shoppers V2.0
Personal shoppers exist in real life and their less expensive counterparts work at stores and provide the experience of a personal shopper for free. But what if you feel the person at the store simply doesn’t get what you are looking for and you want an alternate way to curate your shopping list? Artificial Intelligence is all up in that. Even backpack and outdoor gear brand The North Face tied up with IBM’s AI engine Watson to curate your jacket buying experience, and I must say – it was a delight talking to Watson to find a jacket I liked.
Image: The North Face
By asking a few basic questions, the engine took care of customer segmentation without me needing to fill up forms or enter information about what color, size, and material I wanted. In no time, I watched my customized results appear, and I liked what I saw. North Face, I’ll be back!
Mona – This iOS-only app can, according to her website “do the heavy work.” Searching over 260 trusted shopping sites to let customers find what they like is quite impressive.
Wazzatlabs – A fashion curation platform powered by AI that helps you save looks and outfits from your pinterest and matches them to products around the web to curate your lookbook automatically.
Assortment intelligence is a great way for ecommerce stores today to stay on top of their competition in terms of sales, offers and pricing. Assortment intelligence platforms analyze your competitors and tell you how they are managing their catalog, what stands out about your catalog and how you can make the best of it by pricing and stocking right.
Image: Upstream Commerce
Upstream Commerce: Helps you understand how the competition is managing their catalog, and optimize your assortment.
Dataweave: Promote the right products, enhance stock availability of popular products, understand competitor promotion strategy, optimize marketing ROI and get analytics to make faster decisions.
What’s the best thing that can happen after you find the kind of product you love in an ocean of products? Well, you could find another one just like it – but that doesn’t happen to often does it? Wrong. With Artificial Intelligence and machine learning, you can go beyond customer segmentation strategy to create intelligent, customized recommendations that work for users on a 1:1 level.
Whether it is content, clothes, food, chainsaws or anything else they may order online – artificial intelligence software can intelligently predict what your customers would like using advanced algorithms that are learning to think like the human brain does.
Boomtrain: Personalized 1:1 recommendations for ecommerce, publishing and more.
Artificial Intelligence powered visual search has gotten so good that you can now just hold up your camera or take a photo of a product, and have an AI engine do the rest of the work for you. Want to find clothes with a similar color? Done. Style? Done. Pattern? Also done.
That isn’t all. Some visual search platforms also help ecommerce platforms take care of tagging their product database and offer to source online ecommerce recommendations for similar product from your ecommerce store for pictures taken in regular brick-and-mortar stores. Cool, right?
Mad Street Den: Mad Street Den’s visual search and recommendations technology analyzes clothes and pulls up visually similar outfits, adding tags to them. Say goodbye to manual tags!
Twiggle – This visual search platform is still in beta, but that didn’t stop Ali Baba from investing in it.
Slyce – Using image recognition technology for both mobile and desktop, we activate visual product recognition on existing product images or by simply snapping a photo.
In January 2016, Chris Messina (the inventor of the hashtag) predicted that 2016 will be the year of conversation commerce. It appears he was partially right. Ever since the explosion of bots onto the scene and facebook opening up messenger’s API to make it bot-friendly, a wave of online retail and service websites have taken the conversational commerce route. Although we aren’t leaving you with a list of tools to use conversational commerce with, here’s a video from Tacobell that shows you how they used conversational commerce to help teams order food from the messaging app Slack.