A Blog by Jonathan Low

 

Aug 15, 2017

The Reason Artificial Intelligence Has Become Imperative For Retailers

Better retention and correlative or causal data relationships result in more predictive accuracy, meaning higher sales at lower costs. JL

Japjit Tulsi reports in Venture Beat:

AI by itself is a catalyst for achieving greater levels of personalization with shoppers. The ability to use text, voice, and photos is becoming the new norm because these provide users with a much richer and more efficient way to express their shopping intent. We call this “multimodal shopping.” It can find similar products it knows you like based on a similar image or photo match.These interactions yield a tremendous amount of user data that can be poured right back into AI algorithms to improve contextual understanding, predictive modeling, and deep learning.
Most people don’t realize that they’re likely exposed to AI each and every time they shop online — whether it’s on eBay, Nordstrom.com, Warby Parker, or any other retailer. When you are searching for an item and a merchandising strip appears saying something like “similar items” — that’s AI in its simplest terms. It’s what gives retailers the ability to automatically make informed recommendations.
AI has been around for many years, but recent advancements have moved AI out of the realm of science fiction and made it a business imperative. The game changers: powerful new GPUs, dedicated hardware, new algorithms, and platforms for deep learning. These enable massive data inputs to be calculated quickly and made actionable, as technology powers new algorithms that dramatically increase the speed and depth of learning. In mere seconds, deep learning can reach across billions of data points with thousands of signals and dozens of layers.
We all aspire to a grand vision of AI’s role in commerce, and recent developments are creating a fertile environment for new forms of personalization to occur between brands and consumers. Make no mistake about it, the implications of AI will be profound. This is the new frontier of commerce.

A multimodal, multi-platform approach

As an industry, we are just beginning to scratch the surface of AI. In the next few years, we will see AI-powered shopping assistants embedded across a wide variety of devices and platforms. Shopping occasions will take advantage of camera, voice interfaces, and text.
We are already witnessing the early success of voice-activated assistants like Google Home, Siri, and Cortana. It won’t be long before we see virtual and augmented reality platforms commercialized, as well. We see a future rich with voice-activated and social media assistants on platforms such as Messenger, WeChat, WhatsApp, and Instagram. Personal assistants will be everywhere and are already being woven into the fabric of everyday life. This means commerce will become present wherever and whenever the user is engaged on the social, messaging, camera, or voice-activated platforms of their choice.

AI: The future is personal

AI by itself is simply a catalyst for achieving greater levels of personalization with shoppers. Customer data and human intelligence are the critical ingredients needed to run a personal AI engine. As we continue to launch more sophisticated applications, technologists should continue to focus on how to make greater use of our treasure trove of customer data. Looking ahead, the industry will evolve to combine customer data and human expertise into a deep knowledge graph. This will establish a knowledge base to create highly personal and contextual experiences for consumers. For the commerce industry, this will allow us to get a clearer understanding of shoppers’ intent and to service them in a more personalized way.

Personal commerce

Keyword search for shopping is not enough anymore. The ability to use text, voice, and photos is becoming the new norm because these avenues provide users with a much richer and more efficient way to express their initial shopping intent. We call this “multimodal shopping.” And these new types of consumer interactions yield a tremendous amount of user data that can be poured right back into AI algorithms to improve contextual understanding, predictive modeling, and deep learning.
Across the three spectrums of multimodal AI, we’re starting to get much better at understanding our customers and the way they like to interact with us. A few good examples of this have to do with how our personal shopping assistant, eBay ShopBot on Facebook Messenger, “remembers” you. It can keep track of your shirt size or the brands you like, so it won’t keep suggesting Nike when you prefer Adidas. The assistant also uses computer vision — it can find similar products it knows you like based on a similar image or an exact photo match.
Innovating on a canvas of AI provides many new opportunities to create highly contextual and personalized shopping experiences. From our perspective, every company should be investing heavily in AI, and it shouldn’t just be about using cognitive services. Companies should actually be developing their own models that keep them on the cutting edge of technology. While there is still a lot of work to be done in this area, one thing is clear. The companies that chart the right course in this exciting endeavor will prosper. The ones that don’t face extinction.

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