When AI Meets Retail: Opening New Possibilities

While the emergence of ChatGTP has pushed artificial intelligence (AI) into the headlines, this technology has been used for some time in retail environments to help us better understand consumer behavior, spot trends, and optimize the customer experience.

In fact, the market value of AI in retail is expected to be over $31 Billion by 2028, according to Fortune Business Insights.

Already, retail chains such as Lowe’s and Kroger are using AI simulations to optimize store layouts, improve merchandising, and design easier and faster checkout.

AI has also been central to helping the new “grab and go” autonomous shopping experiences that proliferated during the pandemic. (Just think of the unmanned convenience shops and food stands that are now commonplace in airports.) Without smart cabinets, AI-enabled shopping carts and checkout stations, this new autonomous model would not be possible.

At the most accessible level, AI is helping smaller retailers communicate with their customers online. In fact, you may already be using a chatbot to answer common questions on your website. What’s more, some e-commerce sites are incorporating virtual dressing room technologies that allow customers to visualize and style products on models that resemble their shape and size.

Fashion Forward

In the fashion world, AI is now going even further by helping some vendors generate designs based on customer feedback, as well as track market trends and other data.

One innovator in the space is a company called Fashable AI, which puts together neural networks to take in trend, clothing, and style data from a variety of sources. The technology can then parse what is going in and out of style to create digital AI collections (see pic above as example.). It also gives designers the ability to show their designs to customers and gauge demand before they manufacture.

Smarter Planning

In addition to creating new ways of seeing the retail world, AI can also help us get better at how we analyze our in-store data. As professional planners, we know that the more and better data we collect, the better we’ll be at creating accurate forecasts. This helps us improve sell-through rates, margin, and cash flow.

Our custom planning software has a lot of intelligence built in, since it incorporates both merchandising best practices and decades of retail experience in its algorithms. But as far as AI is concerned, we are looking at new tools that allow us to look at the data in a fresh way. One is a data visualization tool called Tableau, which can help us uncover insights and improve prediction capabilities.

“Using AI can definitely make us smarter, but we can’t overlook the value of lived experience when it comes to retail cycles in specialty stores,” says Blacks’ Founder Steve Pruitt. After all, data is always backward looking and to see the future we need to blend past information with reasonable estimates for what will come next, he adds.

Fortunately, with tools like Tableau we can start to take in important contextual data in the wider world to help us understand what’s happening in our stores. For example, it can help us see the enthusiasm and energy around certain trends and retail locations.

Although recent headlines about AI have made the technology sound like something to fear—by giving human jobs to robots, for instance — at least in the retail world AI opens the door to a lot of interesting possibilities.

“We will continue to invest in technology tools that help us get better at what we do, and AI is one of them,” Pruitt says.