Artificial intelligence is enabling big-box retailers to create hybrid physical-digital environments — and that could be just what brick-and-mortar retailers need in order to compete with e-commerce.
E-commerce hasn’t been friendly to big-box retailers. Ever since Borders bookstore realized it could no longer compete in 2011 and shut down all 399 of its stores, there’s been a steady stream of iconic stores that folded.
Over the last decade, e-commerce’s victims included Toys “R” Us, the Sports Authority, and Pier 1 Imports, to name a few. For a long time, it seemed that big-box retailers were facing an inevitable descent into obscurity and irrelevance.
However, AI tools are starting to level the playing field — giving big-box retailers a fighting chance of survival.
Big-box stores frequently feel like they’re at a disadvantage. Online shops are open 24 hours a day, making it easy for consumers to compare prices. Furthermore, people shopping online can easily search for products, see related and recommended items, and get then delivered to their house within days or even hours, without having to lift heavy boxes or push their way through crowded aisles.
In many ways, though, AI is providing retailers with the ability to fight back.
Perhaps the biggest challenge facing retailers was the physical limitations that they needed to contend with. In an online environment, changing prices can be accomplished with the click of the keyboard. In a physical environment, a simple price change requires a stock person to find the item and replace all the price tags.
Changing prices, one tool that physical retailers could wield to compete, was simply cost prohibitive, when you consider the labor involved and the sheer volume of items in a store.
However, AI tools have been part of a digital revolution taking place in retail shops. The physical store is introducing digital technology, which is allowing it to compete, in many ways, with its online competition.
A few pieces of technology are helping to bring digital transformation to physical locations.
Electronic shelf labels (ESLs) are essentially digital price tags. Some simply display a price, while others contain product details, and have the space for messaging. ESLs can be updated from a central location, allowing pricing managers to change their price at point of sale and on the shelf at one time.
Computer vision is another AI-driven technology that’s finding its way into stores. Essentially, these systems recognize items on the shelf. It can be used for tracking inventory on display, or following items that are placed in a shopping cart.
Beacons that use ultra-wideband frequencies for geo-positioning are also being deployed to track items on the shelves. The real-time data can be used by AI systems, as they guide consumers on their shopping trip.
Shopping in a store has some real advantages over e-commerce. Customers can see the item they’re buying, ask questions to a salesperson, and bring their purchases home without having to wait for a delivery.
Yet the benefits of shopping in a store are often overshadowed by e-commerce. Following are five ways that AI tools are creating an in-store shopping experience that rivals the benefits of online shops, while preserving the physical retail shopping trip.
Profit optimization. E-commerce sites use pricing optimization techniques to woo customers. They can create special offers to customers who are members, or change prices in a moment to compete with other retailers.
Using ESLs, retailers have much of that ability as well. When connected to an AI-driven pricing optimization tool, retailers can track competitor pricing, and make adjustments at any time. The prices are clearly labeled on the ESLs, and will scan correctly at the checkout lane.
As retailers get more advanced, they can introduce loyalty pricing features, which could appear on a customer’s phone as they walk past items, or even be displayed when the ESL recognizes a loyal customer.
Inventory turnover. AI tools can track inventory levels, and use that information to help stores turn their inventory over more effectively. Physical grocery stores, for example, can use inventory turnover tools to move items that are nearing their expiration or sell-by dates. Stores can offer discounts on this merchandise, allowing them to sell off the inventory before it goes bad.
Inventory turnover tools can also be used to ensure that merchandise is always available, by increasing the price — and profit margin — on merchandise that’s in high demand.
Clearance items. Seasonal merchandise or models that are about to be replaced represent a big challenge to retailers, who often throw everything into a discount bin and try to sell it at large discounts. This eats into profits, though, and weakens the retailer.
Using AI, retailers can precisely identify the price where an older item will sell. Rather than practically giving merchandise away, AI helps retailers remain competitive while clearing out unwanted merchandise.
24/7 availability. Big-box stores can turn to AI tools to provide their customers with 24/7 availability. Computer vision has evolved to the point where it can track individuals as they walk through the store, and identify the items they’ve picked up while shopping.
Computer vision enables retailers to operate unmanned stores. The technology can track every item placed in the cart, and integrate with self-checkout machines so that customers can buy whatever they need, any time of day or night.
Search for products. Ultra-wideband technology is used to track items indoors, and capable of guiding consumers to within 12 inches of an item. Powered by AI, it can be deployed by retailers in a number of different ways.
First, consumers can search for products, making it easier to find what they’re looking for. Second, it can be used to guide them toward recommended items. If consumers put a camera in their shopping cart, for example, it can guide them toward camera cases.
At Walmart Inc., computer vision tools track product inventory and availability, and smart cameras locate abandoned and empty shopping carts in the store. Cameras track the number of customers in line and the number of open checkout lanes. When needed, the system alerts human employees to open up additional registers.
Costco Wholesale Corp. uses machine learning to help it determine the number of baked goods to make each day in its bakery. The system uses a demand forecasting algorithm, which ensures that they have the right number of fresh products available every day.
By transforming their stores into hybrid physical-digital environments, big-box retailers have the ability to create a shopping experience that captures the ease and convenience of online shopping with the tactile, real-world experience of walking through a store. That could be just what they need to get customers back in their stores.
Pini Mandel is cofounder and CEO of Quicklizard, an AI-driven pricing optimization platform.
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