Why AI Could Be the Solution Your Store Needs

Artificial intelligence (AI) is one of those terms that can conjure up a lot of images and ideas, from lifelike robots to futuristic video games. Its current uses are much more down to earth, though, and food retailers large and small are finding ways to harness its power to forecast demand and stock, customize promotions, create frictionless shopping journeys, and so much more. 

AI leverages data, computers and machines to accurately mimic the problem-solving and decision-making capabilities of the human brain. In retail, this can translate to machine learning that uses customer analytics to predict trends, Internet of Things solutions that can help streamline operations, or computer vision that brings business insights to physical stores.

With myriad additional applications, AI is rapidly taking the grocery industry to the next level during a time when price volatility, labor shortages and competitive markets threaten to derail its progress. Whether it’s used in the picking, packing, stocking, decision-making or purchasing step of the retail journey, the technology can bring unprecedented efficiencies and customer value to every kind of grocery operation.

Keeping It Fresh

Maintaining the freshness of produce, meat and other perishable products is a perennial problem for grocers, along with ensuring that very little of them go to waste, but AI is now being employed to help create solutions. San Francisco-based Afresh Technologies, for example, has created AI-based networks that can predict demand trajectories over time to help forecast how demand will change over the next few orders. The company’s state-of-the-art neural networks take into account several fresh variables for each forecast, in turn helping to build the best order possible. 

Afresh recently joined forces with food solutions company SpartanNash to pilot the AI-powered predictive ordering and inventory management solution at 10 Grand Rapids, Mich.-area Family Fare grocery stores. Not only will this ensure fresher products for Family Fare’s customers, but it will also empower the banner’s associates to make decisions based on hard-earned data.

“Our partnership with Afresh will help SpartanNash deliver fresh produce to our store guests while also minimizing food waste, which is a key focus area for our company’s ESG efforts,” said SpartanNash Chief Merchandising Officer Bennett Morgan, when the technology rolled out to the stores in December. “Leveraging the strength of artificial intelligence and digital workflow will provide our associates with insights to create solutions that benefit our corporate retail store guests.”

Removing Friction

AI is also being used in other parts of the world to help grocers create a seamless, friction-free customer experience. German discount supermarket Aldi Nord recently partnered with Israel-based computer vision company Trigo to open an AI-powered supermarket in the Dutch city of Utrecht. Thanks to Trigo’s algorithms, shelf sensors and ceiling-mounted cameras that analyze shoppers’ movements and product choices, the autonomous supermarket can let shoppers walk in, select their items and walk out without having to wait in a checkout lane or scan any items. 

Edge computing and AI provided by Chinese company Lenovo have enabled The Kroger Co. to create an even more seamless self-checkout system for its customers. According to Lenovo, an AI application analyzes the video footage from checkout kiosks in real time to recognize regular processes and also to step in when something is amiss. The process covers instances when a customer or cashier fails to scan an item, as well as more targeted and intelligent use cases.

“We operate in a sector where margins are very thin, so anything that gives us the opportunity to grow sales while reducing losses can be a great source of competitive advantage,” says Chris McCarrick, senior manager of asset protection solutions and technology at Cincinnati-based Kroger.

The Whole Kit and Kaboodle

While AI is certainly helping in bits and pieces, some retailers and third-party vendors are taking a more all-encompassing route with the technology. Through a partnership with Focal Systems, Sheboygan, Wis.-based Piggly Wiggly Midwest is running a pilot program of the retail automation company’s operating system that digitizes the entire store to automate and optimize ordering, inventory management, merchandising and in-store labor. 

“We’re thrilled to work with such a beloved and historic grocer that has been a staple in American lives for more than a century,” says Francois Chaubard, CEO and founder of Burlingame, Calif.-based Focal Systems. “I’m seeing the first signs of massive adoption of AI and computer vision in the grocery and retail industry, and it’s exciting to see one of the best grocery chains helping to lead the charge.” 

Walldorf, Germany-based SAP, meanwhile, has created an intelligent concept store dubbed “S.MART” that showcases several AI use cases offered by the software company. Forecasting technology driven by AI can help prevent stockouts, while AI connected to video cameras and other sensor-based technology can alert store personnel when products are misplaced or shelves are empty. Additionally, AI coupled with machine learning can help tackle workforce issues by offering insights into the busiest times and store sections to create optimized staff schedules.

Getting Onboard

With the ability to help shoppers, team members and ultimately a food retailer’s bottom line, AI is the latest piece of the grocery puzzle that should not be ignored. Roy Horgan, SEVP of strategy at Nanterre, France-based SES-imagotag, a company that provides in-store digital technology solutions for retailers, explains that the practical use of technology, including computer vision, on-shelf automation and analytics, can indeed allow a retailer to see how profitable every shelf is, how it’s performing, and thereby find ways to dynamically optimize its operations.

Even smaller retailers can find success by wading carefully into the world of AI. Horgan shares an AI use case where an analytics tool can look at a product and its price on the shelf, and then scrape competitor websites to see their prices on the same product. Using a dynamic price tag, retailers can then shift their own pricing, thereby increasing rates of sale and delivering a value message to the consumer in a completely hands-off manner.

“We believe every store can learn, every store can be optimized,” Horgan says. “There’s no reason why you can’t have stores that have 2% or 3% higher profitability but also have waste below 1.5%. That’s where it gives me so much joy and hope that physical retail is a completely underperforming, underutilized asset that can be improved.”