![Atlantis Management Group, InStore.ai](https://cdn.winsightmedia.com/platform/files/public/2024-08/background/800x1000/WSM-instore-ai.jpg?VersionId=yffPfxT3LpQ4OAqWXKKaoUI.nFf_E2D4)
Using data to tell stories helps Atlantis Management Group (AMG) train its employees and maintain success in operations. The Mount Vernon, New York, 95-location convenience-store chain partnered with InStore.ai to enhance its data collection.
- Atlantis Management Group is No. 71 on CSP’s 2024 Top 202 ranking of U.S. c-store chains by size.
InStore.ai is a technology company that offers retailers artificial intelligence (AI)-based data reports. The company provides microphones for retailers to place strategically throughout the store, near the register, for example, to record audio from employees and customers. The audio is then assessed by AI.
The technology provides retailers with highlights of customer complaints, theft attempts, cashier behavior and more. Retailers can view themes on a dashboard or search for any phrase or word in the system to hear what’s being said.
“I wanted to find ways to not just tell big stories about what's going on in our stores, but back it up with data, Rick Rigby (left), chief technology officer at Atlantis Management Group, said at CSP’s Outlook Leadership conference last week in Rancho Palos Verdes, California. “And so we looked at InStore.ai. We wanted to figure out how we could do better things with loyalty, and how to improve the data, [which employees are] talking about it, who's not.”
Rigby was joined by Babir Sultan (middle), president of FavTrip, and Jay Blazensky (right), CEO and co-founder of InStore.ai in a session at Outlook.
InStore.ai has been active in Atlantis Management Group for about five weeks, and instead of shoehorning data, Rigby said that it’s valuable to have the data tell him what’s going well and what could be improved.
“Then I give smart people smart data, let them do smart things with it,” he said.
AMG has benefitted from figuring out how to take the regions that are performing well with loyalty and apply it to regions that are struggling. Rigby has been able to use InStore.ai to look at trends and patterns on the dashboard—such as which region of employees are pushing the loyalty program at the checkout counter—instead of spending time trying to figure out the data himself to move the needle.
“Now I can sit down with my training teams and say, ‘here's where you're doing well, and here's an example, here's some audio,’” he said.
In addition to loyalty, Rigby has been learning more about the safety of his employees through audio, which was unexpected, he said.
“I wouldn't have caught that if I was just trying to listen to 24 hours of audio in one store,” he said. “And when I see hot spots, I can go, ‘Hey, this one store in Bay Chester is struggling because X data told me something I didn't know.’ To me, that's super powerful.”
This can be applied to any area of the store, Rigby said, such as forecourt maintenance or bathroom cleanliness, and “that can effectuate actual change,” he said.
From a merchandising standpoint, it’s also powerful to capture when specific products are mentioned by name, whether its by customers or employees trying to push product.
“We all have lots of data, but you can't find it and squirrel it away somewhere, so there’s a lot of power in [AI],” Rigby said.
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