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How can computer vision pump-up digital transformation at the convenience store?

Added to IoTplaybook or last updated on: 01/09/2023
How can computer vision pump-up digital transformation at the convenience store?

While the challenges facing the retail sector have been substantial over the past few years, convenience stores are seeing their sales continue to reach new highs. In 2022, convenience stores raked in 25 percent more revenue than the year before, topping $663.5 billion, according to the 2022 Convenience Store News Industry Report.

So what makes convenience stores a unique—and thriving—sector compared to traditional brick-and-mortar retail? For starters, roadside convenience stores (also known as c-stores) are designed to be a one-stop-shop for family road trips and truckers alike.

Combining traditional retail layouts with self-service food and beverage, the c-store environment offers some great examples into the ways computer vision technology can help operators make smarter business decisions. Integrating vision AI into their stores can help to increase efficiency and maximize profits.

For many mixed retail/restaurant spaces this means monitoring self-serve food stations, coolers, and even fueling stations. But how can these businesses keep eyes on their whole operation all at once? Vision AI offers a possible solution. As more top c-store companies, like East Coast standard Wawa, look towards digital transformation we can expect to see other industry giants follow. 

Computer vision technology allows businesses across sectors to train cameras to autonomously monitor or collect information through images and video by creating specialized computer vision models. These vision AI models distill business insights out of the video and images that are being collected through camera networks and open up new streams of operational analytics for proprietors to improve processes and increase efficiency.  

Smart Inventory

We’ve written before about how smart planograms can help retailers automate daily inventory and maximize their backstock; a use case that absolutely applies to the c-store space. From stocking every candy under the sun to sodas, beer, water and sports drinks, there is a lot of product to track. With specialized CV models retailers can track individual coolers for brand specific products or monitor snack shelves to send notifications to employees when items need to be restocked.

Keeping it Hot and Fresh

Warming stations are another area that vision AI insights could help operators cut food waste and stay within food code regulations. Models can monitor how long items have been out in the warmer and alert employees when it’s time to restock with a fresh batch. With in-store foodservice sales being up 20% in the last year, according to the Convenience Store News report, investing in new technology to further optimize the operational efficiency of foodservice is a no-brainer.

Fueling Business Analytics

There is also plenty of opportunity for vision AI to be useful outside of the store. Gas sales make up a large percentage of revenue and some franchises even offer rewards programs. Adding cameras to read QR codes would be one way retailers can create contactless payment experiences at the pump while enriching the customer experience. Store operators can also monitor wait time, customer turnover and safety, and interaction at the pumps.