Humans hate waiting in line — and retailers are captivated by the prospect of frictionless point of sale. Anything they can do to remove resistance from in-store transactions yields happier shoppers and better shopping experiences.
Standard Cognition’s solution is simple: It removes the checkout process entirely.
The San Francisco-based start-up’s artificial intelligence and computer vision-based system lets consumers shop and pay without having to scan bar codes or queue up to check out; they simply remove items from the shelf, place them in their bag and leave. Payment is processed automatically as shoppers exit the store, and store inventory is updated in real time.
“Our solution is fully autonomous, and the technology can be deployed very fast,” says Michael Suswal, co-founder and chief operating officer. “We put cameras in the ceiling, set up a computer in the back room and that’s it.”
Standard Cognition’s artificial intelligence and computer vision-based system lets consumers shop and pay without having to scan bar codes or queue up to check out.
Anonymous data
The cameras, which are slightly more sophisticated than traditional security cameras, can identify who walks in, what they’re carrying and what they walk out with. Facial recognition is not used; the images keep the data anonymized and they are removed once the person leaves the store. The platform hosts all its processes on-premise, rather than over a cloud-based infrastructure.
Two apps underpin the technology — one for shoppers and one for store staff. Customers check in by simply opening the shopper app; there’s no need to interact with it beyond that. On the store side, staff can monitor who’s in the store, where they are and what they’re buying; the system automatically detects shoppers, matches them to their basket and processes payment.
Shoppers can shop as a guest, but some of the convenience is lost: Guests are directed to a kiosk where the store app detects the shopper and the basket and accepts payment via credit card or cash. Anyone who attempts to leave without paying will be flagged on the store app and redirected by staff to a kiosk.
“There are a handful of companies out there trying to solve for frictionless checkout. We’ve seen trials where shoppers scan items with their smartphone, another measure uses a smart basket and many are familiar with the Amazon Go experiment which relied on floor sensors, specialized shelves, machine vision and several other tools,” Suswal says.
“The difference is that our technology doesn’t require investments in sensors or radio frequency identification. We can deploy this technology in a small store in a day — even large retailers can be up and running in less than two weeks.”
Suswal believes the Standard Cognition platform can help retailers lower labor costs, reduce shrink, take back real estate formerly dedicated to checkout and better track inventory.
“Our solution improves the checkout experience for their customers and thus improves their ability to compete,” he says.
Pilot plans
Right now, the most natural application for this technology is smaller format: convenience stores, mom and pop operators or small footprint grocery retailers. In the meantime, the team is working to solve challenges around fitting rooms and items that need to be weighed. “Obviously we can’t put cameras in a fitting room, so we need to solve for that before we could deploy in an apparel setting,” says Suswal.
Early next year plans call for opening a beta store that will demonstrate how the technology works. Suswal expects to have four to five pilots up and running by mid-year.