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The average time a consumer spends in a grocery store is 41 minutes. The trip quickly gets longer when shoppers spend time looking for out-of- stock items. Retailers who are already dealing with post-pandemic staffing shortages, supply chain disruptions and reduced foot traffic want that too.
cashierless checkout and inventory management is powered by computer vision and artificial intelligence. A variety of companies, both big tech and startups, have taken different approaches over the past few years, using cameras and sensors to identify items and ringing them up, allowing the customer to quickly grab items from the shelf and leave without standing in line.
Even as the economy slows, investors don’t seem to pull back on their investments in this sector. The Tel Aviv-based Trigo, which last week announced a $100 million series C investment, is one of the big funding rounds still making news.
Amazon Go spawned many competitors
Six years ago, everyone thought that Amazon had a cashierless grocery store model in its bag. There are only 28 Amazon Go stores worldwide, and that includes its recent expansion in India.
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Brad Jashinsky said the main technical challenge was scaling up the systems to handle more customers and larger store formats. There is a need to integrate them into existing footprints.
Several startups have stepped in with their own computer vision-powered technology in order to solve for scale and ease of integration. Caper Artificial Intelligence, which was acquired by Instacart in 2021, has focused on plug-and-play smart carts or kiosks. Ceiling cameras, shelf sensors, and digital twin technology are some of the things that AiFi and Trigo are focused on. Even though the economy is going through a downturn, there are still opportunities in this niche sector.
Bringing computer vision to the physical store
The draw of computer vision for grocery retailers is gaining the capabilities currently available to them in an online space and bringing that intelligence into their physical store spaces according to Michael Gabay, CEO of Trigo.
Gabay said that the market for grocery retailers is larger than the online market.
According to a study released late last year, the majority of retail respondents expect to increase store technology investments.
Jashinsky explained in an email that retailers have been forced to focus on connecting their stores to their entire network. Digitalization of store technology investments, including check-out computer vision, has been given new attention.
Brothers Michael and Daniel Gabay, who grew up on a kibbutz in northern Israel, founded Trigo in 2017. The CEO and CTO were set to be the antidote for the headaches of waiting in checkout lines.
Its 3D store mapping and computer vision capabilities uses artificial intelligence and machine learning to keep track of a customer’s shopping tab as they go, even updating the total if they put an item back, and it charges them accordingly when they walk out. It can alert store employees if it suspects an item has been hidden in a jacket by tracking item stock and customer body language. This doesn’t involve any data from facial recognition or Biometrics.
While that may sound like a lot for retailers to wrap their brains around, all they need to do is work with Trigo to set it up, and once the installation is complete, nothing more is required, and they have the green light to begin using it.
Gabay is confident in Trigo’s ability to stand out among the crowd despite the plethora of competitors and growing interest in the market as a whole. The company is currently deployed in supermarket chains in the U.S., the U.K., Israel, the Netherlands, and Germany.
Gabay told VentureBeat that they are the only startup that converts existing stores to autonomously-operated stores. We are the only startup that is focusing on supermarkets and not just convenience stores.
Trigo claims to be able to implement its technology in stores of 3,000 to 5,000 square feet. AiFi claims it can be used in up to 10,000 square feet.
Retail-focused computer vision surge
The market for computer vision is expected to increase to $41 billion by the year 2030. McKinsey analysts recently wrote that investing in technology like this is the next step for the industry.
Grocers used to be able to experiment with or increase the wow factor in their stores rather than support mission-critical operations, according to an article. A wide range of affordable, field-tested technologies can help retailers reduce the cost structure of their stores while delivering a better experience for consumers and employees.
More than half of C-suite executives have plans to increase their tech budgets next year, with 75% saying they have plans to increase it within the next five years, according to a survey.
Jashinsky doesn’t expect the boom in retail-focused computer-vision innovation for retail to phase out anytime soon with its range of use cases from labor allocation, checkout ease, merchandising, inventory management, loss prevention and maintenance.
The ability to provide ambient customer transactions is one use case for smart check-out computer vision technology.
Retailers using computer vision for smart check-out can leverage real-time insights captured to improve decisions.
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