Ravi Annavajjhala - CEO, Kinara Inc.
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The retail world is undergoing a dramatic change driven by pandemic-induced economic and societal factors. Over the last few years, the appearance of frictionless self-checkouts has surged through high street stores and supermarkets of the world.
Now, entirely cashierless stores are beginning to emerge. By combining a variety of sensors and technologies powered by artificial intelligence (AI), these stores enable consumers to shop quickly and efficiently—improving stores' ability to drive revenue, draw customers and better understand their own businesses. Many retailers such as Aldi, Carrefour, Sainsbury's and 7-Eleven are now testing or using this frictionless technology to great effect.
The Catalysts For Cashierless Stores
The new surge in the popularity of this retail model appears to have been precipitated by several factors.
The online shopping experience has raised consumer expectations about retail experiences. Old-fashioned retail has difficulty competing with the ease of clicking a few times and having a product delivered to the door. The rise of the cashierless store can be seen as a way of merging the multiple conveniences of online shopping with the communal experience of in-person shopping.
Although the rise in cashierless shopping is largely driven by the decreasing cost and increasing availability of AI-powered technologies, convenience is perhaps the clearest benefit for consumers, who get to enjoy the live shopping experience coupled with the ease of online shopping.
The Current State Of Cashierless Retail
The number of cashierless stores has increased significantly over the last few years—and for good reason. These stores allow customers to merely walk in, take what they want, get automatically charged and leave. However, this seemingly simple interaction is principally underpinned by a complex and evolving series of AI-powered technologies driving the revolution.
Computer vision uses a series of cameras embedded throughout a store and translates visual information into actionable data. Like the human eye, computer vision doesn't just see shapes and colors; it can recognize objects, people and products. Therefore, it can thoroughly map customer interactions and choices within the store.
Sensor fusion combines data from sensors throughout a store—including, for example, weight sensors on the shelves that detect when an item is removed or put back. Camera sensors can simultaneously capture video that feeds person identification technology to identify and track individual customers. In that way, sensor fusion can help cashierless stores paint a full picture of what's happening within a store.
Deep learning technology enables other store technologies to continuously learn through the collection and analysis of data from multiple sensors and cameras. In doing so, it can improve processes, fix supply chain issues, better understand customer preferences and resolve potential long-term problems before they arise.
There are other technologies at work, too, such as customer identification systems that involve an app-generated QR code that smart retail account holders scan upon entry into a store.
Recognizable Models Of The New Reality
The model of cashierless retail by Zippin, which involves AI technology embedded throughout a store, is a very popular option. Zippin uses a combination of cameras, shelf sensors and AI that allow customers to walk in and tap their credit card or a pre-generated QR code on a turnstile sensor to pay.
The Grabango application was designed for large stores of more than 100,000 square feet. It uses an array of tiny cameras embedded in stores' ceilings to run its computer vision capabilities, track what customers are buying and log stock changes. It can then integrate with existing, unattended checkouts—so customers still pay, albeit contactlessly, in-store.
Other models offer distinct forms of frictionless functionality. For example, Imagr and Caper produce smart shopping carts. Customers scan items before they put them in their cart or have their purchases totaled through a series of sensors within the cart itself. The smart carts also employ deep learning to improve the operation of each cart.
Mashgin, on the other hand, employs a countertop device into which customers place their desired purchases. Cameras, weight sensors and computer vision then establish what those desired purchases are and generate a bill that customers pay in-store—making the process distinctly different from other kinds of cashierless stores.
Practical Matters
The presence of AI makes the benefits of cashierless stores far more noticeable and profound for consumers. However, for their owners, cashierless stores can be managed remotely, which means they do not require manual intervention. Processes can be changed and improved automatically, improving staff utilization and reducing the chance of human error. The presence of AI can also cut down on theft.
Not Quite Self-Aware, But Self-Correct Is Close
The AI within cashierless stores can also use the data it collects to learn and self-correct, thus greatly driving efficiency, supply chain improvements and helping to solve problems before they arise. The longer a store is in operation and the more data it collects, the better it can refine and improve its operations to identify and act on necessary operational changes, regardless of the problem's size.
Cashierless stores may well be the frictionless future of brick-and-mortar retail. Many large retailers in the U.S., India, China and across Europe are already testing it—if not using it outright. As AI technologies become more widely available, reliable and accurate, the prospects for cashierless retail stores become even more attractive to retailers, consumers and suppliers.
The explosion of those cashing in on the cashierless store revolution is only just beginning.
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