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Amazon Go competitors make case for eliminating cashiers

The NRF Big Show in New York City debuted a host of cashierless checkout technologies hoping to capitalize on the interest generated by Amazon Go.

The NanoStore from AiFi displayed at the NRF show uses payment kiosks to enable automatic checkout.

January 21, 2019 by Elliot Maras — Editor, Kiosk Marketplace & Vending Times

The race is on to make unattended shopping for everyday convenience products a reality. During last week's NRF Big Show in New York City, numerous cashierless store solutions were on display, hoping to capitalize on the interest Amazon created when it introduced its Amazon Go in late 2016.

When Amazon Go debuted, the concept of a cashierless store became a conceivable convenience for many. While the e-commerce giant did not create the world's first unattended convenience store, it did offer one of the most technologically advanced such stores, and at a time when the general public had become more comfortable with self-service technology.

During the Big Show at the Javits Center, five young technology entrepreneurs took turns pitching their cashierless shopping solutions to an attentive audience in a session, "From checkout free to self-checkout — what you need to know about the latest convenience-based payment technologies." All five concepts featured camera vision technology, and all presenters claimed to offer a more cost-effective alternative to Amazon Go.

Some of the solutions presented included prefabricated physical stores, while others consisted of technology to be used in existing stores.

AiFi

Steve Gu, co-founder and CEO of AiFi, presented his NanoStore, a fully assembled, automated store powered by artificial intelligence. Unlike Amazon Go, which is built from the ground up, the NanoStore can be moved from one location to another, Gu said. The store has payment kiosks inside that allow automated payment, and uses AI algorithms for real-time customer tracking and product recognition. Receipts are generated in near real time, and the entire shopping journey can be completed in seconds.

The initial investment can be recovered in less than a year, Gu said.

Francois Chaubard of Focal Systems Inc. explains the benefits of computer vision.

Focal Systems Inc.

Focal Systems Inc. offers a hardware/software solution that uses computer vision and deep learning algorithms to provide automatic checkout to existing stores. Cameras are clipped onto retail shelves that continuously monitor out of stocks, according to the company's website. A product recognition camera retrofitted to the store's register eliminates the need to scan products, accelerating checkout speeds and reducing shrink.

Francois Chaubard, CEO of Focal Systems Inc., said the computer vision is more accurate than barcodes for identifying products and is also highly scalable.

By eliminating barcode scanning, item throughput increases from 22 items per hour to 52 items, he said, and product shrink and "sweethearting" are reduced by 60 percent, delivering a $150,000 economic benefit per year per store. In addition, real-time reporting of out of stocks yields 96 percent on-shelf availability.

Focal Systems conducted operating profit scenario analyses for Kroger and Walmart, Chaubard said, and concluded the technology would improve the companies' operating incomes.

Chaubard said Amazon Go requires a $35 million investment and is not applicable to all locations.

Krishna Motukuri of Zippin claims existing kiosks increase friction.

Zippin

Zippin operates its own store in San Francisco that uses deep learning, computer vision and sensors to demonstrate a cashierless solution that it markets to other stores. While Zippin offers a prefabricated turnkey store, the customizable, modular shelf sensors can be retrofitted to existing stores with no need for wiring, said Krishna Motukuri, co-founder and CEO. The technology also provides real-time inventory tracking and forecasting.

Claiming that existing self-checkout kiosks are clunky and increase customers' friction, Motukuri said Zippin can work in a 25- to 30-square foot store, which is much less than the size of an Amazon Go store. He claimed the investment can be recovered in six to 12 months.

Maxerience

Maxerience provides an AI-powered solution that not only eliminates checkout lines, but links activity at the retail shelf to distribution centers and the product manufacturers, preventing out-of-stocks.

Pradeep Pydah claims the Maxerience solution is highly scalable.

Pradeep Pydah, CEO and founder of Maxerience, said his solution is highly scalable and uses vision cameras to monitor what products are picked. According to the company's website, the solution links retail shelf information to product manufacturers and distributors to eliminate out-of-stocks and provide insight about behavior at the shelf level in real time.

The Maxerience solution does not require any infrastructure changes or hardware installations, or layout changes to prevent camera dead spots, Pydah said. Nor is it necessary for customers to download any apps.

Caper

Caper, the last solution presented, builds a smart shopping cart that is powered by deep learning and AI to enable automatic checkout, said Lindon Gao, co-founder and CEO. The smart cart has a mounted camera that takes a picture of each product as it is placed in the cart, while a mounted customer-facing touchscreen displays a running tally of the products placed in the cart, according to the company's website. The customer then pays by credit card on a card reader mounted next to the touchscreen. The customer skips the checkout line.

Pradeep Pydah claims the Caper solution can increase the customer's bucket by 18 percent.

The Caper technology can increase the average bucket by18 percent, Gao said, and it yields savings that allow the investment to be recovered in 10 months.