How data is reshaping real estate in US

By Patrick Sisson

Jordan Fisher was troubled. Every variety of the Red Bull energy drink comes in a similar metallic can, and his company’s camera system, which tracks products that customers pick up in stores, was having trouble distinguishing them.

This obstacle was one of many that his company, Standard AI, faced while retrofitting a Circle K convenience store in Tempe, Arizona, with computer vision software, which tracks every item that customers pick up so they can simply scan their app-enabled phone to pay as they leave, eliminating the checkout line. A network of more than 100 cameras can identify any of the thousands of similarly sized candy bars or beverages grabbed by customers, including cans of Red Bull, now identifiable thanks to a combination of geometric projections and higher-resolution cameras.

This tracking of consumer activity within the store — where shoppers look and linger, with cameras capturing their interactions and their near-misses — is part of a growing effort to use data collection to make commercial real estate more efficient.

“Checkout is kind of the killer app, but that’s just the tip of the iceberg,” said Fisher, CEO of Standard AI, which hones camera accuracy in high-volume, high-density environments. “You have a system that understands where people are in real-time, down to the centimetre. It’s all about utilisation of real estate.”

From the invasion of big-box stores to the ascendancy of e-commerce and, most recently, pandemic lockdowns, physical retail may seem stuck in perpetual crisis. But in-person shopping is still very popular and the subject of significant investment. (Retail tech investment hit a record $31.5 billion in the second quarter this year.) Amazon has spent generously on physical retail, including $13.4 billion on the acquisition of Whole Foods, and the development of its Just Walk Out system, which kick-started a race for cashier-less checkout among grocery stores and retailers.

The added layers of technology in stores and entertainment venues — crowd-tracking cameras, information gleaned from smartphones, tallies of neighbourhood foot traffic and sophisticated demographic data — aim to replicate the data measurement and analysis of the online experience.

But privacy advocates are sounding the alarm about the technology as Big Tech is under increased scrutiny. Congressional testimony from the Facebook whistleblower, Frances Haugen, in October has intensified calls for new regulations to rein in Silicon Valley giants.

Complicating efforts to address privacy concerns is a lack of regulatory clarity. Without an overarching federal privacy law or even a shared definition of personal data, retailers must sort through layers of state and municipal rules, such as California’s Consumer Privacy Act, said Gary Kibel, a partner at law firm Davis+Gilbert who specializes in retail privacy.

Technology companies counter the pushback by noting that their systems are designed to limit what they collect and anonymize the rest. For instance, Standard AI’s system does not capture faces, so they cannot be analyzed with facial recognition technology.

The growing volume of data on consumer and crowd behaviour is having significant implications on real estate design. It is making even physical space more interactive for marketers.

WaitTime, an artificial intelligence crowd-counting startup backed by Cisco Systems, is used by venues such as Dodger Stadium and the Melbourne Cricket Ground in Australia. At the FTX Arena, where the Miami Heat play, digital messaging on concourse entrances powered by WaitTime tells fans not just where to find food and drinks but the length of the lines.

In today’s market, “data eliminates the risk,” said Ken Martin, executive director of global sales at Cisco, adding that crowd-tracking technology could guarantee a high return on investment.

The increased use of crowd-counting technology is part of a wave of changes that industry experts say sports and other entertainment venues will use to improve security and crowd flow and allow mobile and contactless ordering.

Proponents argue that data can make a difference in decision-making by streamlining the leasing and scouting of new locations. Detailed information about how customers use parking or specific stores helps landlords and property owners better curate their malls and shopping centres.

“It’s not that the data is so out of touch with intuition. It’s that the data is real and gives brands the extra push they need to open a store,” said Adam Henick, a founder of Current Real Estate Advisors, which focuses on social media and data analysis.

He compared the adoption of data in real estate to MLB’s recent embrace of more aggressive defensive alignments, using statistical analysis to shift fielders for every batter. It is the same game but played with much more strategy and certainty.

Brokers can more easily winnow potential locations to a handful of spots based on local demographics and the mix of nearby stores, said Ethan Chernofsky, vice president of marketing at Placer.ai, which provides location intelligence and demographic data for retailers.

“Now you truly understand the demographics that come to a location, actual foot traffic, the value of co-tenants and their traffic, a far richer understanding of a location,” said Kevin Campos, who runs the retail technology fund at venture capital firm Fifth Wall. “It’s a more informed conversation between a landlord and a potential tenant.”

Placer has roughly 800 customers in commercial real estate and retail, including top brokerages and developers such as Tishman Speyer and Marcus & Millichap. The Placer data has been a go-to tool for measuring returning shoppers this year, offering week-old insights where earlier methods would lag behind three or four months, said James Cook, director of retail research for the Americas at JLL, a commercial real estate brokerage.

The growth of data mining has attracted more entrepreneurs, who are eager to create a more data-informed experience for retail brands.

Leap, a New York startup, operates boutique stores in several states for small, often digitally native, direct-to-consumer brands, handling their real estate, design work and even data analysis, said Amish Tolia, a co-CEO of Leap. For example, Goodlife Clothing, an online retailer, hired Leap to operate its two Manhattan locations.

“I look at this business in a digital way, and they look at it the same way,” said Andrew Codispoti, Goodlife’s co-founder and co-CEO. “They’re becoming experts in more and more places around the country, where to grow, based on your data as a brand.”

The option to open a turnkey location is a big selling point, but Leap also amalgamates shopping patterns — including local e-commerce sales, foot traffic and neighbourhood demographics — across all of its locations. This allows it to pick ideal tenants and even tell them the most profitable merchandise to display.

“Leap is effectively going to own a data set nationally that’s truly meaningful to retailers and to real estate owners,” said Henick of Current Advisors, which has helped Leap find Manhattan locations for retailers. “It can give brands comfort with their success rate in a given location.”