Location data firm Placer.ai, which tracks where people shop, work, and live using their mobile phon
- Location data firm Placer.AI raised a $50 million Series B, after seeing huge increases in demand.
- The round was led by tech investor Josh Buckley and included proptech giants Fifth Wall.
- The company now provides services to hedge funds, as well as real estate companies and retailers.
Location data company Placer.ai announced today that it has raised a $50 million Series B round. The round was led by Josh Buckley, tech investor and CEO of Product Hunt, and included participation from largest proptech investor Fifth Wall, as well as previous investors JBV Capital and Aleph VC.
This round brings the total raised for the Bay Area- and Israel-based company to $66 million. The company declined to provide a valuation.
Placer uses mobile phone location data to provide a wide range of customers with information about foot traffic and migration patterns.
Location data is a key piece of the puzzle for forward-looking real estate firms, which are turning to data sets to make decisions about their portfolios. Traditionally, the data was used by retail landlords and retailers themselves to quantify their foot traffic and provide another metric than overall sales performance to understand how a location was doing.
But now, office managers could use location data to figure out how to structure a socially distant floor plan, while multifamily landlords might analyze it to figure out how to build rentals where Americans are moving.
The company launched its service in November 2019 and now has more than 500 customers, including commercial real estate services firm JLL, mall landlord Taubman, Dollar General, and Planet Fitness.
The company originally "braced for impact" when the pandemic hit, said Noam Ben-Zvi, Placer's CEO and cofounder. What does a location-based data firm do when people aren't leaving their homes? For one thing, it is able to track which retailers they do choose to leave the house for as soon as restrictions lifted.
"The data probably tells the story that many historians will know anyway," Ben-Zvi said. "Humans are very resilient, and they love leaving the house."
The team actually tripled its customer base and revenue during 2020, Ben-Zvi added. This led the company to raise a convertible note to meet rising demand, double its engineering team to 50 people, and offer webinars and free data tools on its website that showcased many parts of the pandemic's impact.
While some customers did have to scale back their budgets and stop paying for Placer, others looked to the startup's data as a way to gain a competitive edge.
"If a commercial real estate company is doing really well and has all of its spaces leased out for the next five to 10 years, they don't really need our data," Ben-Zvi said. "They don't need our data if there's no change or future uncertainty, but they do need it when there's a lot of turbulence."
Over the last year, Placer found its customer base expanded from retailers and their landlords to include more than 50 municipalities hungry for data on tourists and people looking to relocate to their area, hedge funds looking to predict company performance and beat earnings calls by following foot traffic, and consumer packaged goods manufacturers that wanted to learn more about the movements of their in-store customers.
The company's next step is to integrate more data into their product, said Ethan Chernofsky, Placer's vice president of marketing. The company began by offering "answers" to customer questions using mobile data, but can provide even more value by combining their data with other sources. The owner of several properties, for example, might wonder how the weather impacts foot traffic to different sites; it can purchase meteorological data from Placer's new marketplace and combine it with location-based tracking to analyze cause and effect.
"Mobile data is only an ingredient to that answer," Chernofsky said. "Different data sets — demographics, crime, weather, credit card purchases — could and should be layered on top of our data, and make for better answers."
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