SAN FRANCISCO — Real-time data of human behavior is an increasingly valuable resource real estate professionals should take advantage of, according to panelists at the Real Estate Connect conference in San Francisco.
The ability to track consumer habits both online and offline keeps advancing with technology — a boon to marketers who want to find and engage with a target audience.
“You’ve got to embrace it because it’s not going anywhere,” said Jed Katz, managing director of Javelin Venture Partners. “The concept of putting the right ad on the right device for the right person in a way that’s not creepy” is more and more important, Katz said.
Michael Chui, a principal at McKinsey Global Institute, noted that since the advent of the multiple listing service, data has continued to increase at an exponential rate.
“We’re seeing a diversity of sources of data: social media, all kinds of sensors out there. (And of an) increasingly real-time nature,” Chui said. Data is also being used in new ways, particularly for marketing and forecasting or “now-casting” purposes, he said.
Companies that can make large, real-time datasets useful “are going to be very valuable,” Katz said.
“There’s more data being collected across the board right now every year than the previous million years of human existence. But you have to analyze and store that.”
Katz noted that predictive marketing company SmartZip, where he serves as a board member, can use homeowner data to decipher who might be ready to sell — sometimes even before homeowners themselves know.
“It’s been working phenomenally well,” he said.
Jason Sosa, founder of New York City startup Immersive Labs, described how his company’s face detection technology is bridging the gap between the offline and online worlds.
Ninety percent of purchases still happen in the physical world, which makes gathering real-time data on consumer demographics, interest and traffic very difficult, Sosa said. Marketers have previously been limited to lagging census data or research surveys. But in the future, gathering information will be as easy in the physical world as on a website, he said.
“What if it wasn’t so difficult to get this kind of data? What if it wasn’t a snapshot in time but more like a moving picture?” he said.
“We taught a machine, a computer, how to sense and understand our world. Her name is CARA.”
CARA detects a person’s gender and age, how long a particular ad held his or her attention, and the number of glances a person made toward the ad. CARA also detects foot traffic, how long people wait in line and where they gather at a particular venue.
“What was once science fiction is now reality,” Sosa said.
He was quick to emphasize, however, that CARA was not face recognition software, but rather face detection software.
“We are respectful of privacy. There’s no personally identifiable information associated with the data we’re collecting” and CARA does not record images, Sosa said.
What can real estate professionals do to gather their own big data? Panelist Glenn Kelman, president and CEO of Seattle-based online brokerage Redfin, suggested agents and brokers start out by pursuing the answer to one fundamental question: Which customers close and which customers don’t?
“What’s unique about Redfin is that we have a website and we have a brokerage and we try to be data driven on both. We have systematically studied the attributes of a user … that is going to become a profitable customer,” Kelman said.
For each person that contacts an agent through Redfin, the company measures if they closed, what homes he or she looked at, and other behavior. To obtain demographics data not provided by users, the company sends their list of registered users to a third-party company.
“It’s about taking data from different sources and marrying them together. Your data is worth a lot more if you can marry it to someone else’s data,” said Jed Kolko, chief economist for real estate search and marketing site Trulia.
While real estate agents and brokers may already have an idea of what those “closing customer” attributes are, analytics can help them either support or refute those hypotheses, panelists said.
“We are human and we are often wrong. It’s a competitive disadvantage not to look at the data,” Chui said.