Skip to main content
Business Observer Friday, Jan. 22, 2016 6 years ago

Neighborhood watch

A real estate data firm targets a unique segment: Pinpoint predictions into who will sell a home before it hits the market.
by: Beth Luberecki Contributing Writer

Mark Dickson thinks he's gotten pretty close to predicting the future — at least in the world of residential real estate.

As founder and CEO of Sarasota-based, he runs a startup that can tell Realtors which homes in a specific territory are most likely to be listed for sale in the next year. With that information, Realtors and brokers can then concentrate their marketing efforts on the most receptive targets.

“Big data and predictive analytics are really the future of marketing in every industry,” says Dickson, a former commercial real estate broker in Jacksonville and Washington, D.C. “We're able to create custom audiences using our predictive analytics so that Realtors can advertise only to the people we believe are most likely to sell their home in the next 12 months.”

The company began in a garage in Dickson's Lakewood Ranch home in January 2015. It started with a focus on Florida and Washington, D.C., and now it's now expanded to 42 states and works with some 2,000 Realtors at firms such as Keller Williams, Sotheby's International Realty and Coldwell Banker. (Dickson declines to provide any sales/revenue figures.)

“And we're continuing to grow significantly,” says Dickson. “By the end of 2016, we'd like to have full national coverage.”

To get there, plans to add 10 employees to its current Sarasota staff of 20, and increase its number of field-based sales reps from 20 to 60.

The company's forward-looking information comes from an algorithm that leverages property and consumer data. Dickson developed the initial basis of that formula with the help of business partner Rich Swier, co-founder of Sarasota co-work space and business incubator the HuB, where is headquartered. The pair then worked with Ph.D.s in statistical analysis to refine the algorithm and take the most scientific approach possible in identifying the properties most likely to be put on the market.

The algorithm looks at dozens of variables that can impact home sales. That's everything from loan-to-value ratios and age of the youngest child in the household to how long people tend to own homes in a specific neighborhood. Properties are given a score from zero to 100, and those with ratings over 70 are considered prime targets.

“At that point, we would recommend the Realtor reach out to them on a monthly basis,” says Dickson. “And ultimately if that person is going to list their house, we've given the Realtor we work with a competitive advantage to be the first one in the door to secure the listing before anyone else.”

The company works with just one Realtor per territory, and the average monthly fee for access to the predictive data for a territory is $225. Realtors can then use that data on their own or work with (for additional à la carte fees) on a targeted marketing campaign using platforms such as social media, email marketing, and direct mail.

According to Dickson, has predicted some 70% of the homes sold in the last year. Putting that kind of data in the hands of Realtors helps them be more efficient with their time and money. “That's really important for people who are trying to build their business,” he says. “If they can reduce waste and reinvest that money into something else or spend that time on developing additional business, then it's a highly effective tool for them.”

Related Stories