How big data and predictive analytics are helping Realtors® expand their businesses

For decades, county record reporters and tax assessors’ offices have kept troves of information on homes and homeowners, including selling price, mortgage loan records, occupancy, defaults, delinquencies and more. 

Intrepid Realtors® used individual data points, especially those related to FSBOs and expired listings, to land one-off listings. But the majority of the information was offline, so despite an overload of data, real estate practitioners had almost no way to use it.

WHAT IS PREDICTIVE ANALYTICS?
During the last 10 years, the algorithmic analysis of “big data” became the backbone of massive enterprises. Online retailers such as Amazon began analyzing past purchase patterns. Amazon is now rumored to get 30 percent of its sales through its data-backed “recommended for you” carousels. Facebook famously tweaks its algorithms to provide a desirable user experience that allows for ads and other revenue-building activity.

HOW DOES PREDICTIVE ANALYTICS FOR REAL ESTATE WORK?
The offline records from assessors’ offices are not user-friendly, but they hold much of the big data of the American residential real estate industry. Now that most of these files have been transcribed into online records, organizations like the National Association of Realtors® and data-crunching companies are working to normalize the data and provide actionable insights for real estate professionals. 

Within the real estate industry, predictive analytics can be used to analyze seller patterns and to predict the homeowners who are most likely to sell in hyperlocal neighborhoods. From there, the real estate professionals who use a predictive marketing solution can deploy highly targeted marketing campaigns to their top prospects. The end goal, of course, is for Realtors® to optimize their time and efforts by focusing on a smaller group that is more likely to transact. And when the time comes for those homeowners to sell, the proactive agent will be top of mind. 

IDENTIFYING POTENTIAL SELLERS
Predictive analytics companies sell hyperlocal territories to their clients, because selling patterns change from one block to the next. Clients can test different territories to find the neighborhood with the highest commission and/or turnover. 

Such platforms also rank each homeowner within the territory by likelihood to sell in the next 12 months, so Realtors® can target market and follow up with their top prospects. 

“We are in a high rent area and local executives and lawyers get a lot of junk in the mail. So we are mailing to data-identified possible sale candidates once every two months and then following up with online ads and retargeting. From these efforts, I usually get 10-15 responses each month, and I follow up personally with a video introduction to get the ball rolling,” explains Karen Close, a Century 21 real estate agent in Arlington, Virginia, who uses a predictive analytics platform to land listings.

GETTING THE LISTING
Most agents have a tried-and-true listing appointment strategy. However, many agents also use the various insights found on their big data platform’s dashboard such as equity, home price appreciation and neighborhood selling trends —  to forge in-person discussions with their top targets. 
In other cases, the connection has already been made through marketing mailers. 

“One local veteran was given three referrals through the USAA process, and my name wasn’t on the list. I’d been mailing to him for some time because he was identified as one of my top selling prospects, and he knew my name as a result. Rather than work with one of the referred agents, he followed up to see if I qualified, and I got the listing. To me that was proof that the marketing was hitting the right people and making an impact.” said Karen.

PLAYING THE LONG GAME
Just as Amazon needed to earn the trust of American consumers, so, too do the Realtors® using data-backed farming. For predictive analytics clients such as Close, that means using a platform that identifies top sales candidates, and then using natural relationship building techniques like door knocking or personal phone calls. 

Think of it this way: big data and predictive analytics get agents to the front doors of the homeowners most likely to list. Agents can use additional insights and their own savvy to get to the kitchen table for a listing appointment.

Avi Gupta is the president and CEO at SmartZip, a Bay Area data and predictive analytics company currently focused on the real estate industry.