Real estate business

How to Use Predictive Analytics in Your Real Estate Business

Editor’s Note: This was originally posted on RISMedia’s blog, Housecall. See what else is cooking now at

In this second article in a three-part series, learn how real estate agents can use predictive analytics to drive positive change and prediction in their business.

You’re always looking for ways to show your value and stay ahead of the market. One way to do this is to use predictive analytics.

As we explained in a previous article, predictive analytics is not new, but real estate professionals have been slow to adopt it, according to experts. With so much relevant data at your fingertips, from consumer demographics to housing trends to historical property prices, predictive analytics gives you an edge in a competitive landscape. Here are some specific ways to use it in your real estate business.

Give buyers and sellers more confidence
The most relevant way for agents to use predictive analytics is to target the right customers for their marketing efforts to find the right types of buyers for specific listings. This allows you to focus on your strengths: negotiating and nurturing relationships.

Rudy Pierre has been using HouseCanary for about a year. The realtor at YellowBrick Real Estate in Stamford, Conn., says it uses predictive home price forecasts to give buyers greater confidence in their investments. The data helps protect his logic when suggesting a listing price that sellers might disagree with, he adds.

When you can identify where the most up-to-date comparables are, which direction prices are moving, and show the numbers to sellers, Pierre says, “It’s hard for sellers to chat with you…I’ve seen an increase ads because I’m showing them something no one else is.

Gone are the days of agents driving buyers on viewings to point out a home’s features; buyers can find most of these details online. However, when you share predictive data reports with them, you add value to their lives, says Stan Humphries, director of analytics and chief economist at Zillow Group.

Agents who use predictive analytics in their businesses make an instant impression on potential customers, he adds.

“The difference between a mediocre agent and a great agent is amplified by technology, as you leverage tools that have more impact,” says Humphries. “Great agents use technology to move the needle.”

Find motivated owners to sell
Jay Macklin loves what predictive analytics brings to his business. RE/MAX broker/owner Platinum Living in Scottsdale, Arizona uses SmartZip analysis to target homeowners who may be more likely to sell their home.

The service pulls data from the U.S. Census to track seller lifecycles based on public records, such as divorces, deaths, and marriages, Macklin says. From there, the algorithms can predict a certain percentage of homeowners who are most likely to sell their home, so agents can call them (using proprietary scripts) to gauge their timing and seriousness.

“A lot of agents will hear from people who want to know what their home is worth, but it doesn’t tell them if someone is ready to sell their home,” Macklin says, adding that agents can better “massulate the message” into their marketing campaigns. .

Another smart use of predictive data: matching rushed sellers whose homes aren’t on the market (yet) with the right buyers who are ready to make offers, similar to classified ads. This strategy can also be applied to expired and canceled listings, and FSBOs, Macklin says.

Worth the investment
Predictive analytics program costs can vary depending on how much (or how little) data you request and whether or not you are requesting proprietary algorithms for your specific market needs. Macklin says his agents close an average of 10 deals a year using predictive analytics. With an average selling price of $425,000 to $450,000 in the affluent Scottsdale market, that’s significant commissions, he says.

Peter accepts. The time he saves through predictive analytics more than pays off because he can spend more time with clients and negotiating deals, he says.

“Before, I had to manually pull properties from the MLS and spend most of the day before an appointment preparing a listing layout,” says Pierre. “Now I can do it in minutes and be out. It makes you look smarter than the average agent, and the time I save by using it is valuable. »

Stay tuned for the final part of our series, which will look at specific ways brokers can use predictive analytics to recruit and retain the best agents.

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