Marketing that targets homeowners statistically more likely to move soon could save you money
By Megan Craig
Targeted advertising is a well-known tactic for online shoppers: Search for specific keywords, and you’ll be bombarded with ads for similar items. So it is with home shopping.
According to a National Association of REALTORS® report, 95 percent of potential homebuyers reported using the internet when looking to buy or sell a home in 2016. Because of the large internet audience, agents can use services like Zillow Premier Agent to advertise to potential homebuyers in specific ZIP codes.
The ability to target those online home shoppers and potential sellers may make direct mail seem less useful, but agents want name recognition even before a person starts looking in earnest to buy or sell.
Unfortunately, an agent using the United States Postal Service to send a direct mail campaign could spend thousands of dollars every month to reach all the homes in a ZIP code, depending on the number of homes.
Enter the latest form of targeted advertising: Direct marketing filtered via predictive data analytics.
The What and How of Predictive Analytics
Although several levels of predictive analytics for real estate agents exist, it basically works like this:
Analytics companies gather data from several sources about potential homebuyers and sellers. The data collected includes ages of homeowners, turnover rates in a specific neighborhood or ZIP code, lifestyle events of public record, when a home was last sold and other factors known to play into making someone more or less likely to buy or sell a home.
The company then gives the agent in a certain area information on specifically who they should target with direct marketing materials, using a formula to determine the top
20 or 25 percent of people in the area who are likely to buy or sell in the near future. These lists are updated regularly.
“Real estate agents already target the market using intuitive predictive models,” says Joel Shapiro, a professor and executive director of the program on data analytics at Kellogg School of Management at Northwestern University. “They use their own knowledge and expertise to predict who is likely to buy a given listing. Since agents are already using these ‘intuitive’ predictive models, it absolutely makes sense to try to build more accurate predictions with more rigorous models. This may yield insights that intuition would miss.”
Some analytics companies also take it to the next level, not only providing predictive data for REALTORS®, but also following through with direct mail, email and social media campaigns (based on the data, of course) on behalf of the agent.
Once an agent signs on, “within the course of a week or two, this entire side of their business can be on autopilot,” says Mark Dickson, CEO and co-founder of predictive analytics and automated marketing company Offrs.com. “We can use all the marketing options—direct mail, voicemail, emails, texts, digital ads and even handwritten notes—all that’s out there to optimize the number of touches to ensure that particular agent is top of mind and the one who’s ultimately going to secure the business.”
Cost and Effectiveness
More than 25,000 agents use at least one of Offrs.com’s various platforms and products, Dickson says. But how many are using any of the many available analytics tools—and how well those tools work for the agents who do use them—isn’t known.
“Even for those agents who do it, there’s no guarantee that formal models will do a better job at prediction than good agents’ intuition,” Shapiro says.
Carl Medford, CRS, The Medford Team, sells in Fremont, California, and says he’s always looking for ways to build market share. His team tried using a predictive analytics company to aid his direct marketing for about a year, paying $12,000 for a geographic zone in which the team already had some market presence.
“While we had queries and responded appropriately and in a timely fashion, and consistently followed up, we did not see one single sale originate from ‘smart’ marketing in the year we tried the program,” Medford says. “Sometimes we can be too smart for our own good.”
Although he thinks he may have seen more success had he continued the program, he called the pricing “ridiculous” and was disappointed to find that many people who weren’t being targeted moved and most who were being targeted did not. He switched to a direct mailing company to mail to the entire area rather than the few chosen by predictive analytics.
But Terry Naber, CRS, with REMAX Properties, Inc. in Colorado Springs, Colorado, had the opposite experience with predictive analytics. In fact, in an area where she’d previously had no luck selling through traditional farming practices, Naber closed two sales this year. She also heard from one man who was so pleased she had reached out, he said he would use her as his agent whenever he was ready to sell some of his $2 million in rental properties.
“Predictive analytics give you an edge,” she says.
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Putting the Work In
Whether predictive analytics may help your marketing game depends on several factors, not least of which is how much effort you put into the process, says Terry Naber, CRS, an agent in Colorado Springs, Colorado.
Naber says she hasn’t perfected her follow-up system, leading to fewer sales than she could be generating thanks to the more targeted mailings offered through analytics.
“You still need that personal touch,” Naber says. “That is absolutely imperative because you can knock yourself out sending impressive pieces, but if you never get in touch with them to set yourself apart, they’re not necessarily going to use you.”
And decision-making about best marketing practices also can’t be outsourced.
Joel Shapiro, a professor and executive director of the program on data analytics at Kellogg School of Management at Northwestern University, warns agents to understand the limits of prediction.
“Predictions merely predict—they don’t tell you how best to allocate your marketing resources,” he says.
