Marketing

Predictive analytics breathe new life into direct mail marketing

Whittling down to specific house-hunting clients could keep marketing strategy alive

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Marketing is one of the biggest expenses for successful real estate agents. Digital marketing has become a cornerstone of every agent’s marketing strategy, and when you consider the cost effectiveness, it’s easy to see why.

Real estate agents using direct mail marketing campaigns in a ZIP code with 5,000 homes can spend anywhere from $2,500 to $10,000 every month to reach those residents. Unfortunately, most of that money is spent reaching homeowners who are not currently trying to buy a new home or sell their existing one.

With Google AdWords, Zillow and other digital marketing platforms, agents can spend their marketing dollars to target people who they know are looking to buy or sell property. Targeting a single ZIP code with Google or Zillow, you can advertise to most potential homebuyers for around $500 to $1,000 a month.

According to the National Association of Realtors, 92 percent of homebuyers in 2014 used the Internet in some way during their home search process. Clearly, the reach and efficiency of targeted digital marketing for agents is undeniable.

So what about direct mail marketing? Should agents be abandoning a proven marketing strategy that has worked for decades?

No, certainly not. Event-driven marketing and predictive analytics can lower costs and increase effectiveness for direct mail marketing, which makes it a viable option, even in the digital age.

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The reasons that direct mail worked in the past still applies today — it’s just that there is a more effective and efficient way to do it with precision. Why spend thousands of dollars to reach 5,000 people when the data shows that, at most, only a few hundred of those people will be buying or selling a home this year?

By taking advantage of predictive marketing, it is possible to pinpoint homeowners who have a high probability of selling their home or buying a new one. By targeting the 20 percent of homeowners with the highest probability of selling or buying, you can save thousands on a direct mail campaign.

Companies including SmartZip and RealAgile gather data from many sources, both public and private, that give them the ability to predict who is going to buy and sell. Individual data points, such as occupation, income, marital status and age, might not tell you much about the probability that someone will be buying a new home, but when you combine these data points together to get a sense of the bigger picture, suddenly the ability to predict potential homebuyers becomes increasingly accurate.

For example, if I know that an individual recently got married and had a child, the probability that they will be looking to buy a home goes up. If, in addition, I know that this person just turned 33, is currently renting a small one-bedroom apartment and recently got a new job with a significant increase in pay, there is a very high probability that they will be looking to buy a new home. This example is oversimplified, but, in essence, this is how predictive analytics works.

By comparing people who have bought or sold homes in the past on a large number of variables, we can predict with a high degree of accuracy who will likely buy or sell homes in the future.

SmartZip, an industry leader in real estate analytics, runs hundreds of models against thousands of variables to find the best model fit for each market, increasing their predictive ability. They boast 1.3 million gigabytes of data on over 95 million homes, with the goal of making big data work for you.

RealAgile takes a similar approach by using large amounts of data to construct models that predict the likelihood that a homeowner is ready to move. According to RealAgile, it calculates a MoveScore for each home in your specified territory. For the top 20 percent of ranked homes, the MoveScore has predicted 40 percent or more of sales within the following year.

ReboGateway focuses more on event-driven marketing opportunities by providing data about legal filings, distressed homeowners and tax defaults. When homeowners encounter circumstances that are often precursors for selling their home, there is an increased likelihood that they need the services of a real estate agent.

In the ever-changing landscape of online marketing, one thing is certain: as data becomes more and more openly available, predictive analytics will become more powerful, commonplace and increasingly accurate. Real estate agents and brokers need to be taking a close look at this new class of targeted marketing to achieve the most cost-effective results. Whether you are a cash-strapped agent on a budget or a large brokerage firm with ample marketing dollars, getting the most out of your marketing spend always makes sense.

Rick is the senior content manager with MadValorem. MadValorem provides high-end real estate technology tools to consumers and agents. Rick received his master’s degree from Florida Atlantic University where he studied advanced statistical methods and behavior. He also worked as a writing consultant advising graduate students on academic writing.

Email Rick Frascona.