In this first article of a three-part series, learn all about predictive analytics and how it works for real estate. In future stories, we’ll examine how brokerage owners and agents use predictive analytics in their businesses.
By Deborah Kearns
Real estate brokerage owners and agents would likely agree they want to better target their marketing dollars and efforts with laser-precision focus. Who can blame them?
Imagine whittling consumer data down to a handful of demographic categories so you can not only reach the people who are most likely to buy your listings, but also fine-tune your messaging to prospective sellers in the neighborhoods you want new business. Imagine how sellers will react to being able to see your marketing efforts in real time.
What is predictive analytics?
Generally speaking, predictive analytics is a way to forecast future trends and results by analyzing historical data with statistical algorithms and machine learning methodologies. While predictive analytics isn’t a new concept, technology has made its accessibility and presentation much more attractive to business leaders who are under pressure to market and promote their products and services with more precision.
In other words, predictive analytics takes what we know about past behaviors to make informed and quantifiable forecasts on what will happen in the future, according to the SAS Institute. And it starts with having a problem to solve.
For example, predictive analytics models help retailers pinpoint marketing strategies and consumer messaging based on past consumer behavior so they can drive more engagement or sales. This is especially helpful for brick-and-mortar shops who are struggling to survive and compete with online sales mammoths like Amazon.
According to the SAS Institute, there are two types of predictive models: classification and regression models. Classification models are used to categorize people into class memberships while regression models predict numbers such as revenue or length of time a service or good will be effective.
How it benefits real estate agents
Predictive analytics isn’t a fly-by-night fad or applicable to data enthusiasts only; it can help you set yourself apart from competitors—and make you a trusted adviser to consumers. Having this type of tool in your arsenal is critical as more consumers, many of whom are savvier and more adept at online research, might question your value in the transaction, says Martin Morzynski, chief marketing officer with HouseCanary, a real estate data analytics firm based in San Francisco.
“Really, [predictive analytics] helps agents get better at their jobs, because consumers’ expectations and questions are getting more precise,” Morzynski says. “It brings a level of accuracy and granularity into the process that changes the game.”
Predictive analytics helps you show consumers future price projections for specific properties and neighborhoods. It can also match buyers to specific listings and help you zero in on homeowners who are most likely to sell their homes.
Stay tuned for our next article in the series, which will examine specific ways real estate professionals can use predictive analytics in their business.
