> The Importance of Predictive Analytics for Real Estate Companies

Resource Center

The latest real estate crowdfunding news and resources

The Importance of Predictive Analytics for Real Estate Companies

Predictive Analytics in Real Estate

Crystal balls in fairy tales allow soothsayers to see the future. This valuable resource has been created in reality by complex mathematical formulas that use massive sets of data to predict the future. Real estate companies can use these predictive analytics, as they are called, to take lead generation and prospecting to the next level.

Predictive analytics evaluate and forecast market trends. They can be used to predict the behavior of any market, but are used primarily in macroeconomic forecasting. Expectations about production, inflation, and employment are all set to some extent by predictive analytics. In the real estate market, this capability is used to predict the value of real estate in a particular location.

Data companies offer a variety of products based on these calculations. These range from computer-generated appraisals for a particular address to a 30-year forecast for an entire area. Some of these models are used to comply with government regulations which require companies to evaluate the value of their portfolios under negative economic assumptions.

Predictive analytics involve the evaluation of large sets of data to identify patterns, and then the evaluation of those patterns based on some set of assumptions to project them into the future. This requires a significant amount of computational power and an equal amount of intellectual rigor.

Firms which build the systems to do this type of work are specialist in the field. CoreLogic is one of these specialists, but there are a variety of others that offer similar services. Housecanary is another example that offers their computational results to the real estate industry on a fee basis. Opendoor uses this type of data to purchase houses that it then resells on the market, offering sellers the benefit of a fast, easy sale.

Predictive analytics are useful for the uses already described, but they are not predictors of individual behavior. They cannot tell a real estate agent if a particular owner of a home will sell that property in the coming months. Nor can they predict if a prospective buyer will decide to buy a house they have seen, or what amount they will offer for a property.

In addition, no matter how robust the calculation, these algorithms cannot do what humans can do in understanding all aspects of value. They can replicate the math, but not the full range of intangibles that may contribute significantly to value. The simple fact is that market value is not always entirely rational, but computer calculations must be.

How Predictive Analytics Benefits People

Information on the value of real estate is useful to a variety of participants in the industry. Many would put real estate investors at the top of the list because quantitative analysis is the backbone of a well managed real estate portfolio. This characteristic is why banks and other lenders also value these services. Obviously, real estate appraisers can either authenticate or supplement their calculations with predictive analytics. 

But it is real estate agents and brokers who can derive the greatest value from these calculations. The use of quantitative calculations removes the significant element of guesswork that has always been part of a real estate transaction. It can give any potential buyer or seller greater confidence that the real estate agent is getting the fair market price for a particular property.

Join Now to Discover Real Estate Marketplace Lending

Real estate companies can use predictive analytics in a variety of ways. The most basic is simply to differentiate themselves in the market. Offering the prospective buyer a 10-year forecast on the value of a property under consideration can also move that transaction another step closer to closing. Keep in mind that the calculations are not being done by the agent. These are third-party firms used by others to satisfy federal regulations.

And although predictive analytics cannot tell which houses in a neighborhood will go up for sale, they can predict which neighborhoods will see the most transactions. This allows mass marketing to become targeted marketing. Bulk flyers can be sent to the zip codes most likely to see listing in the future, not those that have seen them in the past.

Share this post: