Knowing future market trends is a big plus for real estate agents. Predictive analytics provides that competitive edge.
Key Takeaways:
• Predictive analytics is the process of using big data to gain insight into what is likely to happen based on past events.
• Real estate agents and investors can use predictive analytics to determine housing trends, forecast pricing, and assess big-picture value.
Big data and business intelligence have made it possible to take the heaps of scattered computerized information gathered from industries, businesses, social networking, and more and use it in a meaningful way to predict future trends. It’s called predictive analytics. And the concept is being used in real estate to predict trends, which, when applied, should lead to better real estate investment decisions.
Big data’s big picture
Predictive analytics is a fancy term for leveraging available data so that individuals or groups (real estate agents, brokerages, and the industry as a whole, for example) can use the information to gain insight into what is likely to happen based on past events. “Likely” is an important word in this instance, as predictive analytics is not about absolutes, but rather about probabilities, according to an article by Rob Marvin on PCMag.com.
In essence, predictive analytics is computers learning from past behavior and enabling data users to do certain business processes better, according to PCMag.com.
One of the ways predictive analytics can be used is for data mining, which involves studying big sets of data to uncover behavioral and other patterns and discover new information. Predictive analytics also allows for what’s called machine learning, which drills down into the data to reveal what’s most important—the “gold data nuggets,” Marvin wrote.
Predictive analytics is not about absolutes, but rather about probabilities.
Predictive analytics uncovers patterns that are not easily seen by humans and reveals reliable forecasts, which take into account the “what-if” possibilities, according to an article on the use of predictive analytics in real estate investing by Peter Abualzolof on MashVisor.com. It’s a step ahead of traditional analytics, in which big data is collected and studied to provide a picture of what happened in the past, according to Abualzolof. Today’s big data and predictive analytics provide a big-picture view, he wrote.
Predictive analytics: Possibilities in real estate
Making sense of local real estate markets can be a complicated task because real estate is constantly changing. Predictive analytics takes what has been known to occur and the potential for market volatility to paint a picture of what’s ahead for the industry and for a particular neighborhood.
There are tools that help to pool and analyze the data. Agents, for example, might find available analytics tools like MashVisor can shed light on the decision-making process about whether to invest in properties or not. If they’re assisting buyers, sellers or interested in investing in real estate themselves, agents can use MashVisor’s analysis of big data to assess conditions in the housing market and forecast pricing, as well as predict risk, demographic shifts and other market changes in neighborhoods throughout America, Abualzolof wrote.
The result is investors feel like they’re going into real estate investments with their eyes wide open — with a sense of what is likely to happen and what to expect with the properties they buy. This, and other predictive analytics tools, helps investors to assess investments for timing, location, and big-picture value, according to Abualzolof.
Agents and investors can use predictive analytics to more effectively manage rental properties, so clients earn higher returns on their investments.
Agents and investors can use predictive analytics to more effectively manage rental properties, so clients earn higher returns on their investments. Abualzolof cited the business intelligence capabilities on MashVisor’s Airbnb Pricing and Occupancy Insights, which forecasts important variables needed to enhance future occupancy rates. It also helps analyze where and how buyers can get the highest return on properties, including such things as whether a buyer in a specific market is better off investing in a one-, two- or three-bedroom home, based on likely renter profiles —whether they’re singles, couples or families.
The information helps not only with the ignition decision to purchase a rental property but with focusing on targeted marketing efforts to those future tenants, according to Abualzolof.
Another option in the real estate predictive analytics’ space is CoreLogic, a property information, analytics, and data-enabled solutions provider. CoreLogic offers home price index tools and an analytics suite that aggregates public records, mortgage performance, valuation, MLS and pricing data to forecast home prices up to three decades and more information for real estate agents, mortgage professionals, and others.
These are just a couple of tools for using available data to the real estate agent’s advantage. Many others are industry-specific and more general. It’s best to do your research on whether a particular tool fits your needs and if using the data makes sense for your real estate business.
What it all means
Essentially, predictive analytics turns big data into real and usable information that can give real estate agents a competitive edge. Armed with predictive analytics and knowledge of how best to use the information, agents can filter information to fit clients’ needs and provide a value-added service by helping clients get the most bang for their real estate bucks.
