Technology has dramatically reshaped the way that customers and agents alike experience the process of buying or selling a home. The internet, mobile devices and digital photo media tools have all been prominent parts of this revolutionary shift.
The tech landscape is experiencing another transition as big data takes on a more prominent role in how agents can approach real estate in whatever corner of the market they inhabit.
What is predictive analytics, anyway?
Many agents and brokers are already analyzing big data to determine homebuyer patterns and behaviors. It’s a wave that Remine founder and CEO Leo Pareja saw coming when he founded the company in Northern Virginia, near Washington, D.C. After creating some software for his own real estate business with Keller Williams to make it easier to access the data that’s available to agents, Pareja saw further potential in a new way to crunch numbers.
“Predictive analytics is one subset of the byproduct of being able to harness big data,” Pareja said. “What that means to me is taking lots of different things and making it easy to gain insight from them. Instead of having to go to my MLS system and then a public record system and or my county website, I can actually see it all compiled in one place.”
For many years now, big data and traditional analysis tools have helped agents determine when a neighborhood started becoming more desirable, pointing to factors that might have driven the shift: improved amenities, new businesses or an influx of homebuyers belonging to a particular demographic. In this way, past data gives insights into what homebuyers might be looking for and the types of areas that are likely to attract their attention.
“You first have to have a view of everything that’s going on. Once you have that, you then you add the intelligence,” said Keller Williams Chief Product Officer Neil Dholakia. “Now we want to take it a step further with our agents and give them an unfair advantage by having artificial intelligence that makes them more effective.”
Rather than determining what caused an area to change, predictive analytics tools apply data from the past and the present to develop a picture of what future real estate activity in an area might look like. Predictive analytics tools can take information like existing data, trends and predictions and turn that data into a visual representation of what an area might look like as it changes over several years. Prices, density and the ratio of renters to non-renters are among the factors that might be determined. Ultimately, it can all be marshaled in the service of helping agents target potential clients more accurately, helping them cut back on time wasted chasing leads that aren’t likely to go anywhere.
Analytics tools used by social media companies such as Facebook are already sophisticated enough to send users targeted ads based on their likes, posts and browsing habits while they’re connected. Likewise, Amazon turns searches into opportunities to put products in front of online shoppers. That doesn’t mean that real estate agents are in danger of being replaced by AI systems and predictive analytics algorithms.
Predicting where leads will come from
Mark Dimas, broker-owner of Mark Dimas Properties, sees predictive analytics tools as providing numerous ways of reaching out to potential clients who he might not have encountered otherwise.
“There are so many things you can do with it,” Dimas said. “It’s like drilling down and and the better the platform is, the more accurate their data, whether it’s mortgage information, flood information, what their equity is and contact information. That’s key. You can you can change the game. You can door knock without door knocking.”
SmartZip president and CEO Avi Gupta helped found the company in 2008 to provide tangible data to agents. The company’s offerings include SmartTargeting, which uses data to identify homeowners who may be considering selling. Contrary to what some might think, this technology augments, rather than replaces, the human beings that make real estate transactions happen.
“When you’re talking about sellers, they do not find their agent on the web,” Gupta said. “They go through different relationships. It’s people they have worked with before. What this allows these agents to do is get in front of those sellers before they’ve already made up their mind. Otherwise, if they just wait for sellers to call them, it will never happen. By being proactive and preemptive, they can actually get in front of people who are most likely to sell and be one of the first or second agents to be interviewed when the seller is ready to list their home. Most sellers will choose the first or second agent they interview. As an real estate professional, if you’re not the first or second agent, then your chances are pretty slim.”
It’s not as though predictive analytics is something that’s completely new to users. Many people use the technology every day without noticing. They use Google Maps to figure out the best way to get to their destination, or Amazon suggestions to guide their shopping. “It allows an agent to understand who is three or four times more likely to sell than others,” Gupta said. “That allows them to focus their marketing, their prospecting and their time and energy on a small subset of people as opposed to mass marketing to everybody. But at the end of the day, the agent still has to build relationships with those people.”
Understanding the advantage
Many real estate professionals are prepared to embrace predictive analytics. A 2017 survey from Imprev Thought Leadership on what real estate tools will look like in 2022 revealed that two-thirds of real estate executives surveyed prefer predictive analytics, big data and marketing automation as potential investments over augmented or virtual reality and artificial intelligence applications. Predictive analytics was rated the best technology for real estate brokerages by 74 percent of executives surveyed. They based their conclusions on the technology’s ability to perform analytical tasks on targeted markets.
“We have a tremendous amount of data exhaust that that our agents produce just in their day-to-day activities,” Dholakia said. “That exhaust can fall on the floor and just blow away in the wind. Or if they’re using our tools, we can capture that exhaust and make some meaning out of it for them. And so that’s really our challenge. A gap we need to fill is working with our agents to understand the advantages of using the systems that we’re providing to them so that they generate the data to their benefit.” By finding novel ways to use data that’s already broadly available, these companies can help agents become more efficient in their outreach efforts and in their marketing spending. Instead of using a scattered, catch-all approach, they can home in on the types of clients who are looking for homes in the areas where those agents typically work.
Dimas uses Remine in his business to find potential clients because he finds it effective in narrowing his marketing campaigns when he’s farming neighborhoods. He looks for platforms that are easy to use, offer the data that he needs and have a track record of making changes and adapting to enhance the user experience. “If I can drill down and just look at people who are in this specific neighborhood that have owned their home from 15 years to five years and still live in the home so they’re owner-occupied and they have at least $20,000 worth of equity or $30,000 with the equity based on their mortgages, then I could target to those people,” Dimas said. That kind of data-mining capability isn’t always available out-of-the-box. Remine, for example, uses a process of incorporating user feedback to add new types of information that its software can mine, sort and represent on a map.
Remembering what it’s really all about
It all ultimately goes back to the agent. That’s who can drill deeply into data to uncover patterns of consumer behavior that can be helpful to them in their business. Agents are needed to help people navigate the emotional experience of the purchase, according to Dimas.
“Most people who buy homes are buying them for the American dream,” Dimas said. “They’re buying because they want to build memories and they want to have something that they can call theirs. There’s more to it than just the real estate and you need a professional who’s going to help you through that.”
Pareja agrees that developing relationships and having those face-to-face interactions will remain the most significant means of agents finding new clients.
“I don’t think technology will ever replace the real estate agent, at least in my lifespan,” Pareja said. “I do think that the agents who adopt tools and technology will 100 percent replace agents who don’t. They’re just a tool. Just because you purchase one of these tools or your MLS buys it for you or whatever, you still have to work. You still have to make the phone calls, go to the meetings, do the mailers and all the activities that are required by your profession. We’re just trying to give you an edge.”