Technology has dramatically reshaped the way that customers and agents alike experience the process of buying or selling property. The internet, smart phones, mobile devices and digital photo and video tools have all been prominent parts of this revolutionary shift.
But the tech landscape is experiencing another transition as big data takes on a more significant role in how real estate professionals approach the housing market in their area. Many agents and brokers are already using predictive analytics to determine homebuyer patterns and behaviors, and the trend lines point to more adoption of this technology as it matures.
Predictive analytics and real estate
Remine founder and CEO Leo Pareja started his predictive analytics company after creating software to make it easier for agents to access data available in his own real estate business.
“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, a public record system and my county website, I can actually see it all compiled in one place.”
Remine, based just outside of Washington, D.C., gathers data and makes it easier for agents to use it in their everyday business. Alix Nadi of the Alix Nadi Team with RE/MAX Around Atlanta is one of the many agents who have access to the system through their MLSs, more than two dozen of which have partnered with Remine. “It allows you to go in and upload your contacts,” Nadi said. “It will track them, and it does a cool algorithm. It looks at how they’ve lived in this house for X number of years, this is how much of their mortgage they’ve paid off and this is how old they are.”
To the initiated, these might seem like mundane facts. But for real estate professionals, having all this data in one place is golden. “Based on these factors, it lets us predict whether they are hot, warm or cold as far as potentially moving,” Nadi said. “It can help identify people in general who might be looking to make a move now.”
Predicting where leads will come from
Agents can use big data to extract a broad range of useful information, but perhaps the most developed form of use is in helping them zero in on clients who might be preparing for a purchase. This translates directly to their marketing plans, assisting agents to target potential clients more accurately.
SmartZip is another company that’s been in this business for a few years. The company’s president and CEO, Avi Gupta, helped found SmartZip in 2008 with the goal of providing tangible data solutions to agents using predictive analytics. SmartZip’s offerings include SmartTargeting, which uses data to identify homeowners who may be considering selling.
Gupta noted that this is a particularly important group to target.
“When you’re talking about sellers, they do not find their real estate agent on the web,” Gupta said. “They go through different relationships… 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 minds. Otherwise, if they just wait for sellers to call them, it will never happen.”
Real estate agents and brokers could crunch these numbers themselves, but as Gupta noted, time is really of the essence when it comes to winning listings.
“Most sellers will choose the first or second agent they interview. As a real estate professional, if you’re not the first or second agent, then your chances are pretty slim,” Gupta said. “By being proactive and preemptive, agents can actually get in front of people that 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.”
Nadi sees value in the fact that predictive analytics can reduce the time she spends following up on leads that might not pan out. “Don’t get me wrong, there are big teams out there that absolutely spend their time and money chasing down every single one of those leads and trying to contact them… The way that I run my business, it doesn’t make any sense for me to do that,” she said. She also likes the fact that technology can help her find leads hidden in plain sight, where she might not have expected them on her own. “Even within my own personal sphere of influence and my personal database, which is primarily warm leads, there are people that maybe I would not have realized are thinking about making a move.”
And it’s not just time — Gupta noted that there’s also a potential to save money by only reaching out to those who are very likely ready to make a move. “It allows a real estate professional to understand who is three or four times more likely to sell than others,” he said. “That allows them to focus their marketing… on a small subset of people as opposed to mass marketing to everybody.”
Indeed, analytics tools used by social media companies such as Facebook are already sophisticated enough to send users targeted ads based on their likes, their posts and their browsing habits while they’re connected, a factor many real estate professionals are taking advantage of in their marketing.
Predicting how the local market will develop
Big data and predictive analysis tools can also help buyers who are unsure of where to invest. Technology can look backward to determine when a neighborhood started getting hot and point to factors that might have driven the shift, such as improved amenities, new businesses or an influx of homebuyers belonging to a particular demographic. This can add to agents’ and brokers’ understanding of how their area has developed over time and help them see the next booming neighborhood.
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. Still, Nadi noted that this type of buy-side prognostication is a bit more slippery. “Being able to predict where they’re going to move is tougher,” Nadi said. “You see with some of this data that people living in condos in downtown Atlanta might be getting married or having a baby. Then the chances are good they’re going to be moving somewhere that maybe has better schools or a more family-friendly neighborhood.”
Predictive analytics takes those efforts a step further. 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 development in an area might look like. These tools can take information like existing data, trends and predictions and turn it into a visual representation of what an area might look like as it changes over several years. Future prices, density and the ratio of renters to non-renters are among the factors that might be revealed by predictive analytics.
Integrating big data into everyday life
While some of these tools can make privacy hawks uneasy, it’s not as though predictive analytics is something that’s completely new to society. Many people use the technology every day without noticing. Google Maps figures out the best way to get to a destination by layering current travel information with driving trends, and Amazon’s algorithms are able to use data to make targeted suggestions to guide shoppers to products they didn’t realize they needed or wanted before.
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.
Keller Williams is making a big push to provide agents access to data and technology that can give them a streamlined means of approaching their business. The company’s Command platform seeks to provide them with all the tools they need in one place, layering artificial intelligence on top.
“That’s where all the AI predictive analytics comes in,” said Keller Williams chief product officer Neil Dholakia. “You first have to have a view of everything that’s going on. Once you have that, you then you add the intelligence.”
Dholakia said many new tech products are designed to capitalize on all the information that’s generated in the typical real estate transaction. “We have a tremendous amount of data exhaust that that our agents produce just in their day-to-day activities,” he 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.”
But Dholakia also noted that in order to make big data products work, they have to be widely adopted by real estate professionals: “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.”
Finding the humanity
While big data can be overwhelming for some who are used to focusing on the human factor of the real estate transaction, none of these developments suggest real estate agents are in danger of being replaced by AI systems and predictive analytics algorithms.
“The chances that a home seller will basically choose an agent they’ve never met are pretty slim,” Gupta said. “It’s a way to home in on the right people, but it’s not the end-all because the agent still has to go build that relationship through whatever means they choose.”
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 that don’t. [But] they’re just tools. 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 either make the phone calls, go to the meetings, do the mailers and all the activities that are required of your profession. We’re just trying to give you an edge.”