Technology has dramatically reshaped the way that real estate clients and agents alike experience the process of buying or selling a home. The internet, 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 agents approach the housing market in their areas. 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.
The power of predictive analytics
Leo Pareja was inspired to start his own predictive analytics company when he was still an agent. By age 28 he’d become the No. 1 Keller Williams agent in the world, but found himself unsatisfied with the technology on the market at the time. So, he created software to make it easier for agents to access data. Now he’s CEO of Remine, the company he founded to solve the problem of aggregating data from various public entites so agents can use it to uncover patterns.
“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 my county website, I can actually see it all compiled in one place.”
Traditional analysis tools have long been standbys for agents looking for insights into local markets. The numbers can indicate 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. In this way, past data offers insights into what homebuyers might be looking for and the types of areas that are likely to attract their attention.
With predictive analytics, agents can look at trends as they’re beginning to develop and use that information to target potential homebuyers. Rather than looking to the past to find out what drove a market to heat up, 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.
Another relatively new element that predictive analytics tools bring to the fore is the sheer volume of information that can be harnessed. Nearly endless amounts of existing datasets and trend lines can be layered on top of each other and turned into visual representations 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 many factors that might help agents see changes in their neighborhoods before they happen.
Why people buy
For Stephanie LoVerde, vice president of sales at Jameson Sotheby’s International Realty, the potential to understand what’s driving consumer behavior is intriguing. She likened the use of data and predictive analytics in real estate to the way credit card companies track consumer spending habits to understand what purchases a person may make in the future.
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“That ties into understanding of when millennials will, on average, get married and when a millennial, on average, will buy a home,” LoVerde said. “And it ties into housing trends in general. We can use all of that data to understand people’s spending habits and predict at what age they’re going to buy or what age they’re going to be making a major life decision. It even goes as far as companies like CVS seeing when people are buying baby diapers. Usually, children and the growth of children will inform someone’s housing position.”
By understanding consumers, their spending habits and trends among generational groups like millennials through predictive analytics, agents can more accurately target their marketing efforts. LoVerde sees the assumptions that can be made based on information gleaned from sources like Facebook ads as helpful in developing targeted marketing, though she notes that it’s a work in progress.
“It’s not hard and fast,” LoVerde said. “It doesn’t mean that every 35-year-old couple with two kids is going to be moving soon. But the likelihood would increase when that third baby comes along.”
Figuring out where leads come from
By using data that’s already broadly available in novel ways, 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.
Agents can drill deeply into data to uncover patterns of consumer behavior that can be helpful to them in their business. 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.
Ultimately, predictive analytics might be marshaled to assist agents in targeting potential clients more accurately, thus saving them time and money that otherwise would have gone to dead-end leads. That’s the theory behind SmartZip, a predictive analytics company co-founded by Avi Gupta in 2008. SmartZip’s offerings include SmartTargeting, which uses big data to identify homeowners who may be considering selling.
“It allows a real estate professional to understand who is three to four times more likely to sell than others,” said Gupta, who’s now president and CEO of the company. “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.”
While buyers may be attracted to marketing around property listings, predictive analytics is a much more important tool for the listing side of the prospecting puzzle, according to Gupta.
“When you’re talking about sellers, they do not find their real estate 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.”
While some may cringe at the idea of computers predetermining our every move, it’s not as though predictive analytics is something that’s completely new to users. Most people use the technology every day without noticing, whether they’re allowing Google Maps to lead them to the best way to get to their destination or letting Amazon’s suggestions guide their shopping.
It seems many real estate professionals are prepared to embrace predictive analytics as well. 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 the executives surveyed. They based their conclusions on the technology’s ability to perform analytical tasks on targeted markets.
But when it comes down to the real work of agents, big data won’t fundamentally alter the client relationship. “At the end of the day, there’s nothing better than a competent, knowledgeable, respectable, proven broker getting on the phone with someone,” said Scott Newman, a SmartZip user and founder and principal at RNG Group Real Estate. “You’re developing a relationship, answering their needs and helping them with whatever it is and making a plan with them.”
Newman suggested that agents think of predictive analytics as merely a way to open more doors, not close more deals: “This technology is just the tipping point. This is just about getting someone to take your call or to raise their hand and self-identify, and from there it’s about how good you are.”
The human touch
None of this means real estate agents are in danger of being replaced by algorithms. Agents are needed to help people navigate the emotional experience of the purchase, according to LoVerde.
“Technology serves a purpose and makes our lives more efficient and streamlined,” LoVerde said. “But at the end of the day, technology does not replace the human connection. Technology does not replace the need for our clients to have a strong advocate, or the need for our clients to have guidance and honest input. There’s an emotional component of real estate. Whatever tools you use won’t replace the human touch. It doesn’t replace the understanding and the listening that goes into a strong real estate interaction.”
Gupta agreed that personal interactions and interpersonal connections are key to establishing strong client-broker relationships. The ability to connect with a client on a personal level will always matter, regardless of how that client chose their agent.
“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 said developing relationships and having 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. They’re just a tool. Just because you purchase one of these tools or your MLS buys it for you — 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 of your profession. We’re just trying to give you an edge.”
User experience matters
While real estate professionals may be excited to integrate new technologies into their businesses, tech companies looking to make inroads in the industry would do well to design their products with the unique needs of agents and brokers in mind.
Jameson Sotheby’s International Realty provides LoVerde with software that uses predictive analytics principles to distribute monthly mailings to potential homebuyers. LoVerde looks for cross-platform compatibility and ease of use when she’s seeking out new tech tools to bring into her business.
“It has to have user-friendly options and it has to have mobile applications because real estate brokers are working from their phones a large majority of the time,” LoVerde said, adding that she chose a product called Basecamp to organize her listings and buyer clients largely because she liked how the mobile application worked. “Systems that perhaps are good desktop or laptop platforms but aren’t mobile-compatible aren’t even an option for me in my business. It needs to be something that I can access from my phone.”
After all, whether it’s predictive analytics or a new CRM, the best technology product isn’t worth a dime if you don’t use it.