Think about the times you’ve purchased a home. What was going on in your life at the time?
Had you landed your first job? Gotten married? Finished graduate school? Had your first or second child? Moved to a new town?
Moving, it seems, is inherently tied to these life events. And most of those events leave behind some paper trail that, to date, no Realtor has been able to easily track.
At least not before a pair of Durham entrepreneurs started collecting the data and then building a software to analyze and make sense of it, locate the people along the trail and target them with the right message when they’re most likely to buy a home. Their company called First (formerly First Leads) doesn’t yet have a product on the market. But a working prototype has already delivered Realtors around the nation bunches of solid leads by sending targeted emails to people who just completed graduate programs at one of 101 colleges in 53 U.S. cities. First has even made some money—a 25 percent commission on any sale that comes through a lead has brought in $50,000 in early revenue.
Idea Fund Partners was pretty sold on the idea and first-time founders Mike Schneider (left) and Jess Martin (right)—the early stage capital fund provided the final $250,000 to close a $750,000 round in May, investing alongside Sovereign’s Capital, run by former Bandwidth co-founder Henry Kaestner, and a dozen angel investors.
“It’s a big opportunity. But I think what is important is not how big the market is but how unique the approach is,” says Lister Delgado of Idea Fund Partners and a new First board member. “We look for companies that are doing things in unique ways.”
First founders back story
Schneider and Martin met through Kaestner and his local portfolio company CloudFactory. Schneider took a job with Kaestner’s Sovereign’s Capital after he graduated from Duke University in 2009. He was integral in helping to bring CloudFactory, a startup founded in Nepal, to Durham. And its unique way of doing business process outsourcing while leveraging on-demand human labor (thousands of trained “cloudworkers” in Africa) had a profound impact on him. CloudFactory provides the scalability of tools on Amazon Web Services but for tasks that require a person’s (or thousands of them) brain and touch.
“It was fascinating to see them win multi-million dollar contracts away from big players,” Schneider says. He began to think of business models that could take advantage of the CloudFactory platform—tasks that required the handling of huge data sets but which could be simplified, sorted and better understood using software. He started a search for a technical co-founder to help figure it out.
Kaestner and CloudFactory were the connection to Martin. Martin is a full-stack developer who had worked with many high-growth ventures before he happened to meet the CloudFactory team in 2011 at Kaestner’s house. Martin was preparing to spend a year with his wife in Africa and so CloudFactory founder Mark Sears invited him to spend the end of the sabbatical in Nepal—Martin took him up on the offer, spending his final 10 weeks training and mentoring teams of developers in Kathmandu. It was back in the U.S. in 2013, when he’d moved back into a consulting role, that Schneider reached out about his idea.
The pair spent the next several months looking at pain points in seven major industries that data analysis and CloudFactory’s labor source could address. After considering security, e-commerce, B2B lead generation and collectibles, they eventually settled on real estate. They believed they could solve the No. 1 pain point for professionals in the field—Who is my next customer?
It all came down to identifying the triggers that made people ready to buy a home and targeting them just at the time they’re most likely to start the process, and to actually buy. Lucky enough, there’s public data for the majority of those triggers—they represent life events. The problem was finding a way to structure the data—marriage licenses, birth certificates or diplomas are often locked in county courthouse or college filing cabinets or found in various file formats online. Human workers (i.e. CloudFactory’s teams) would be needed to sort through the data and verify the people. Software could be trained to identify the triggers in it and in other communications online (say, social media posts), and then to contact verified potential real estate customers and provide those who respond to Realtors as vetted leads.
“Jess and I both wanted to grow a venture-backed startup where we had the opportunity to transform an industry,” Schneider says. “We don’t want to be working on the No. 7-9 pain points.”
Transformational for real estate agents
Real estate represented a market of two million independent contractors who take in $69 billion of commission and spend $12 billion on marketing a year. And yet, the process they use to sell and market a home is largely the same as it’s been for 20 years.
Schneider and Martin believed that if they could understand why and when people will move, they could target people with specific products and services at the exact moment they need it, providing the best experience possible for buying a home. The prototype proved many of their assumptions correct.
45.6 percent of the graduates responded to this email: “We know you’re likely to sell your home in the next six months. Would you like to be connected to top agents in your market?” And many agreed to spend 15 minutes on the phone talking about their real estate search. First found the most productive Realtors by mining MLS data and county tax records—they provided that data to potential customers too.
“Our favorite response is, ‘I was just thinking I should be thinking about this. This is great timing,” says Schneider.
And Martin: “When you reach people with the right offer at the right time for something they are already thinking about, they really appreciate it.”
For beta tester Jed Gronewald of Hunter Rowe Real Estate in Raleigh, the offering proved to be a very different type of leads service. Instead of the typical leads websites that deliver “cold leads” that “take a lot of time to convert into business”, First’s leads are “warm.”
“The barrier for trust is reduced because of the warm referral from First Leads,” Gronewald says. And he appreciates that the agents with proven track records are allowed to rise to the top.
VCs like real estate…and data
Schneider and Martin also saw a venture capital industry eager for solutions to real estate’s problems—$605 million went to real estate technology companies in 2015, up from $241 million in 2013, according to a recent TechCrunch article.
To test that theory locally, they showed up to Delgado’s office hours earlier this year. Though there were follow up meetings and the regular due diligence, Delgado says he knew immediately after hearing their presentation that he wanted to invest. He saw in Schneider and Martin what he saw in iContact’s Ryan Allis, Automated Insights’ Robbie Allen and Windsor Circle’s Matt Williamson.
First also followed a similar path to those Idea Fund portfolio companies. Like Automated Insights with sports, WedPics with wedding photography and Windsor Circle with e-commerce, the men are starting with a single (but large) market but have a vision and technology that is much bigger. Think leads for insurance companies, HVAC contractors, landscapers, and more.
Data is also a common theme. WedPics just hired its first data scientist, and most of the other companies in the Idea Fund portfolio have a need for deep analytics as well. A focus on data analysis isn’t unique to the Triangle. But Delgado is increasingly impressed by the interesting ways in which smart Triangle entrepreneurs are making sense of it and building products around it.
For Schneider and Martin’s part, developing the tools to analyze and use data positions First to take advantage of the increasing amount of data being collected and made available over the next decade. It also contributes to the unbundling and rethinking of an industry still lacking in transparency, yet collecting huge fees from consumers. They’ll use the funds to make key hires and get the product to market.
“The core thing we’re realizing is that this new iteration of real estate companies are driven on data and yet it’s almost impossible to find the very best Realtor in any market. There isn’t data out there,” Schneider says. “We’re excited to be one of many companies driving from a data perspective to transform this industry.”