Real Estate Startup HomeLight Secures $109M In Debt & Equity
Buying a home is one of the biggest, and most expensive, decisions in a person’s life. Over the past year or so, we’ve written about a slew of startups that have developed technology aimed at making the process smoother and cheaper in one way or another.
Today, another such startup, San Francisco-based HomeLight, has announced a $109 million round of debt and equity funding. The financing round includes $63 million in Series C equity from venture capital firms and $46 million in debt financing “to fuel mortgage operations.”
Zeev Ventures led the round, which included participation from Group 11, Menlo Ventures, Crosslink Capital, Stereo Capital, and others. The financing brings the company’s total raised over its lifetime to about $164 million, according to Crunchbase data. Previously, it raised a $40 million Series B in August 2017.
HomeLight’s initial product focused on using artificial intelligence to match consumers and real estate investors to agents. Since then, the company has expanded to also providing title and escrow services to agents and home sellers and matching sellers with iBuyers. (Note that although we almost killed using this overused term, we decided to leave it but explain what it is, which is, according to Housing Wire, “the catchall term for online real estate investors who seek to reduce transactional property costs via digital tools”). In July, HomeLight acquired Eave as an entry into the (increasingly crowded) mortgage lending space.
CEO Drew Uher founded HomeLight in 2012 after he and his wife experienced firsthand the pain of trying to buy a home in the competitive Bay Area market.
“The process of buying a home in San Francisco was so frustrating it made me want to bang my head against the wall,” Uher told me. “I realized there was so many things wrong with the real estate industry. I went through a few real estate agents before finding the right match. So when I did find one, it made me feel empowered to compete and win against the other buyers.”
Thus, the concept behind HomeLight was born.
“We decided to first try to help people solve the problem of finding the right real estate agent,” Uher said. “But now it’s grown into so much more.”
If you’ve ever bought a home, you know how important it is to have good chemistry with your agent. That person gets to know you and your family intimately. They need to be familiar with your target market, attentive and know how to negotiate well on your behalf. Like Uher, some people go through multiple agents before finding someone with whom they are comfortable.
Uher said that even as a graduate of Stanford Graduate School of Business and having worked on Wall Street, he was overwhelmed by the whole process in general.
“I viewed myself as being financially savvy but when it came to navigating the home buying process, I was just out of my element,” he admitted. “There’s a lot of nuances in the way which real estate is transacted that is very specific to the industry.”
How It Works
HomeLight uses “proprietary machine-learning algorithms” to analyze millions (over 40 million it says) real estate transactions and over 1.4 million agent profiles. It claims to connect a client to a real estate agent on average “every two minutes” and that it has “driven well over $17 billion of real estate business nationwide.”
With its “Simple Sale” product, HomeLight aims to be “a Kayak for iBuyers,” according to Uher.
“It helps sellers determine which iBuyer is going to pay the most money for their home, and then connects the seller to that iBuyer,” he said. “For example, some buyers are not able to purchase homes that need a lot of work, or were constructed before a certain year. The diversity of our platform helps with that and pairs very well with our core matching agent product.”
Uher emphasized that HomeLight is not trying to “kill the real estate agent.”
“We’re not so sure that makes sense when it’s time to make the largest financial transaction of someone’s life,” he told Crunchbase News. “But when you have six or seven figures on the line, it doesn’t make sense to completely remove the human element in the process.”
Dovi Frances, founding partner of Group 11, said in a statement that his firm has been investing in HomeLight since its seed stage, and put money in each round since.
The company, Frances said, “has a seven-year head start on other companies in the proptech space hoping to monetize agent referrals.”
Oren Zeev, managing director of Zeev Ventures, said that HomeLight’s “evolution from a single product company to a real estate platform aligns with our vision for the future of real estate.”
Currently, HomeLight has over 200 employees, up from about 100 at this time last year. Its revenue has been growing at about 145 percent for the last three years, according to Uher. Besides San Francisco, it has offices in Scottsdale, Ariz., Seattle, Wash., and New York.
Looking ahead, HomeLight plans to use its new capital primarily to join startups such as Better.com (which recently raised a $160 million Series C that we reported on here) that are in the digital mortgage lending space. It also plans to “get into” the title and escrow business “to help agents and clients work through the closing process.”
I’ve been paying attention to the real estate tech space and all the funding taking place in it as of late (in a former life, I used to be a real estate reporter). In September, I wrote about how Divvy Homes raised a $43M Series B round to help in its mission to help more Americans “move from renters to [home]owners.” Earlier this year we saw some massive funding rounds from the likes of Knock and Compass.
And in July, we covered Fifth Wall Ventures’ raising $503 million for its second fund to invest almost exclusively in real estate tech companies. I’ve said it before and I’ll say it again: Buying a home appears to still be the American dream for many. And as long as that’s the case, there will likely be demand for services that companies like HomeLight offer. The company does seem to be trying to do a lot of things at once, but I guess only time will tell if that approach is successful, or not.
