Data is a wonderful thing. It can be harnessed in vast quantities to further our understanding on almost anything. The subReddit Data is Beautiful is a prime example of this. Impressively, Big Data investments will account for over $65 Billion in 2018 with the expectation of continued growth. Moreover, one startup has now utilized big data, along with machine learning, in a particularly unique way in the property market, creating a marvelous situation where everyone wins.
Landis Technologies Inc., today announces the launch of its platform that connects institutional investors with property owners. The platform leverages extensive property data and machine learning to match owners of single family homes with large real estate investors to create win-win transactions for both buyers and sellers.
The launch of the platform will change the way institutional investors purchase portfolios of residential properties. Landis’ clients are some of the largest residential investors in the US with an aggregate $200bn of assets under management.
“The application of data science to real estate is long overdue, but the traditional broker system isn’t set up to take advantage of this invaluable information,” said Tom Petit, co-founder of Landis. “By contrast, data sits at the heart of what we do. This enables us to connect investors with the properties that make sense for them. It also means we can reduce the costs associated with buying and selling rental properties because everything is streamlined to create a much more efficient system that benefits buyers and sellers.”
Landis’s industry-leading technology is designed to use data science to remove the frustration associated with traditional brokers. Currently, most real estate deals still happen over phone calls, scans and faxes, and institutional buyers who have very specific criteria for their holdings still need to do the filtering work themselves. Landis fixes this. Analogous to Amazon, Landis uses massive amounts of data to show buyers the properties they know they will want to acquire. The platform leverages its knowledge of what customers have bought in the past along with proprietary data to show accurate suggestions. Landis’ curation results in buyer conversion rates 100 times higher than the industry average.
Landis focuses on transacting portfolios of off-market single family homes to institutional investors. These portfolios are typically comprised of 10 to 100 properties and allow buyers to gain scale quickly in their targeted geographies. Landis also makes the transaction process fast and seamless, heading in the direction of Amazon’s “one-click buy.”
Landis was founded by Stanford classmates, Tom Petit and Cyril Berdugo. Petit, a Cambridge-trained mathematician who’s spent his career leveraging data and technology to solve business problems, previously worked at the intersection of data science and strategy at Airbnb, HelloFresh, and as a strategy consultant. Forbes 30 Under 30 member, Berdugo, was an institutional real estate investor at Crown Acquisitions and Fifth Wall Ventures, where he spent time working with single family home flipping company Opendoor.
“As a former institutional investor, I can attest that nothing close to Landis’s value proposition has been available,” said Cyril Berdugo, co-founder of Landis. “I’m proud of providing liquidity to smaller investors in the space while making the lives of institutional investors much easier. We’re completely changing the nature of the game.”