How Many Ways Can You Monetize Data?


I watch the real estate sales vertical with great interest. There’s a lot of data, and money here, which in turn means a lot of innovation and competition. Companies like Trulia, Zillow (which are poised to merge shortly), Move (which operates the Realtor.com site) and a host of fascinating and scrappy regional players such as PropertyShark makes for endless creativity and impressive user experiences. The first thing you notice about all the online real estate information services is that none of them is trying to disintermediate real estate brokers. Indeed, these services typically have business models that depend on agents for revenue. Thus what has happened in this very unusual market is that customers have taken on the primary work of discovery (formerly a big part of the agent’s job), even though agents haven’t reduced their commissions to reflect this.

The second thing you notice is the wealth of structured data that is available for parametric searching. Search by zip code, price range, bedrooms, lot size, and much, much more. In fact, such powerful searching is table stakes now. Map integration? Done. Alerts? Done. Rich multimedia? Done. So what’s left to innovate?

Zillow burst onto the scene (beautifully timed to coincide with our late, great real estate boom a few years back) with its audacious system that put a price valuation on every home in the country. That brought it tremendous visibility, but also introduced consumers to the power of predictive analytics.

Trulia later upped the ante by overlaying neighborhood crime statistics on its database. Not to be outdone, its competitors overlaid school district boundaries to map the schools nearest to each home. Trulia then upped the ante again, licensing data from our Model of Excellence winner GreatSchools.org, that showed the relative quality of each school. And that’s where the market seems to be headed today – qualitative assessments of neighborhoods, along with more predictive analysis.

As you might expect, qualitative assessment starts with Census demographic overlays. Real estate site Movoto.com is already there, with zip-level income, education and ethnicity. Some other sites are hesitating because of the vagaries of real estate anti-discrimination laws. But that is not an impediment to third-party data providers such as Onboard Informatics, which provides a raft of local data, including an innovative “lifestyle search engine.” Other sites like neighborhoodscout.com provide sophisticated demographic views of local areas. And we’d be remiss not to acknowledge diedinhouse.com for those who need to know if former home occupants left on their own power or not.

But what’s most fascinating is that this lifestyle analysis of neighborhoods has even been elevated to a personalized, consultative model. The New York Times recently profiled a New York area firm called Suburban Jungle that helps homebuyers target areas based both on demographics and deep market knowledge. Suburban Jungle doesn’t sell real estate; it refers its clients to real estate agents in exchange for a fee-share, another great example of how many different ways data can be monetized.