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Scientifically Measuring The Value Of “Curb Appeal”

January 30, 2020

The importance of “curb appeal” as a factor for selling Greenwich homes has never been questioned. It’s as important as packaging is to any product that competes for a buyer’s attention. “Curb appeal” is a first impression, and how it strikes the buyer elicits a reaction which sets up a mindset, attitude and interest level of the rest of the tour.

Just exactly the degree to which curb appeal determines any Greenwich home’s sales success is—like most of the other factors that go into the art of selling—not something that you’d think would lend itself to scientific study.  Until recently, that is.

As the Journal of Real Estate Finance and Economics editors wrote: recent advances in the “theoretical and empirical research using the paradigms and methodologies of finance and economics” can be applied to real estate. 

That promise made some headway in a recent article authored by two college professors: “Valuing Curb Appeal.” The academics used newly developed Artificial Intelligence advances (“a deep learning classification algorithm”) to rate Google Street View photos, then combined that with sales data from nearly 89,000 properties. The result was a determination that homes with excellent curb appeal “sold for 7% more than similar houses with poor curb appeal.” Furthermore, in slow markets, that figure rose to as high as 14%.

As a Wall Street Journal reviewer acknowledged last week, the idea that buyers react to manicured lawns, attractive landscaping, and well cared for home facades isn’t surprising. Still, the way the researchers came up with the results could be important—at least in terms of putting numbers to what has until now been impossible to measure with any precision. 

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