In Depth Real estate

Published on October 28th, 2015 | by Henry Sherwin and Daniel Castro

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Open Data Impact: How Zillow Uses Open Data to Level the Playing Field for Consumers

This article originally appeared as a guest blog for the U.S. Department of Commerce Economics & Statistics Administration. 

In the mid-2000s, several online data firms began to integrate real estate data with national maps to make the data more accessible for consumers. Of these firms, Zillow was the most effective at attracting users by rapidly growing its database, thanks in large part to open data.

Zillow’s success is based, in part, on its ability to create tailored products that blend multiple data sources to give customers answers to questions about the housing market. Zillow’s platform lets customers easily compare neighborhoods and conduct thorough real estate searches through a single portal. This ensures a level playing field of information for home buyers, sellers, and real estate professionals.

The system empowers consumers with all the information they need to make well-informed decisions about buying or renting a home. For example, information from the Census Bureau’s American Community Survey helps answer people’s questions about what kind of housing they can afford in any U.S. market. Zillow also creates market analysis reports, which give consumers information on questions such as whether it is a good time to buy or sell, how an individual property’s value is likely to fluctuate over time, or whether it is better to rent or to own in certain markets. These reports can even show which neighborhoods are the top buyers’ or sellers’ markets in a given city. Zillow uses a wide range of government data, not just from the Census Bureau, to produce economic analyses and products it then freely provides to the public.

In addition to creating reports from synthesized data, Zillow has made a conscious effort to make raw data more usable. It has combined rental, mortgage, and other data into granular metrics on individual neighborhoods and zip codes. For example, the “Breakeven Horizon” is a metric that gives users a snapshot of how long they would need to own a home in a given area for the accrued cost of buying to be less than renting. Zillow creates this by comparing the up-front costs of buying a home versus the amount of interest that money could generate, and then analyzing how median rents and home values are likely to fluctuate, affecting both values. By creating metrics, rankings, and indices, Zillow makes raw or difficult-to-quantify data readily accessible to the public.

While real estate agents are important to the process of finding a new home or selling an old one, Zillow and other platforms have connected consumers to a wealth of data, some of which may have been accessible before but was too cumbersome for the average user. Not only does this allow buyers and sellers to make more informed decisions about real estate, but it also helps to balance the share of knowledge. Buyers have more information than ever before on available properties, their valuations for specific neighborhoods, and how those valuations have changed in relation to larger markets. Sellers can use the same types of information to evaluate offers they receive or decide whether to list their home in the first place. The success that Zillow and other companies like it have achieved in the real estate market is a testament to how effective they have been in harnessing data to address consumers’ needs.

Image: Camernnovak.

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About the Author

Henry Sherwin is a graduate policy fellow at the Center for Data Innovation. He is finishing a Masters in Science, Technology, and Public Policy at the Rochester Institute of Technology. Henry has previously worked on program evaluation and expanding capacity for state and local housing and urban development organizations in both government and non-profit capacities.



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