A house is the most important investment most people own. Consumers are constantly faced with critical decisions regarding their home and financing of their home. Until the last few years, consumers had little objective and reliable information on which to make their decisions. Zillow has brought transparency for consumers, giving them the data and tools they need to navigate the real estate marketplace. As a result, an entire industry is in a state of upheaval, where both consumers and professionals are able to make more intelligent data-driven decisions.
At the heart of Zillow is a living database of more than 100 million U.S. homes – including homes for sale, homes for rent and homes not currently on the market. The database is built from a range of disparate sources, incorporating streams of county records, tax data, listings of homes for sale, listings of rental properties and mortgage information. Added to this rich collection is data that Zillow users – home owners and professionals – enter on homes on the Zillow web-site. The transaction, listing and attributes are overlaid with a nested geographic hierarchy from neighborhoods and census tracts to cities and states. Expanding and improving this database is a never-ending effort: we always need to get better.
The core innovation that Zillow offers are its advanced statistical predictive products, including the Zestimate®, the Rent Zestimate and the ZHVI® family of real estate indexes. The Zestimate is an estimate of the value of over 100 million homes and is updated three times each week. The challenge is to be able to deploy sophisticated and changing models at this scale and frequency. Zillow has developed a proprietary system that runs models in the R programming language in a parallel architecture to take advantage of multi-core processing servers, either in our own corporate server farm or on the Amazon Cloud. The R language is well known as a leading system for rapidly prototype statistical analytic solutions. By using R in production as well as research, Zillow maximizes flexibility and minimizes the latency in rolling out updates and new products.
Ingrained in Zillow’s corporate culture is finding new and better ways to help consumers make “data-informed” decisions. This corporate focus has led to the most comprehensive database on U.S. homes along with a powerful analytic development environment to exploit this data. As a result, Zillow has established itself as the leading innovator and disruptor in the real estate marketplace.
Dr. Stan Humphries is the Chief Economist of Zillow Inc. (NASDAQ: Z), the leading real estate information marketplace. Stan joined the company as one of its earliest employees in 2005 and created the Zestimate and its first algorithm. Since that time, Stan has built out the industry-leading economics and analytic team at Zillow. Prior to joining Zillow, Stan spent five years at Expedia where he ran the advanced analytics team. Before Expedia, Stan served as a researcher and faculty member at the University of Virginia, and was previously a Presidential Management Fellow where he served at NASA, the Office of Science and Technology Policy in the Executive Office of the President, and the Technology Administration within the Department of Commerce. Stan has also served in the United States Peace Corps, where he taught high school physics and chemistry in the West African country of Benin. Stan has a Bachelor of Arts from Davidson College, a Master’s of Science in Foreign Service from Georgetown University, and a Ph.D. in Government from the University of Virginia.
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