Buying a home can be considered one of the most important investment decisions a person will make in their lifetime. Unfortunately, it is extremely difficult for buyers to make an informed choice. Buyers have historically had very limited access to real estate data (available listings, market prices, trends) and have been forced to rely on intermediaries like real estate brokers to communicate information. The scant information that is made publicly available is difficult to gather and interpret. In this environment, buyers are forced to pay brokers high fees for their expertise (often 6% of sale price) and may miss out on better deals. Despite the obvious pain points, the industry has been slow to adopt technological solutions.<\/p>\n
Zillow saw an opportunity to use data aggregation and machine learning to address this information asymmetry. Zillow developed a web- and mobile- based marketplace that helps people find information on homes and connect with professionals. Zillow aggregates data from multiple listing services, brokerages, the U.S. Census Bureau (including the Housing Vacancy Survey and the Survey of Construction), the Bureau of Labor and Statistics Employment Cost Index and homeowners themselves. The consumer-friendly website digests the data and delivers accessible and helpful metrics to potential buyers and sellers. One democratizing metric Zillow offers is Zestimates, which uses sophisticated data aggregation and analytics to predict the value of a home. Another helpful tool is the Breakeven Horizon, 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 maintains a living database of over 100 million homes, offering property facts, transactional history, and listing information.<\/p>\n
Increasingly, consumers are turning to Internet and mobile solutions for real estate information – in 2016, over 65% of Zillow’s traffic came from mobile. Zillow has positioned itself well to take advantage of this shift in consumer habits and increased demand for information. It may seem like Zillow is the real estate company of the future, however, its model relies on many old-world real estate realities. For example, Zillow’s business model relies on the participation of real estate agents and brokerages. Zillow generates revenue from the sale of advertising services and tools to professionals in the real estate, rental and mortgage industries. Zillow’s operating model similarly relies on data from multiple listing services, brokerages, and real estate agents. For these stakeholders, Zillow provides lead generation that drives their businesses.<\/p>\n
Part of what Zillow has done for the real estate industry is highlight the inefficiency of the existing model of home buying. The real estate tech world has responded by developing a myriad of ideas to solve the problems of home buying, with focus on the 6% fee paid to brokers. The market is trending towards technologies that will replace the agent in real estate transactions, increasing efficiency and reducing or eliminating commissions. Companies like auction.com, Allre, and VivaReal are just some examples of online marketplaces that disintermediate the broker. As people move towards a completely digital model, tech-enabled brokerages that reduce transaction costs may have a role to play. Here, companies like SmarterAgent, Zumper and Movoto compete. In addition to this threat to the real estate industry composition as whole, companies like S’moretgage, Real Matters and FindTheBest fiercely compete on the research and analytics front, challenging Zillow’s leadership in this area.<\/p>\n
All together, these companies represent a revolutionary change to the traditional model of real estate, which Zillow, though advanced, still relies on in great part. Zillow needs to recognize this seismic shift and focus not on how to create value for the customer in the existing market, but how to compete in the new world of real estate. Zillow needs to reduce its reliance on traditional data providers like real estate agents, brokerages, and MLS. If customers have viable options to list, find, and purchase homes without using these intermediaries, the quality of Zillow’s data will be greatly damaged. Zillow might consider acquisition of online marketplaces that offer valuable data on homes that are bought and sold through that medium. More radically, Zillow might move towards a tech-enabled brokerage or marketplace model that actually hosts these transactions itself. Such a move would not only guarantee high quality data, but would also allow Zillow to compete with newer models of real estate.<\/p>\n
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\nhttps:\/\/www.datainnovation.org\/2015\/10\/zillow-uses-open-data-to-level-the-playing-field-for-consumer
\nhttp:\/\/www.esa.doc.gov\/sites\/default\/files\/cdac\/cdac–member-presentations-zillow.pdf
\nhttp:\/\/www.infoworld.com\/article\/3060773\/big-data\/hot-property-how-zillow-became-the-real-estate-data-hub.html
\nhttp:\/\/www.informationweek.com\/big-data\/zillow-uses-analytics-machine-learning-to-disrupt-with-data\/d\/d-id\/1327175
\nZillow 10-K, SEC Filing
\nTechCrunch.com<\/p>\n","protected":false},"excerpt":{"rendered":"
Zillow uses big data and machine learning to address pain points in the real estate industry, but is it thinking too small?<\/p>\n","protected":false},"author":2637,"featured_media":17886,"comment_status":"open","ping_status":"closed","template":"","categories":[2117,2523,298,2270,2527,2519,2530,346,502,2522,2529,775,2520,2526,2525,2528,2521,2524,2096],"class_list":["post-17885","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-advanced-analytics","category-allre","category-big-data","category-digital-disruption","category-findthebest","category-homes","category-information-asymmetry","category-machine-learning","category-marketplace","category-movoto","category-online-marketplace","category-real-estate","category-real-estate-industry","category-real-matters","category-smoretgage","category-tech-enabled-brokerage","category-trulia","category-vivareal","category-zillow"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/digitization-challenge-2016\/","yoast_head":"\n