In November 2021, Zillow announced the closure of its iBuyer business.
Popular media largely attributed this to a failure of its proprietary forecasting algorithm. We study the response of consumers to Zillow's iBuyer business closure. We show that after the iBuyer failure, home sellers started making list-pricing decisions that deviated more from their Zestimate–Zillow's algorithmically generated estimate of a home's current value–suggesting that the iBuyer forecasting algorithm failure negatively affected consumer trust in the Zestimate algorithm.
Moreover, sellers deviated more by increasing rather than decreasing their list price. We next look at the downstream consequences of the Zillow iBuyer closure on sales outcomes, such as sales price premium over the list price and time on the market. We find that properties are sold for more and in less time, thus benefitting home sellers.
Davide Proserpio is an Associate Professor of Marketing at the University of Southern California Marshall School of Business. In his research, Professor Proserpio seeks to measure and quantify the impact of digital data and platforms on industries and markets, and most of his work focuses on the empirical analysis of a variety of companies, including Airbnb, Amazon,TripAdvisor, and Expedia. Professor Proserpio holds a B.S. from Politecnico di Milano (Milan, Italy), a M.S. from Carlos III University (Madrid, Spain), and a Ph.D. in Computer Science from Boston University.
This seminar will be held in English.
Major information: Daniela Bolzani (daniela.bolzani@unibo.it).