Algorithm Failures and Consumers' Response: Evidence from Zillow

By: Isamar Troncoso, Runshan Fu, Nikhil Malik and Davide Proserpio

Format:Electronic
| Language:English
| Pages:41

Abstract

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 business closure, home sellers started making list-pricing decisions that deviated more from the 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, both benefitting home sellers.