RealTrends Q32021 BrokerPulse sees brokers still optimistic about the market, wary of competition and wondering when inventory will rise.

2021 RealTrends Brokerage Compensation Report

For the study, RealTrends surveyed all the firms on the 2021 RealTrends 500 and Nation’s Best rankings, asking for annual compensation data for the 2020 calendar year.’s Sean Black on the transaction revolution

Real estate is on its third revolution, from the digital revolution of the early 2000s to the information revolution kicked off by Trulia and Zillow to today's transaction revolution.


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Zillow says they’ve got a new, more accurate Zestimate

An upgrade to the Zestimate algorithm uses neural networks, a type of machine learning, to produce more accurate price estimates.

Accuracy of the Zillow Zestimate has been in question for years. In fact, many agents built entire marketing campaigns around the importance of a real estate professional who knows the area to offer a more accurate assessment of value. With housing sales at all-time highs, that hyperlocal experience would offer insight into the quickly changing values of a specific neighborhood.

But, Zillow wants to change all that. They recently launched upgrades to its Zestimate® home valuation model. The changes allow the algorithm to react more quickly to current market trends and improve the national median error rate to 6.9% — an improvement of nearly a full percentage point for more than 104 million off-market homes. Although improved, an error rate of 6.9% is still significant, so agents can breathe a sigh of relief that they are still the go-to expert for home valuation.

The new Zestimate algorithm leverages neural networks, the latest machine learning approach, and incorporates deeper history of property data such as sales transactions, tax assessments and public records, in addition to home details such as square footage and location.

Neural networks are artificial intelligence systems that imitate how the human brain works. They are able to map hundreds of millions of data points efficiently, drawing connections among inputs and using the relationships formed to produce or predict an output. In the case of the Zestimate algorithm, the neural network model correlates home facts, location, housing market trends and home values.  

As a result of this update, the Zestimate can now react more quickly to dynamic market conditions, providing homeowners with a more accurate estimate [prediction] of a home’s current value. In addition, transition to a neural network-based model will reduce Zestimate processing time.

As a result of the company’s increasing confidence in Zestimate accuracy, in February Zillow began using the Zestimate as a live, initial cash offer through its home buying program, Zillow Offers. The Zestimate is an initial cash offer on about 900,000 eligible homes across 23 markets. With this latest update and increased Zestimate accuracy, the number of homes eligible for a cash offer will likely increase by 30%.

Applying a neural network model to a national real estate dataset was an innovation used by the winning team of Zillow Prize, the two-year, $1 million data science competition that included more than 3,800 teams from 91 countries working to improve the Zestimate.  One member of the team, Jordan Meyer is now a senior applied scientist at Zillow and works on home valuations for Zillow Offers.

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