Some Lessons About the Housing Market From Zillow’s Blunder

Technology has made our lives better in numerous ways but there are certain industries that have yet to experience much innovation from the tech sector.

The healthcare and education systems come to mind. Both areas are ripe for innovation but each is complex in its own ways that make it difficult for Silicon Valley to fix.

Then there is the housing market. Fees have come down across the board in asset management yet realtors still command a premium of 5-6% for their fee when a house is purchased. Zillow tried to take some of the frictions out of this process but failed miserably.

Here are some lessons for the rest of us from their ordeal.


The United States is in the midst of the biggest house price boom ever. The Case-Shiller National Home Price Index was up nearly 20% in the 12 months ended in August, the biggest one-year increase in the history of that index.

Yet one of the biggest real estate brands in the world has seen its stock fall nearly 70% since mid-February. Zillow has gotten hammered after bungling its iBuyer program just three short years after getting into the house-flipping business. The company announced it is shuttering the platform, selling the rest of its housing inventory, and laying off up 25% of its staff.

This was a serious misstep for a company that has become so synonymous with house-hunting that it was even featured on a Saturday Night Live skit earlier this year. While analysts can debate what the company needs to do next to turn things around, there are plenty of lessons here for individuals when it comes to understanding the real estate market.

Real estate is local

Zillow’s iBuyer program was predicated on the idea that their home-price algorithm could find houses to purchase, fix up, and sell for a profit. The idea was Zillow could find efficiencies in the system if they could do this at scale on a national level.

Unfortunately for them, real estate is local. Value in the housing market is determined by a wide range of factors from location to neighborhoods to taxes to school systems to amenities and much more. This is one of the reasons realtor fees are so sticky.

It’s hard to believe people still pay upwards of 6% to a realtor in this day and age with all of the technological innovations we’ve seen in the past few decades. But those realtors understand their local markets. They can help prospective buyers and sellers alike understand pricing trends, pros and cons of different locations, and which houses are suitable for their clients.

This is not an easily scalable business model.

Forecasting housing prices is difficult

Yogi Berra once said, “It’s tough to make predictions, especially about the future.” This is true of the housing market as well. On the company’s earnings call, CEO Rich Barton cited price forecasting volatility as one of the main reasons Zillow has been overpaying for houses:

Because of the price forecasting volatility, we have also had to reconsider what the business would look like at a larger scale. We have offered sellers a fair market price from the start, but we’ve also been clear that the business only becomes consistently profitable at scale. With the price forecasting volatility we have observed and now must expect in the future, we have determined that the scale would require too much equity capital, create too much volatility in our earnings and balance sheet, and ultimately result in a far lower return on equity than we imagined.

The problem with using historical models and algorithms when making buy and sell decisions in something as large and complex as the housing market is that it’s impossible to account for unknown variables. It was widely known millennials were coming into their prime household formation age, but no one could have foreseen how a global pandemic would force so many young people to look for a house all at the same time.

People get emotional about the housing market because it’s the roof over their heads. It’s the community their children grow up in. It’s the place they call home. Those emotions make it nearly impossible to predict how prices will change over time depending on the circumstances.

The long term usually wins

Most people are told from a young age that a house will be the biggest investment of their lifetime. This is partly due to the fact that it’s by far the highest-price item for the majority of the population. But this is also the case because many of us live in our homes for a long time. In fact, according to the U.S. Census Bureau, the average tenure for a homeowner in America is more than 10 years. Compare this with the average holding period on the New York Stock Exchange of just under six months.

Zillow wasn’t trying to hold houses for the long term. They were trying to buy and flip them in the short term. Barton mentioned on Zillow’s earnings call that the iBuyer program “was underpinned by the need to forecast the price of homes accurately three to six months in the future.”

Not only is it difficult to forecast housing prices in that short of a window, but there is a lot of friction involved in the buying and selling of homes as well. A stock can be traded instantaneously for free with the push of a button these days. Houses are neither that liquid nor cost-effective.

Buying and selling a house requires realtor commissions, inspections, title insurance, renovations, paperwork, taxes, and closings. It’s not an easy process, and maybe it shouldn’t be. Yes, technology could make it more efficient in some ways, but buying and selling a house shouldn’t be as simple as trading stocks on Robinhood.

Stocks are an intangible representation of ownership in a corporation. Houses are tangible structures that require a lot of work, maintenance, and understanding.

Buying and selling homes in the short term with the goal of turning a quick profit may sound intriguing. And there are certainly people out there who can flip homes for a profit. But it is not easy, and it is not guaranteed.

In the housing market, as well as the stock market, the long term usually wins.

This piece was originally published at Fortune.

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