iBuyers is used to describe online real estate buying companies such as; Zillow, Opendoor, and Offerpad.
Zillow announced this week that it is exiting the iBuyers market and selling its total inventory of >10,000 homes. Some have already been purchased by a company specializing in rentals. Zillow has announced that it couldn’t accurately predict future home prices and was losing too much money. The company expects to record losses of more than $500 million from home-flipping by the end of this year and is laying off a quarter of its staff.
Here is a snapshot of this market:
Home Listings: Offerpad:1,000, Zillow:2,500, Opendoor:4,500
Method: All three do a slight renovation; Offerpad usually does a more-intensive remodeling.
Days on the Market: Offerpad:72, Zillow:69, Opendoor:83
Profit Margin: None of the companies have made money on an annualized basis, but that may change this year.
They make their margin in add-on services like mortgage origination, and title and escrow.
Opportunity is enormous if the market shifts from offline (99%) to online(1%).
Must manage overall market risks and local risks in each city they operate in.
Purchase decisions are made in minutes by using an algorithm designed by software engineers—no one traipsing thru the house.
Observations:
If Zillow can’t predict its own buying, who says its flagship product on the web of listing the current market value of homes is accurate? (my buddy Joe brought this up during a discussion earlier today) Real Estate professionals have often criticized Zillow’s valuations.
Does Zillow see an overall market downturn - remember, an early sign of trouble in the real estate market has always been when the direct investors get out of the market - rents cannot sustain investment. That said, Opendoor is increased buying….
The Real Estate market has always required the personal services of a seasoned professional - is this now not needed? Is this another service that no longer requires people to guide us (i.e., hearing aid technicians, insurance and vehicle salespeople, any others…)?
In my current line of work (residential real property appraisal) we do analysis on prior sales and transfers for the home we are appraising for three years and any homes we use as comparable sales for one year. We’ve been trying to figure out the instant buyer model, as it appears they overpay on a relatively frequent basis. It’s been particularly noticeable over the last 6 months. Prior to that the profit margin appeared to be there, at least in the purchase and subsequent sale prices, most of the time. Lately it’s been more frequent to see the I-buyer going upside down in the deal.
Of course, there are other profit mechanisms in play that don’t show up in recorded sale prices. But still, it seemed unsustainable.
From the perspective of appraisers, the i-buyers add fluidity to the market which is good for us. Whether the market is going up or down, our business is good when houses change ownership. It’s when the market gets stuck that it’s bad for us.
The AI approach to the market works when it works and doesn’t when it doesn’t. Like all algorithms, accounting for exceptions to normal assumptions is the trick.
I read a book recently called Thinking Fast and Slow”. It talks about the two systems in human thinking: the autonomous one that can drive a car across town in busy traffic almost by itself while we daydream, and the other one that recalculates when unfamiliar patterns occur. They work together almost seamlessly. It seems this is the future of AI. Figure out when the pattern changes and kick in a different system.
In my current line of work (residential real property appraisal) we do analysis on prior sales and transfers for the home we are appraising for three years and any homes we use as comparable sales for one year. We’ve been trying to figure out the instant buyer model, as it appears they overpay on a relatively frequent basis. It’s been particularly noticeable over the last 6 months. Prior to that the profit margin appeared to be there, at least in the purchase and subsequent sale prices, most of the time. Lately it’s been more frequent to see the I-buyer going upside down in the deal.
Of course, there are other profit mechanisms in play that don’t show up in recorded sale prices. But still, it seemed unsustainable.
From the perspective of appraisers, the i-buyers add fluidity to the market which is good for us. Whether the market is going up or down, our business is good when houses change ownership. It’s when the market gets stuck that it’s bad for us.
The AI approach to the market works when it works and doesn’t when it doesn’t. Like all algorithms, accounting for exceptions to normal assumptions is the trick.
I read a book recently called Thinking Fast and Slow”. It talks about the two systems in human thinking: the autonomous one that can drive a car across town in busy traffic almost by itself while we daydream, and the other one that recalculates when unfamiliar patterns occur. They work together almost seamlessly. It seems this is the future of AI. Figure out when the pattern changes and kick in a different system.
Zillow learned this the hard way.