The scary thing is that it's easy to see how something how like this could drive a market boom and bust cycle. I'm imagining a scenario where two iBuyer companies try to outbid each other algorithmically, driving the prices further and further out of reach of people who are looking for a primary home.
Tangentially related, I talked to a friend who works on geospatial data for one of the big vacation rental companies, and he was remarking how many homes in many desirable areas are now rentals. It's not that uncommon to see nearly entire neighborhoods converted to short term rentals now in some areas where they're still legal. Hearing that really depressed me.
We often talk about automation in terms of replacing various types of labor, but I've become really interested in automation creating adverse market incentives for smaller market participants because that's exactly what buying real estate right now feels like.
It's honestly quite scary how I'm in the top 2% of income earners in my generation and yet I could barely afford to buy a small place in a semi-desirable area. I can easily see myself not being able to compete in algorithmically dominated markets flush with venture cash in the future and I earn more than just about everybody I know today.
One can blame Airbnb, Zillow or whoever else, but the truth is that speculation in real estate and vacation towns have both been a thing for a very long time. If the population rises and we refuse to build more houses, the existing ones will get more expensive no matter what. The solution is out there in front of us but everyone prefers to dance around it.
> I'm imagining a scenario where two iBuyer companies try to outbid each other algorithmically, driving the prices further and further out of reach of people who are looking for a primary home.
But iBuyers are always low-balling. They are bidding under the asking price with an all-cash offer that they hope will make up in speed and ease what it lacks in price.
> It's not that uncommon to see nearly entire neighborhoods converted to short term rentals now in some areas where they're still legal. Hearing that really depressed me.
I lived in Lake Tahoe for ten years before AirBnB was a thing and three out of four homes there were absentee owners that only used them a few weeks a year. It made it a very hard place for small businesses to stay afloat. Most visitors stayed at big hotels or paid huge premiums for ad hoc "cabin rentals" through local realtors. The most depressing part was Halloween - kids hiking up and down steep hills to mostly empty houses. :)
> It's honestly quite scary how I'm in the top 2% of income earners in my generation and yet I could barely afford to buy a small place in a semi-desirable area. I can easily see myself not being able to compete in algorithmically dominated markets flush with venture cash in the future and I earn more than just about everybody I know today.
A thought exercise: suppose that no new houses are ever built and that housing turnover is nearly zero. What happens to the price of housing in that limit? Market forces do not necessarily entitle the top n% of the income distribution to housing.
I was a bit cynical about this too: I live in Los Angeles, where a "small place in semi-desirable area" gets listed for 1.5M and goes for nearly 2M. I'm somewhere in the top 5% of earners in California, but that $2M 1950s tract housing would be >50% of my post-tax income.
I recently bought a home. We toured a Zillow home, and I can understand what they were going for and where they failed.
We were able to pull up to the driveway, book a tour for that minute, and walk in the front door. It was almost a magical experience compared to the process of finding and going to showings. The listings were clear and thorough. The experience was extremely compelling.
The downside: the homes were absurdly overpriced. I bought a home for about 10% less than the last Zillow listing. For less, I got three times the land, 40% more square footage, a better location, updated appliances, new carpets, landscaped back yard, horseshoe driveway, two car garage. Almost zero effort had been put into modernizing the Zillow home and it showed.
I suspect if I had come in with a very low offer, they'd have accepted it. But for what?
If I was Zillow, I'd have licensed the tech to realtors. I'd definitely be inclined to buy a home through them if they weren't the ones selling the property directly.
If I can give any home buying tip from my experience of buying two houses it's been to look at places that are in "the middle". Both homes I've bought in SoCal have had some god-awful photos online, and the finish is new-ish, but done by someone in the 70s so it's new but tacky in a little-old-lady way.
This ends up pricing the house too expensive to flippers, and not nice enough to sell compared to other houses because it doesn't have the farmhouse sink and looks exactly like a grandma took out a home equity line and renovated (which is what happened).
That’s saying a lot for a red hot real estate market.
I still get updates from Zillow every month saying my home increased 5% in value in the last 30 days and up 30% over the last 12 months. Something is wildly off with their algorithm.
I’m surprised you have an issue with arranging visits to open houses?
Open RedFin, check the houses for sale, go to the open house when there is one? That’s at least how it works in the Bay Area. We never had to schedule or book anything, and only after seeing a house we liked, we asked our agent to check it out and submit an offer.
I was at Zillow for many years and left in 2020. On the tech side the pivot into iBuying was absolutely bonkers. The message from senior leadership was basically: I have no idea what your teams should be working on but it’s definitely not what they are currently working on so stop that and figure something else out.
This has nothing directly to do with their market failure but they probably are driven by the same leadership problems.
Sounds familiar, I read this as leadership saying... "you all need to change what you are doing because you must not know what you're doing because we don't know what we're doing and we're the ones in charge."
i wish we lived in the same area and could have an OTR conversation about this. believe it or not, the new "strategy" now that ZO is all shut down is even less well-defined and more pie-in-the-sky than ZO ever was.
Anecdote on the estimates. We bought a house for X and renovated it. The day before we listed it both Zillow and Redfin estimate had an estimate around the purchase price X. When we listed it for 2X, both companies changed their estimate to be close to the listing. However, Redfin changed the entire price history as well showing a gentle slope. Zillow preserved their previous history and showed a spike.
+1 I have always been annoyed by Redfin's rewrite of history. At least have the decency to show two lines (original prediction for last year and how it turned out to be).
Another anecdote - We sold a house in late 2020, decided to get an offer through zillow first, since we had a newborn and staging would have been a hassle.
Zillow lowballed us 10% under their zestimate, and still tacked on an 8% fee - we ended up going with a realtor instead, and ended up getting 15% over the Zestimate, with a 6.5% fee.
Some twitter threads from Zillow insiders I saw around this referenced a couple things:
* the pricing algorithm was good, but the business leadership got hungry and kept overriding it with higher offers in the hunger to do more business.
* they were trying to do so much business that they couldn't source the labor need to flip - painting, landscaping etc. They were so backlogged they were just sitting on houses they overpaid for (due to overriding the algorithm), and the constant cashflow aspect that makes flipping work at scale was destroyed
Matt Levine's take was something like:
if the pricing algorithm is good but it tells you that the flip strategy is only profitable on relatively small number of properties, then it's not profitable at scale cuz you're paying a big engineering team to create, tune and maintain it.
When you hire at a growth rate the workers will find work to do whether or not it helps your business. In this case I could see a bunch of home buyers being hired and justifying their jobs.
The author buried the lede. Zillow came up with a model to choose bid and ask prices. The model said, "Don't buy". They didn't believe the model and chased the deal, and lost money.
It's such a glaring red flag that one of the largest public resources for getting pricing information on housing is also buying and selling that housing. Come on, this is so glaringly abusable that any teenager could tell you what's wrong.
Can you illustrate the mechanism of abuse? Pricing information on housing is readily available to almost everyone, outside of the couple stated that do not mandate it. Zillow makes it easier, but Redfin and realtor.com and countyoffice.org and other websites offer the same information scraped from municipal websites.
I am especially annoyed at Zillow SF holding "Data Science" meetups in San Francisco at the penthouse place, while advertising for TWO data science positions.. meanwhile, frat guys are at the golf course by the dozens, across three states. The people that they hired at that time, probably built this setup exactly as required by the frat guys. Happy banking Zillow!
The author has a valid point in that the information asymmetry will attract sellers whose property is overvalued to sell to Zillow. I suspect though that something different happened in reality. I live in a 70 unit condo building, so there are a lot of very good comparables. Zillow bought one of the units about 10% over market value, which makes me think that they're doing some sort of market manipulation, like charging a 20% fee that is not part of the real estate record. So they wanted to pump up prices, but it didn't work.
It’s very hard to do good real estate pricing models from raw data. You can get all sorts of metrics on the property statistics but one important factor in the cost of the home is the state of renovation. Since most listings don’t have a historical listing of work done in the home your best hope of accurately assessing this comes from something like computer vision on the listing pictures. Assessing the quality of work, recency of work, quality of materials and factoring that into a house price is extremely hard. It would not surprise me at all if Zillow paid near market value for a whole bunch of dated homes that hadn’t kept up with the times and would sell for below the market of similar homes in the neighborhood according to typical metrics. The stories make it seem like their model had even more issues than that. Still I’m surprised anyone actually tried this idea given how poor the algorithms are and how obvious it is that key data points are not available.
In my experience, Zillow is sometimes conspicuously bad at valuing condos and literally doesn't know their market value, no matter how obvious it may be to you https://news.ycombinator.com/item?id=30724925
> Here’s the problem: my autodraft team ended up with a roster almost exclusively stocked with the players idiosyncratically overrated by Yahoo!. For example, an older player whose younger backup had just earned praise from the coach, suggesting that he might be about to lose his job.
I guess this is pretty obvious but just to be explicit, what's happening I guess is that players that are "correctly" valued by the algorithm are getting taken by others, and only the overvalued ones are left for the algorithm to choose.
Zillow's estimates of home values in my area have consistently been 150% of actual prices, as far as I've seen over the past years. Not that I've looked that closely and given that this is a hard area for them with low sales and a broad range of values for reasons not easy for their algorithms to quantify.
However, I always took that to be intentional, sort of a "see how valuable your home is / how high the values are where you're looking at"; hype that cost them nothing but made everyone feel better. Did the person that set that "glamor bonus" fudge factor get fired or just wasn't allowed to talk to the team deciding offer prices?
The Zestimate history for a condo I used to own is hilarious. There have been several sales of this property over 5 years, all at about the same price.
If you follow the Zestimate through time, it climbs rapidly until there is a sale, then it goes "oh shit" and plummets down to the sale price, which is barely different from the last time it was sold. This cycle repeats each time the property is sold.
Zillow is absolutely certain that this property should be rapidly increasing in value, no matter how many times it sells at about the same price it sold for last time.
When we sold the property, the agent told us it was in an awkward spot: too expensive for single people, not quite big enough for high-earning families. So it's stuck in price limbo as all the neighboring condos skyrocket.
Based on this experience, I remain convinced that there are micro-structural factors the fancy data science pricing models just can't seem to capture yet.
It varies widely by Area how accurate the zestimate is. In some places Redfin is much higher than Zillow, in others places it’s reversed. Sometimes they’re too high, sometimes they’re too low. I presume the algorithm does best when the prices are fairly flat, but in this market real estate prices changed dramatically and it seems pretty impossible for an algorithm to figure it out without modeling the entire economy and movement patterns of the population.
Another anecdote: I’m in Oakland, where condo prices went down slightly during the pandemic overall, yet Zillow’s estimates are always much higher than Redfin’s (which seem to be in the same ballpark as the sale prices).
Zillow purchased a home in my neighborhood for $370K, is now trying to sell it for $410K. Prior to this purchase other houses with a larger footprint in our exact same neighborhood were selling for $250K(literally just months before). For some reason zillow chose to pay 100K over what would have been fair value for the house.
I'm planning to sell very soon and love the iBuyer model.
Don't have to deal with showings, or fix anything, or hope a buyer's financing doesn't fall through at the last minute. To me that's worth whatever percent they're getting.
> A less competitive market is less dynamic and worse for sellers, but it is better for the iBuyers that remain.
If they can avoid taking on the bad deals that Zillow was previously shielding them from. I've seen how in some markets the disappearance of a provider that falls victim to this kind of adverse customer selection merely moves the problem to other providers in a cascading fashion. It's not clear that there are that many profitable deals to be made on the iBuying model
its easy to lose money if you're buying at retail and then selling at retail... there is really no money to be made in that scenario. I buy and remodel and either sell or rent the houses I aquire, but I do this at drastically reduced rates below retail. IMHO its the only way to buy. Every property I invest in has a problem, which is why the price is so low, alot of times its 10x below retail because of this. The top reasons why a house might have a problem is 1) the owners died and taxes were never paid, 2) the bank (or an individual) foreclosed on it reducing the price, 3) there are leins from the county or federal government that are making the house not sellable or worth nothing as a result, 4) the house has permit or code enforcement issues that the owner cannot resolve on their own ... Anyway, the best way to buy property is this way, and one rule I learned from attending auctions in person along time ago (its mostly online now) was that once the bidding goes above a third of its retail value, I'm out... Because sometimes you may have to invest 10-40k to make a house back to normal, and so paying even half its retail value just makes no sense.
I bet humans could have done a lot better than -$881M, and it wouldn't have been very costly to employ them. How many homes did Zillow iBuy in total, 10-20k? If it takes 5 minutes to evaluate a house, that would be 100,000 minutes, which is ~50 people working full time for a week. Spending $100k on that could have saved 100s of millions, plus it might have generated better training data for the model.
"Do market makers in the stock market run into this problem?"
Yes, that's why they have to account for the probability that whoever hits their bid is an informed trader (vs. uninformed/noise trader). And it's part of the reason they can provide price improvement when they source order flow from retail brokers, whose customers are mainly uninformed/noise traders.
How did opendoor manage to do the same thing better? The article seems like a takedown of the model, but opendoor managed to do the same thing profitably.
From what I've read it seems Zillow never had the actual expertise to do this, they were always a house price checking site. On the other hand opendoor started out doing this from the start.
I recall reading months ago that Zillow made cash offers with inspections waived, in order to expedite the process. I believe they had an algo which would access average repair cost which they would factor in the actual offer.
Each house needs to be inspected by multiple experts as there are many toxic properties with huge liabilities.
Yes. Source: I was employee 24 at Opendoor. Zillow's pricing algorithms are and always were terrible.
They tried to paper over this during their iBuying push with humans, and then in an effort to outgrow Opendoor, they incentivized growing at any cost without the proper controls to prevent adverse selection. And due to some unfortunate timing with the market cooling, they got wrecked for it.
If I remember the discussion at the time, OpenDoor and Offerpad are pure-play iBuying while Zillow was an already huge business pivoting into iBuying to make up for declines in its advertising business. Zillow had a reason to scale faster than the others and they didn't do it very well.
This is a good question. I am long on some company figuring out how to really streamline the home buying/selling process. Everyone dreads it, nothing worse than trying to buy or sell a home. These companies could be great buffers allowing the quick sale/buying of a home with minimal overhead. There is definitely a market for providing 'peace of mind' and the guarantee of not being screwed which today there is a high probability of from all angles.
Hopefully Opendoor can figure it out. They're probably going to need a lot of cash, homes, and software to really put it together into something that can be automated and scale.
[+] [-] thr0wawayf00|4 years ago|reply
Tangentially related, I talked to a friend who works on geospatial data for one of the big vacation rental companies, and he was remarking how many homes in many desirable areas are now rentals. It's not that uncommon to see nearly entire neighborhoods converted to short term rentals now in some areas where they're still legal. Hearing that really depressed me.
We often talk about automation in terms of replacing various types of labor, but I've become really interested in automation creating adverse market incentives for smaller market participants because that's exactly what buying real estate right now feels like.
It's honestly quite scary how I'm in the top 2% of income earners in my generation and yet I could barely afford to buy a small place in a semi-desirable area. I can easily see myself not being able to compete in algorithmically dominated markets flush with venture cash in the future and I earn more than just about everybody I know today.
[+] [-] paxys|4 years ago|reply
[+] [-] haroldp|4 years ago|reply
But iBuyers are always low-balling. They are bidding under the asking price with an all-cash offer that they hope will make up in speed and ease what it lacks in price.
> It's not that uncommon to see nearly entire neighborhoods converted to short term rentals now in some areas where they're still legal. Hearing that really depressed me.
I lived in Lake Tahoe for ten years before AirBnB was a thing and three out of four homes there were absentee owners that only used them a few weeks a year. It made it a very hard place for small businesses to stay afloat. Most visitors stayed at big hotels or paid huge premiums for ad hoc "cabin rentals" through local realtors. The most depressing part was Halloween - kids hiking up and down steep hills to mostly empty houses. :)
[+] [-] a1pulley|4 years ago|reply
A thought exercise: suppose that no new houses are ever built and that housing turnover is nearly zero. What happens to the price of housing in that limit? Market forces do not necessarily entitle the top n% of the income distribution to housing.
I was a bit cynical about this too: I live in Los Angeles, where a "small place in semi-desirable area" gets listed for 1.5M and goes for nearly 2M. I'm somewhere in the top 5% of earners in California, but that $2M 1950s tract housing would be >50% of my post-tax income.
[+] [-] bastawhiz|4 years ago|reply
We were able to pull up to the driveway, book a tour for that minute, and walk in the front door. It was almost a magical experience compared to the process of finding and going to showings. The listings were clear and thorough. The experience was extremely compelling.
The downside: the homes were absurdly overpriced. I bought a home for about 10% less than the last Zillow listing. For less, I got three times the land, 40% more square footage, a better location, updated appliances, new carpets, landscaped back yard, horseshoe driveway, two car garage. Almost zero effort had been put into modernizing the Zillow home and it showed.
I suspect if I had come in with a very low offer, they'd have accepted it. But for what?
If I was Zillow, I'd have licensed the tech to realtors. I'd definitely be inclined to buy a home through them if they weren't the ones selling the property directly.
[+] [-] wcfields|4 years ago|reply
This ends up pricing the house too expensive to flippers, and not nice enough to sell compared to other houses because it doesn't have the farmhouse sink and looks exactly like a grandma took out a home equity line and renovated (which is what happened).
[+] [-] judge2020|4 years ago|reply
If this wasn’t another house in the same neighborhood then the differentiator most certainly wasn’t Zillow or their pricing.
[+] [-] awb|4 years ago|reply
That’s saying a lot for a red hot real estate market.
I still get updates from Zillow every month saying my home increased 5% in value in the last 30 days and up 30% over the last 12 months. Something is wildly off with their algorithm.
[+] [-] TomVDB|4 years ago|reply
Open RedFin, check the houses for sale, go to the open house when there is one? That’s at least how it works in the Bay Area. We never had to schedule or book anything, and only after seeing a house we liked, we asked our agent to check it out and submit an offer.
[+] [-] polski-g|4 years ago|reply
[+] [-] hammock|4 years ago|reply
[+] [-] encoderer|4 years ago|reply
This has nothing directly to do with their market failure but they probably are driven by the same leadership problems.
[+] [-] itronitron|4 years ago|reply
[+] [-] phlowbieuq|4 years ago|reply
[+] [-] unknown|4 years ago|reply
[deleted]
[+] [-] dpierce9|4 years ago|reply
[+] [-] harikb|4 years ago|reply
[+] [-] turkishmonky|4 years ago|reply
Zillow lowballed us 10% under their zestimate, and still tacked on an 8% fee - we ended up going with a realtor instead, and ended up getting 15% over the Zestimate, with a 6.5% fee.
[+] [-] double0jimb0|4 years ago|reply
[+] [-] skrtskrt|4 years ago|reply
* the pricing algorithm was good, but the business leadership got hungry and kept overriding it with higher offers in the hunger to do more business.
* they were trying to do so much business that they couldn't source the labor need to flip - painting, landscaping etc. They were so backlogged they were just sitting on houses they overpaid for (due to overriding the algorithm), and the constant cashflow aspect that makes flipping work at scale was destroyed
Matt Levine's take was something like:
if the pricing algorithm is good but it tells you that the flip strategy is only profitable on relatively small number of properties, then it's not profitable at scale cuz you're paying a big engineering team to create, tune and maintain it.
[+] [-] shp0ngle|4 years ago|reply
[+] [-] dmix|4 years ago|reply
[+] [-] projektfu|4 years ago|reply
Sometimes it's better to sit on your hands.
[+] [-] shp0ngle|4 years ago|reply
[+] [-] jjice|4 years ago|reply
[+] [-] lotsofpulp|4 years ago|reply
[+] [-] ianferrel|4 years ago|reply
[+] [-] mistrial9|4 years ago|reply
[+] [-] buzzdenver|4 years ago|reply
[+] [-] TimPC|4 years ago|reply
[+] [-] civilized|4 years ago|reply
[+] [-] alecbz|4 years ago|reply
I guess this is pretty obvious but just to be explicit, what's happening I guess is that players that are "correctly" valued by the algorithm are getting taken by others, and only the overvalued ones are left for the algorithm to choose.
[+] [-] h2odragon|4 years ago|reply
However, I always took that to be intentional, sort of a "see how valuable your home is / how high the values are where you're looking at"; hype that cost them nothing but made everyone feel better. Did the person that set that "glamor bonus" fudge factor get fired or just wasn't allowed to talk to the team deciding offer prices?
[+] [-] civilized|4 years ago|reply
If you follow the Zestimate through time, it climbs rapidly until there is a sale, then it goes "oh shit" and plummets down to the sale price, which is barely different from the last time it was sold. This cycle repeats each time the property is sold.
Zillow is absolutely certain that this property should be rapidly increasing in value, no matter how many times it sells at about the same price it sold for last time.
When we sold the property, the agent told us it was in an awkward spot: too expensive for single people, not quite big enough for high-earning families. So it's stuck in price limbo as all the neighboring condos skyrocket.
Based on this experience, I remain convinced that there are micro-structural factors the fancy data science pricing models just can't seem to capture yet.
[+] [-] throwaway1777|4 years ago|reply
[+] [-] some-guy|4 years ago|reply
[+] [-] avgDev|4 years ago|reply
[+] [-] JRKrause|4 years ago|reply
[+] [-] ourmandave|4 years ago|reply
Don't have to deal with showings, or fix anything, or hope a buyer's financing doesn't fall through at the last minute. To me that's worth whatever percent they're getting.
Sadly, no iBuyer operates in my fly-over state.
[+] [-] ridaj|4 years ago|reply
> A less competitive market is less dynamic and worse for sellers, but it is better for the iBuyers that remain.
If they can avoid taking on the bad deals that Zillow was previously shielding them from. I've seen how in some markets the disappearance of a provider that falls victim to this kind of adverse customer selection merely moves the problem to other providers in a cascading fashion. It's not clear that there are that many profitable deals to be made on the iBuying model
[+] [-] jijji|4 years ago|reply
[+] [-] CloudYeller|4 years ago|reply
[+] [-] rahimnathwani|4 years ago|reply
Yes, that's why they have to account for the probability that whoever hits their bid is an informed trader (vs. uninformed/noise trader). And it's part of the reason they can provide price improvement when they source order flow from retail brokers, whose customers are mainly uninformed/noise traders.
[+] [-] cloutchaser|4 years ago|reply
From what I've read it seems Zillow never had the actual expertise to do this, they were always a house price checking site. On the other hand opendoor started out doing this from the start.
[+] [-] prototypeasap|4 years ago|reply
Each house needs to be inspected by multiple experts as there are many toxic properties with huge liabilities.
[+] [-] devmunchies|4 years ago|reply
Does Opendoor just have better algorithms/models? What factors allow them to have different outcomes from Zillow?
[+] [-] bgentry|4 years ago|reply
They tried to paper over this during their iBuying push with humans, and then in an effort to outgrow Opendoor, they incentivized growing at any cost without the proper controls to prevent adverse selection. And due to some unfortunate timing with the market cooling, they got wrecked for it.
[+] [-] philipodonnell|4 years ago|reply
[+] [-] trixie_|4 years ago|reply
Hopefully Opendoor can figure it out. They're probably going to need a lot of cash, homes, and software to really put it together into something that can be automated and scale.
[+] [-] bkberry352|4 years ago|reply