Earlier quoted context omitted.
Can you not imagine how useful it is to know user data e.g. what neighborhoods receive the most clicks, what type of homes generate the most favorites, how long people view one listing vs. another, … that is unrelated to public MLS data?
> Can you not imagine how useful it is to know user data e.g. what neighborhoods receive the most clicks, what type of homes generate the most favorites, how long people view one listing vs. another, … that is unrelated to public MLS data? Click data is much less valuable that the recent sale price data available in MLS. Using 90s style dwell time and click counts would likely yeild a lot of very noisy data. False po…
Zillow lost money because they weren't willing to lose money
91–100 of 386 posts
Re: Zillow lost money because they weren't willing to lose money
#92> At a high level, the story of Zillow Offers is a story of our industry at its best. Not in my book. All I see is the price of real estate being driven up by corporate greed and the individual home-buyer being shut out of the market. Is it wrong of me to hate "flippers" (be they corporate or private)? Pure capitalists will tell me that every property sold went to the highest bidder — in the case of a flipper winning…
flippers make the real estate market more liquid, in the same way high-frequency trading does for stocks. Flippers take the risk of the market falling while they're flipping - that's the price they pay for their profits.
Re: Zillow lost money because they weren't willing to lose money
#93Earlier quoted context omitted.
You'll have to educate me then: is more liquid better for the buyers or sellers?
Here’s a thought experiment: if I told you the market was going to be less liquid and you may not be able to easily sell the house you’re about to buy, wouldn’t that change your behavior? I think you’ve bought into the tik tok narrative that somehow it’s zillows fault that houses are expensive.
No. Like a normal person, I bought my house to live in and to improve and to stay in for a long period of time. It isn't a speculative investment vehicle.
Re: Zillow lost money because they weren't willing to lose money
#94> They thought they needed to build a machine learning model when they really needed to build an entirely new organization, one that possessed the technical and cultural mindset necessary to succeed in this space. I totally agree. It's not impossible to imagine their model working: why couldn't you serve as a market-maker for homes at a large scale, especially with the unique insights Zillow could have based on their…
> a market-maker for homes at a large scale…a house-flipping company These are different things. Archetypal market making involves simultaneously buying and selling an asset. Flipping involves buying, improving and later selling. One might be able to deal with the heterogeneity of houses by operating at scale. (Zillow attempted this.) One might also deal with the delay between buying and selling by hedging. (Zillow n…
Does it? I worked for a few years for a market maker, and that's not what we did. Simultaneous buying and selling is what the arb guys did. We'd buy and sell with generally short hold times. Which makes sense to me given that the exchange has market makers to provide liquidity. If something can be simultaneously bought and sold, then the market-maker is unnecessary.
Re: Zillow lost money because they weren't willing to lose money
#95Earlier quoted context omitted.
You'll have to educate me then: is more liquid better for the buyers or sellers?
Both. In an illiquid market, it takes a long time to find buyers or sellers. You are incentivized to overprice (if selling) or underprice (if buying) and wait a long time to see if someone will match you. A liquid housing market means people can buy or sell the house at the "right" price without waiting many months or years. As a seller, would you rather wait a year to make a bit more money? That wouldn't be good. Th…
Re: Zillow lost money because they weren't willing to lose money
#96Earlier quoted context omitted.
You'll have to educate me then: is more liquid better for the buyers or sellers?
Here’s a thought experiment: if I told you the market was going to be less liquid and you may not be able to easily sell the house you’re about to buy, wouldn’t that change your behavior? I think you’ve bought into the tik tok narrative that somehow it’s zillows fault that houses are expensive.
It would not change my physiological need for shelter, no
“Oh I might not be able to sell this for a profit in two years, guess I’ll die in the street”
Re: Zillow lost money because they weren't willing to lose money
#97Earlier quoted context omitted.
I would say the opposite is true. Dying companies are stuck in their own routines because they're trying to automate their poorly designed processes that require humans at multiple steps. Smart companies are designing newer, better processes that are enabled by tech. Starting from scratch can be a huge advantage.
Personally, I would treat the GP's mindset of "inventing workflows" differently than your mindset of redesigning at "poorly designed processes". Yes, a poorly designed process sucks but it works at some level. That means the rough flow of it is figured out. Yes, there are exceptions and complications and all kinds of odd things but it's fundamentally different. It's not "from scratch" as you're taking an existing wor…
But if you are trying to solve a novel problem, and the proposed solution involves "ML will magically predict the future", you'd better have a very good idea of exactly how the problems will be solved, or else you're probably better off starting with good old-fashioned human intelligence.
Re: Zillow lost money because they weren't willing to lose money
#98Earlier quoted context omitted.
> a market-maker for homes at a large scale…a house-flipping company These are different things. Archetypal market making involves simultaneously buying and selling an asset. Flipping involves buying, improving and later selling. One might be able to deal with the heterogeneity of houses by operating at scale. (Zillow attempted this.) One might also deal with the delay between buying and selling by hedging. (Zillow n…
> Archetypal market making involves simultaneously buying and selling an asset Does it? I worked for a few years for a market maker, and that's not what we did. Simultaneous buying and selling is what the arb guys did. We'd buy and sell with generally short hold times. Which makes sense to me given that the exchange has market makers to provide liquidity. If something can be simultaneously bought and sold, then the m…
Archetypal, not predominant.
> Simultaneous buying and selling is what the arb guys did. We'd buy and sell with generally short hold times
The ideal market maker is arbitraging (and eliminating the arbitrage-able inefficiency). That’s why humans were replaced by faster-trading machines everywhere they could be. In most cases, the arbitrage is synthetic or approximate, e.g. hedging an options or swaps book. But a fundamental separation between speculating and marketing making is the latter does not take a view on the assets per se, and should not be betting on their future price movement.
No market maker always achieves the ideal. But they tend towards it. Zillow didn’t have that tendency. In fact, they erected fundamental obstacles between themselves and that ideal.
Re: Zillow lost money because they weren't willing to lose money
#99> They thought they needed to build a machine learning model when they really needed to build an entirely new organization, one that possessed the technical and cultural mindset necessary to succeed in this space. I totally agree. It's not impossible to imagine their model working: why couldn't you serve as a market-maker for homes at a large scale, especially with the unique insights Zillow could have based on their…
Re: Zillow lost money because they weren't willing to lose money
#100I really liked this quote, which is also true of machine learning organizations at large tech companies: The most valuable data is not social data, ... but your own data because every dataset that you’re looking at internally describes your own process, including your bugs, ... building models from your own data is the only way to build a really successful system. This is one thing that a lot of outsiders do not unde…
Yeah, I'm gonna say that romanticizing mass surveillance is a bit much. Cambridge Analytica, the five eyes countries, Clearview - all these are using Facebook and Google's data to great effect. Facebook and Google's data are not their own. That data is comprised of private lives, stripped bare pixel by pixel, bit by bit, and it's offensive to frame it as if they're doing something alchemical and special with it. Goog…
You’re also absolutely right that the social media content: the photos, the sentiments, the likes, the connections, should not in any way “belong” to FB/G.
The data that does belong to them, and that is useless to anyone else, are the outputs from their sentiment analyzer service, the weights and trigger conditions for their content ranking algorithms, the intermediate outputs of their ML evaluations, etc.
GP, and the article, are saying: look there first. Try to start by truly understanding “what you already know, but aren’t paying enough attention to,” and don’t just treat the problem as “needs more data.”