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There's plenty of money in it. Imagine if you could price the house correctly out of the gate, reducing the amount of time the home stays on the market. It is indeed a hard problem to solve using ML.

You'd need a few other things:

8. Floor count

9. Size and location of the bedrooms, bathrooms, kitchen

10. In-unit laundry (mostly for condos)

11. Proximity to neighbors

12. Existing tree coverage and other landscaping

13. Proximity to trails, transit, and other mostly-fixed landmarks

... I'm sure I'm missing many more.



Real estate is not liquid enough that a 'correctly' priced house will sell immediately. You have to wait for a buyer that wants the exact featureset that house is offering.

Real estate has sort of a weird duality where it's viewed as a commodity in aggregate - but it is definitely not a commodity good to the individual buyers looking at houses.


In the Bay Area at least, you really cannot discount the Feng Shui attributes of a home [1] and I don't think there is any MLS type of database that takes this into account.

[1] http://blog.pacificunion.com/proper-home-design-crucial-chin...


Opendoor does exactly this?


It's significantly more complicated, but at Opendoor we act as a market maker for real estate by doing this.

We sell our homes far faster than the market in Phoenix, without sacrificing on price.




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