This is a fun little passion project by Airbnb-engineer Andrew Pariser and someone known as Potch. The way it works is that it shows you a picture of a recently sold property, and you have to guess what it sold for. You get a bunch of guesses, and after each one, you are given more information about the property and some feedback on how close you are. To win, you need to get within 1%.

When I tried it out, my initial guess was way off (too high). Toronto has trained me well. I also wasn't sure where Evansville, Indiana was, so that bit of information didn't really help me. But the arrows telling me I was way too high, certainly did. The reality is that it's pretty hard to guess the value of a home if you don't know where it is, you can't see interior photos, and you generally don't have enough information.

But what if you were from Evansville, Indiana and what if you did have enough information? I bet that the guestimates would actually be pretty accurate. This idea of crowd-sourcing market information and pulling wisdom from crowds has long interested me, because price discovery is a major pain point for real estate. Sure you can look at comparable sales and current listings, but that is not an exact science. Neither are algorithms.

But what if there was a way to test the market and get pricing feedback before you actually list? Would you trust it more than Zillow's algorithm? This is something that I'm working on testing right now through a passion project called Unlyst. Myself and a few others are working on a very simple product that will be released this fall. If you'd like to follow along, sign up here.

The responses are still coming in from yesterday’s real estate marketplace survey, but I wanted to thank everyone who took the time to complete it. I really appreciate it. I was reviewing the responses this morning and I thought there were a couple of interesting takeaways.

First, most people who own a home have at one point or another thought about selling that home. And even the people who haven’t thought about it, said they would be willing to sell under the right circumstances. That is, they would sell for the right price, for a better place, and so on. At the time of writing this, nobody said they would never ever sell.

I think this is interesting because, even though the real estate market is a highly illiquid market, my hunch is that it could be made a lot more liquid with the right frameworks in place and if the barriers to selling could be reduced.

And sure enough, many of the folks who said they have thought about selling (but haven’t yet), said it’s partially because it’s too expensive and too much work to sell. But in addition to these barriers, two other points emerged that I hadn’t given a lot of thought to before – but make total sense. 

Homeowners also said that they haven’t sold because they’re too emotionally attached to their home and because they’re afraid they won’t be able to find another place to move into. 

Because of how illiquid the real estate market is and because home transactions are typically asymmetric (that is, buying and selling are independent actions), there appears to be a real concern that you could sell your home and never find anything better.

And since a home is such an emotion filled asset (as opposed to, say, a stock), people are naturally afraid of making the wrong choice. But then that begs the question: Are we, as real estate consumers, being left with suboptimal outcomes because we’re simply too afraid of the making the wrong choice?