I was looking at a house on redfin today, and wondered to myself, “hmm, what is their $/sqft rate relative to the local market” and scrolled down to the graph. I had two reactions in sequence:

1) Holy cow, they actual listened to their blog, and implemented it! That’s unbelievable!

2) Of course! These redfin guys really get it, I should have expected them to implement it that quickly.

I think you nailed the solution in the short-to-medium term. I’m so happy that you didn’t do the tick marks in random ranges (eg 237, 261, 285, etc) like some sites.

So, thank you.

We’ll be changing that in the next release. If you’d like the whole story…

Those graphs are used in multiple places. In the first release of those graphs, they were scaled so that range was a little below the max and min values. However, this brought up strange problem. Regions with small changes looked like they were having massive price fluctuations because the small range was being scaled up to fit the graph. It’s like when you see a magnified picture of your skin. It looks like the Grand Canyon. People were having a hard time differentiating between areas that had small fluctuations to those areas with big fluctuations because they weren’t really bothering to read the scale.

So we went to the data display books and many of them said that the only “honest” way to display data like this was to show them at the same scale. Due to the wide range of areas we cover, that meant starting the scale at 0. In reality, we’re not using the exact same scale because the max value still varies. But it did reduce people thinking there were huge fluctuations when in fact there were often times very little.

But it also made it harder to pick out relevant details. So now we’re kinda going back to a middle ground were the scale does not start at 0, but it doesn’t just cover the max and min values either. We pad on either side of the graphs to smooth things out but still let people pick out details.

In the future, we’re thinking of changing the graphs even more to allow user interaction and let you zoom in and out.

John Kim | Product Manager

Along this vein of continually finding small improvements, I have a suggestion on refining your listing page.

Currently you have a $/sq ft line chart on every listing page. You’ve set the baseline of the chart axis at zero, which is normally a good practice for line charts, since variance will be properly put into context of the overall value.

However, in this case, I don’t believe that’s what people are looking for. Customers are comparing that trend to the current $/sqft price of the listing they are looking at.

For example, a customer is interested in how average prices in that zip code have varied from $200-$250/sqft over the last few years, and that it’s currently at $218/sqft but trending downwards, relative to the current listing’s price of $228/sqft.

Thus, a better way to show this graph would be to set the y-axis min a little below the minimum $/sqft relevant for the region, rather than 0.

Yes, we definitely use the lat/long pairs provided by the MLS in some cases. I say some because like you mentioned, the data can be horribly inaccurate, so we only take it from the sources that our testing found to be reasonably close, most of the time, and then only if we are unable to get a geocode of any reasonable accuracy through any other means. This helps primarily with vacant land; it’s other impacts are minimal.

Yes, we do very little hand-mapping in house, usually as a customer support request. We’re investigating whether we can get the user-supplied mappings from Google Maps.

Thank you for the insights you shared! Your theory about smaller MLSs is probably right, and hopefully as the mergers increase the data quality will go up.

It looks like you’ve actually got us beat (slightly!) for SoCalMLS. Do you map the undisclosed address listings there? I’m pretty sure you’re allowed to by MLS rules, but it’s not something we’ve tackled yet.

Do you actually do hand-mapping in-house? Did you know that Proxix (http://www.proxix.com/) has a “hand-mapping” service? It’s expensive, but it might be something you’re interested in.

Overall, your percentage of “ungeocodables” is surprisingly low. I’m really proud of our own system and the geocoding tips we learned in our travels (which I shared with Arthur via email last week), but our percentage of ungeocodables is definitely higher than yours. My suspicion is that a bunch of our smaller MLS’s that have less mapping data available and so it brings down our percentage of geocodeable properties. In large MLS’s though, like SoCal, our geocoding percentage is very high (95.7%).

Many organizations are driven by either grandiose strategic visions (led by MBAs with strategic differentiating blue-ocean leveraging advantages in their starry eyes), or by inward-looking bureaucratic organizations that change by moving people and roles.

The rare trait you show is the power of starting with a basic but extensible product architecture and then continually looking for small, incremental improvements that improve the customer value proposition.

At IBM’s e-business group in the 90s, I remember this being called “start small, grow fast.”

At another client I worked for, we kept on measuring changes by estimate the % improvement delivered. We never wanted a 50%, or 100% improvement to their product; we just wanted to keep finding lots of tweaks and adds that really made the service better. We weekly thought of and implemented, 2%, 4%, 5%, improvements. This rapid iteration (enabled by the flexible product architecture) quickly added up to a truly kick-ass product.

Which is what you have done here at Redfin. Well done sirs, well done.