Fast Feedback

A9 Yellow Pages 1369

This morning’s buzz on the web seems to be centered around a9′s new Yellow Pages feature, which tries to show photos of the businesses alongside their results. How did they get all these photos? Basically, they had trucks with side-facing cameras and GPS units driving down the major commercial thoroughfares in a bunch of cities, and the system tries to roughly match up the geocoded address with the photos taken near that location. (As Russ Beattie points out, this has been done in Spain before, but not with this level of grace in the U.S.) If you know anything about GPS, you’ll realize that this process isn’t very exact, and indeed most of the photos of Cambridge businesses were about a block off their intended targets.

A9′s saving grace here is that they provide an incredibly painless way for users to correct the listings. At the bottom of the screenshot above, there’s a smooth javascript-driven row of images that you can use to pan down the street, and in a single click, assert that one of the particular photos is in fact the correct photo of the business—without going to another page, without signing in, without hassle. In my own projects like buskarma, I’ve learned the value of fast feedback—if you can present users with a minimal interface at the exact point at which they notice an inconsistency or failure of the system, you can often skim nice, targeted content improvements off the top of the user’s brain.

In A9′s case, once I corrected the entry shown above, it immediately started using that photo as the definitive one. It didn’t, however, update the thumbnail in the search results listing (I assume that’s cached). It also didn’t give me a way to assert that the photos were of the wrong side of the street for the business I was looking for. Finally, it didn’t make any attempt to re-interpolate the locations of the nearby businesses based on my assertion. Still, the mechanism is a great Wikipedia-style way of having the legions of web users who are undoubtedly kicking the tires of this service today improve the results as they go along.

Road Editor

Oh, and by the way, A9′s not the only one who’s been driving around with photo trucks. Peep this screenshot from a collaborative GIS demo that I helped put together for a northeastern state which just happened to have yearly drivethrough data for all of its state roads. Track me down at ETCon if you want to see it in action.

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  • Josh

    Do they state where they get the photos from? Almost all 50 states have federal highway funding to take photos of every 10 meter stretch of their state highway network. These photos are usually taken with digital cameras mounted looking forward and at a 45 degree angle to the right. The trucks/vans that have these cameras mounted on them usually drive in both directions on an annual basis (per the federal funding guidelines). These photos are in the public domain and are tagged with location information. It would not be hard to imagine A9 or others getting a hold of these and applying them. Incidentally, many local municipalities are doing this too as part of neighborhood redevelopment activities.

    A few examples of such projects:

    The 45 degree angle to the right data from these photologs may be of the most interest to folks trying to associate photos to properties.


  • Joe

    From the stories I read, they were using their own trucks to gather proprietary data. The fact that there’s a bunch of public data out there is heartening, though, as it allows for scrappier operations to conceivably compete on data about what is literally their home turf.

  • Joe

    Oh! I just noticed something that I had missed when I posted that A9 screenshot. The star on the map is totally in the wrong place—so I guess it’s not so much their matching of photos to locations which is off, but more that their geocoding is wrong in the first place. (And that it’s for a business whose name is its address is particularly amusing.)