Google Maps: Google Local Search Mashup

This video shows how to combine a Google Local Search with Google maps to do things like look for restaurants around a specific address.

Business Profile Pages in Google+ (Google plus)


Jeff Huber, Google VP of Local and Commerce, has indicated that Google+, at some point in the near future will include the option for business profile page. Here is his comment:

And pre-emptively answering a question — yes, we will have (smb) business profile pages on Google+. I can’t announce a launch date yet, but we want to make them *great*, and we’re coding as fast as we can.

He has additionally indicated that he will be using Google+ as his primary voice (not Twitter) and that, if we let him know, he will make invites available for the Google+ field trial to anyone that needs one.

I am not sure what I think about the idea of having a second SMB profile in addition to an already claimed Places page (it is early, I am on vacation and typing on a bad cell signal on my iPhone but wanted to get this out).

Obviously a large number of small businesses have yet to figure out Places and the idea of a second “Places” is somewhat daunting unless it is well integrated into the existing processes. In the end, I suppose that it comes down to the benefits that an SMB would derive as to whether it will be worth it. It is certainly an interesting idea.

If nothing else, Jeff putting up with my tweaks and providing this information, demonstrates the possibility of a coming transparency from the folks at Google Local (hooray!!).

How does Google create and maintain/add location records for database?

The question “How does Google create and maintain/add location records for their “Google Places” database?” was asked recently at Quora. I am reproducing my answer here so that readers who are new to the blog can get some background information on Google Places from a high level view:

Google obtains records for their business listings from

  • the major list dealers like InfoUSA,
  • feeds from trusted sources like CityGrid,
  • scraping trusted structured websites like Superpages or BBB,
  • scraping less trusted and less structured directories,
  • user input via their MapMaker product and Community edit of unclaimed listings in Maps,
  • across the web in general,
  • and business claimed records via the Places Dashboard.

This data is essentially triangulated to create the Places search result.

Every time that they identify a unique PHONE/business/address/ combo they create what is known as a cluster into which all structured and unstructured known data about a business is placed.

The data that can be normalized is normalized and matched against the same field from all the sources. If there are discrepancies Google will resolve which is accurate by picking the data from the most trusted and most recent sources. Strong preference of trust is given to data from their own claiming process which requires direct post card verification. If a listing is unclaimed preference is given to verified lists like those of InfoUSA and then to trusted feeds and on down the chain of trust.

They do often end up with two clusters that are essentially identical or only differ in small details. They run a merge/purge that merges these two clusters into one. This system uses not just geographic signals but language similarities as well to decide if two listings should be merged. Errors and lack of granularity in this function can lead to merging of two unrelated businesses that are located physically close to one another and happen to be in the same line of work. If the system fails to merge two records, a business listing might lose rank as the cluster data is split between two records. At this point in time there is NO formal mechanism to unmerge two merged listings although there are some off-Google techniques that might accomplish it. This is known among the cognoscenti as a “Cluster-F**k”.

Here is an article that summarizes their clustering technology