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As web pages are rolled into the index, the code looks for strings of text that are location references. In particular, text that is formatted as an address is given a high degree of confidence. When an address is found, tokens are added to the index that represents the location. When a “Near Me” search is executed, the engine is told to look for these tokens in addition to the query and adjust the results accordingly.
The best way to ensure that your site is well represented in these results, assuming your site serves a local need, is to add the address of your business or service on the footer of the page you want selected when a user enters a query that you’re service might be able to satisfy. Often, sites will place address information on an “about” page. Unfortunately, these pages often do not rank well with the queries. Because of potential spam issues, we do not want to attempt to infer the location of a page based on tags in neighboring or child pages.
In order to ensure the address is parsed properly you should format the address as in the following example:
1 Microsoft Way Redmond, WA, 98052
Notice the capitalization for the city name and state. Also, make sure the city and state are not separated by any html tags. Following the above simple suggestion is easy and will help users find you with our system.
When a “Near Me” query enters the system uses the user’s ip address to guess their location via a process called ReverseIP lookup. This data is stored in a non-identifying cookie for future searches.
A few comments from surfing a bit on this:
- It appears, at least from my very cursory look into the SERPs, that the results can be easily swayed by strategic placement of address information or even a city/state anchor tag in the context Chicago listed above. Without some additional checks this would seem to lead toward easily manipulated and potentially less useful results.
- With the dozen or so searches I did, it seems that this algo favors the local community directories heavily. This would keep in line with the statement above. i.e. more addresses = higher relevance. Interestingly, I have yet to see any of the IYP listing data or national directories in these results, only the smaller, grass-roots, local directories.
- It doesn't appear that MSN is calculating any type of radius or proximity score based on your specific location versus the result set. If we assume this as MSN's "local solution" and compare it to Google Local and Y's Local, I question if MSN is going far enough to address the needs of the user. The G result is far more useful when looking for a brick/mortar local business which would seem to me to be the primary use of the local tools.
Just a few thoughts...