Bill Slawski of SeobytheSea brings a deep understanding of the underlying techniques that Google & Yahoo have developed to assemble their local data.
Here is his answer to whether Local needs to be held to a higher standard:
Bill: I’m not sure that local can succeed without the actual involvement of people on a local level who have incentive, inspiration, and impartiality to verify, to explore, and to arbitrate.
I think that differences in local language usage and in knowledge of local areas can play a role in whether local succeeds or fails.
Right now, local search involves at least three different paradigms, and methods of collection of data:
1. Providing map information – with an emphasis on purchased data from data suppliers, and from information (mentions) from directories and web sites. The most authoritative site for one of these listings may not even be the web site of the business owner located at an address.
2. Providing a business directory – with an emphasis on listings from actual business owners that is verified by those owners.
3. Providing contact information for a business in Web searches – with an emphasis on identifying the best contact information from a web site. This contact information may only be shown in queries which are identified as navigational ones, where the business listed is, to use the words of the recent Google Relevance testers document, a “vital” listing in response to the query.
The potential for this information to clash is based upon the differences in data collection methods and purposes. For example, the most important information to a telecom is a phone number, and listing an actual physical address is much less of a priority. Nearness to cross streets is fine with them.
Some types of organizations have very little motivation or desire to verify their businesses. Some may not even know that if they don’t have a web site, they can still verify the location of their organization in Google Maps.
There is no set standard way to display location information on a website, and attempts to scrape a site for the “right” contact information may be hindered by multiple addresses (old, new, multiple locations, etc.), poor formatting (images, incomplete data, uncrawlable information, etc.