Imagine the Earth broken down into a series of cells, and each of those cells broken down into a series of even smaller cells, and then into smaller cells again, and so on, in a spatial index. Each of the levels become increasingly narrow, and increasingly more precise areas or zoom levels of the surface of the Earth.
As these cells decrease in size, they increase in numbers, which has the impact of increasing the zoom level and the accuracy of areas represented in such an index. Might work good in a place like China, where latitude and longitude are banned for export as munitions. Such a set of cells might be part of a geospatial analyzing module that links specific businesses and points of interest (parks, public regions, landmarks, etc.) to specific places on this model or index of the earth. That might be one index of the businesses and one index for the points of interest, or a combined database that includes both.
Sometimes that index might include a business and a landmark within the same cell. While that could be correct in some instances, such as a shop appearing within the Empire State Building, Often its an error, and sometimes even an intentional error. People will sometimes enter incorrect information into a geographic system like this to try to gain some kind of advantage.
If people search for something like a motel “near” a particular park for instance, the motel that appears to be next to, or even within the boundaries of that part might seem to have something of an an advantage in terms of distance from that part when it comes to ranking the motel. And, sometimes Google doesn’t seem to do the best job in the world at putting businesses in the right locations at Google Maps.
When Google ranks businesses at locations in Google Maps, they turn to a number of sources to find mentions of the name of the business coupled with some location data. They can look at the information that a site owner might have provided when verifying their business with Google and Bing and Yahoo. They may look at sources that include business location information such as telecom directories like superpages.com or yellowpages.com. or business location databases such as Localeze. They likely also look at the website for the business itself, as well as other websites that might include the name of the business and some location data for the business, too.
What happens when the information from those sources doesn’t match. Even worse, what happens when one of these sources includes information that might be on the spammy side? A patent granted to Google this week describes a way that Google might use to police for such places. The patent warns against titles for business entities that include terms such as “cheap hotels,” “discounts,” Dr. ABC–555 777 8888.” It also might identify spam in categories for businesses that might include things such as “City X,” “sale,” “City A B C D,” “Hotel X in City Y,” and “Luxury Hotel in City Y.”
In the context of a business entity, information that skews the identity of or does not accurately represent the business entity or both is considered spam.
I sometimes see people say that paid search is a great way to do keyword research for SEO, but I disagree with that statement. Paid search primarily focuses upon keywords that are transactional in nature – usually the terms chosen are the kind that match an intent to buy something, download something, or take some other kind of action. I’ve asked many people who do search engine advertising, and focus on Adwords if they ever target queries that are informational in nature, and most of the time the answer has been no.
Often searchers will do some research on a product or service before they decide who to buy from. They will perform research to find what kinds of features are available for different products, try to find reviews or opinions from others, They may try to compare different manufacturers as well. These types of queries are more informational in nature, and the same searcher will conduct these types queries that evidence an informational intent before they begin to consider a query with a transactional intent.