A Little Light Reading On Google Maps Ranking Factors

From a patent application Google filed in September 2010 entitled SCORING LOCAL SEARCH RESULTS BASED ON LOCATION PROMINENCE

[0047] When the document falls within the broad area (block 460–YES), then a location prominence score associated with the document may be determined (block 470). The location prominence score may be based on a set of factors that are unrelated to the geographical area over which the user is searching. In one implementation, the set of factors may include one or more of the following factors: (1) a score associated with an authoritative document; (2) the total number of documents referring to a business associated with the document; (3) the highest score of documents referring to the business; (4) the number of documents with reviews of the business; and (5) the number of information documents that mention the business. In other implementations, the set of factors may include additional or different factors.

Translation: Ranking factors could include your site’s/URL’s PageRank, the total # of citations that mention or link to your business, the authority of the URL(s) mentioning/linking to you, # of reviews and anything else we can think of.

[0048] The score associated with an authoritative document may be used as a factor in determining the location prominence score for a document. An authoritative document may refer to a document that is identified as being authoritative for the business associated with the document for which the location prominence score is being determined. For example, a group of documents may refer to a business by mentioning the name of the business, the address of the business, and/or a telephone number associated with the business. One of the documents in the group may be more authoritative for the business than the other documents. For example, a document corresponding to the home page of a restaurant may be considered more authoritative for that restaurant than a document corresponding to a review of the restaurant. In one implementation, the link-based score of the authoritative document may be used as a factor in determining the location prominence score for a document associated with the business.

Translation: Your site’s PageRank could be important. Get links/citations.

[0049] The total number of documents referring to a business associated with a document may be used as a factor in determining the location prominence score for the document. As explained above, a group of documents may refer to a business by mentioning the name of the business, the address of the business, and/or a telephone number associated with the business. In one implementation, the total number of these referring documents may be used as a factor in determining the location prominence score of a document associated with the business.

Translation: Get a lot of citations.

[0050] The highest score of documents referring to a business associated with a document may be used as a factor in determining the location prominence score for the document. As explained above, a group of documents may refer to a business by mentioning the name of the business, the address of the business, and/or a telephone number associated with the business. Each of these referring documents may have an associated link-based score. In one implementation, the highest link-based score of these referring documents may be used as a factor in determining the location prominence score of a document associated with the business.

Translation: Get citations from a URL/domain that has a lot of authority in Google.

[0051] The number of documents with reviews of a business associated with a document may be used as a factor in determining the location prominence score for the document. Reviews for businesses can appear in a number of documents, such as newspapers, magazines, web pages, and blogs. In one implementation, the number of documents with reviews of a business may be used as a factor in determining the location prominence score of a document associated with the business.

Translation: Get reviews and get reviewed on a wide variety of sites.

[0052] The number of information documents that mention a business associated with a document may be used as a factor in determining the location prominence score for the document. An information document may refer to a document that provides important information about a business, such as the address, telephone number, and/or hours of operation of the business, reviews and/or atmosphere of the business, whether the business accepts credit cards, etc. Examples of information documents may include Dine.com, Citysearch, and Zagat.com. In one implementation, the total number of information documents mentioning a business may be used as a factor in determining the location prominence score of a document associated with the business.

Translation: Get citations for your business on sites that are deemed “information documents” aka yellow pages sites, local directories, etc.

[0053] In one implementation, the location prominence score for a document may be determined by combining the above-identified factors. The factors may be combined and/or weighted in any manner. For example, the factors may be “squashed” and linearly combined. Squashing is a function that prevents one large signal from dominating the others. Some of the factors may also be normalized, if necessary, to have values between zero and one.

Translation: They were just looking for an excuse to use the word “squashed” in the application.

[0054] Optionally, the location prominence score for a document may be combined with a distance score for the document, where the combined scores will also be referred to herein as the location prominence score. As explained above, the distance score associated with a document may be determined based on the distance the postal address and/or the latitude and longitude coordinate associated with the document is from the location within the broad area (e.g., the location representing the middle of the search area). This factor may provide a better user experience by presenting the user with documents associated with businesses that are closer together rather than scattered apart.

Translation: Location, location, location.

[0055] In one implementation, the location prominence score (with or without the combined distance score) may be combined with a minimal value (e.g., one). This minimal value may ensure that documents that fall within the broad area are scored higher than documents that do not fall within the broad area. This may also ensure that the user is provided with relevant results in the geographical area of interest.

Translation: You best be located in your service area.

[0073] For example, one factor may relate to the numeric scores of the reviews (e.g., how many stars or thumbs up/down). Another factor might relate to some function (e.g., an average) of all the scores of the reviews. Yet another factor might relate to the type of document containing the review (e.g., a restaurant blog, Zagat.com, Citysearch, or Michelin). A further factor might relate to the types of language used in the reviews (e.g., noisy, friendly, dirty, best). Another factor might be derived from user logs, such as what businesses users frequently click on to get detailed information and/or for what businesses they obtain driving directions. Yet another factor might relate to financial data about the businesses, such as the annual revenue associated with the business and/or how many employees the business has. Another factor might relate to the number of years the business has been around or how long the business has been in the various listings. Yet other factors will be apparent to one skilled in the art.

Translation: it couldn’t hurt to be “skilled in the art”

Good luck my dear Watson.