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Using Local Search Marketing Optimization for your Local Business

Posted on 01 April 2010 by scott

Search Engine Marketing  Local Business Linking – Citations” vs. “Links

Most people know backlinks or inbound links from other websites that are similiar to your type of business is critical for ranking well in the organic search engine algorithms such as Google, Yahoo and Bing. Almost any link, potentially even those that are no-followed, can help a website rank higher for terms that its content targets. Get better and more relevant links that use the right keywords in their anchor text, and your website, thus your business will attract more potential sales and clients.

Google’s Local algorithm – Geographically Relevant Documents – Citations” vs. “Links

Seemingly, however, Google’s Local algorithm (the one that populates maps.google.com and helps populate the 10-pack, 3-pack, and Authoritative OneBox) counts links differently than its standard organic algorithm. Local Google marketing uses similiar traditional “link” algorithm to the Local “citation” algorithm. For instance, quality still matters. A citation from your local community college or city hall is going to be infinitely more valuable than one from findbusinessesinyourcity.info. Volume still matters too, in that if your business is listed on 100 websites, all of equal value, and your competitor is listed on 50 websites, all of equal value, you should rank higher (sorry, be more relevant) for a particular search than your competitor.

Scoring local search results based on location prominence

Key location SEO  prominence factors

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. This set may include one or more (a combination) 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;
   5. The number of information documents that mention the business (such as Dine.com, Citysearch, and Zagat.com); and,
   6. The set of factors may include additional or different factors.

Local SEO Term:

A local document – one associated with particular geographic area, which can be associated with a location.

Broad Area – May be identified as being associated with the search query. Is intended to refer to any geographic location that is specified as an incomplete postal address

Advertisement traffic data – When a searcher selects a displayed advertisement, that may indicate that the advertisement was relevant to the search query. The search query and the category of the selected advertisement may be considered training data that can be used to modify or initially train the category classification model in a manner similar to the training performed for query traffic data.

Local Directory listings – Business information may be taken from yellow page type directory listings, such as those compiled by various phone companies. These listings include business categories as well as business names associated with each of those categories.

Query traffic data – Searchers’ selections from searches may be used by the classification component to classify businesses when their query terms are ambiguous. Example: someone searches for “films” and they receive business listings from a “theater” category and a “photographic film” category.

Centerpoint – When scoring local search results, the search engine may identify a location within the geographical area. It may be associated with the location of city hall, downtown, or a geographic center of the area, or based upon some other centerpoint using geographic information. The local search engine identifies all business listings and/or web pages within a predetermined radius of the identified location. The local search engine may then identify those business listings and/or web pages that match the search query. The identified business listings and/or web pages are assigned distance scores according to their distance from the identified location and ranked based on their scores.

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