LocalRank is a Google-patented method for displaying more relevant sites to users. The LocalRank process consists of an algorithm that processes various signals from websites and presents to the user, search results that are helpful and relevant to their search. The term LocalRank refers to the arrangement of the results and the algorithm, which probably works in the background. Google has not officially confirmed this. However, it is assumed that the LocalRank algorithm has been applied together with other signals for several years.

A special feature of LocalRank is the revaluation of websites. A part of the traditional index with up to 1000 websites is extracted and subjected to a check which analyzes the interlinking between the extracted websites (local interconnectivity). The results of this analysis then flow into the newly generated index. The information from the SERPs processed by LocalRank are displayed in a modified index after they have been reweighted using interconnectivity. The ranking of the sites shown here can differ significantly from the general ranking.

General information[edit]

Against the background of a growing Internet and the increasing mobile use of online services, the delivery of relevant results is critical for every search engine. Google registered in February 2003 a patent, which reevaluates information in an index on the basis of linking data. This is basically exactly what happens in the Page Rank process, hyperlinks between websites are used for the evaluation.

The difference with LocalRank is that the entire index does not serve as the data base, but only a certain part of it. The most relevant results are summarized and rearranged by an analysis of the links within the dataset that way. LocalRank is said to have been a part of the Florida update to prevent simple cross linking and link spam.

How it works[edit]

The functionality of LocalRank is similar to that of PageRank, but the dataset is limited to the first thousand sites in the index. This dataset is also referred to as a corpus, which serves as the starting point for further analysis. The size of the corpus is not known. Estimates range from up to a thousand websites.

When a user enters a search phrase into the Google search engine, they are given sites that are stored in the index and are organized in a specific manner. This result is called Old Score. In the course of LocalRank calculations, the hierarchy of the Old Score is changed by checking the first thousand results more closely. This analysis focuses on how many inbound links refer to a domain. The focus is therefore on the linking structure in a limited dataset of about one thousand websites. Each site from the dataset now receives a local score that indicates how relevant a site is relative to the other 999 sites. The local score is a measured value, which is supposed to represent the local interconnectivity.

A second ranking is now achieved with the data obtained and the mathematical linking of the Old Score and Local Score by an algorithm. The Relevance Score redistributes the results of the analysis and outputs a changed ranking to the user. The most relevant websites from the dataset of the one thousand websites are displayed higher up in the ranking than the original index. It is assumed that other signals, factors, and circumstances are used to calculate the results. These include, for example, various on-page factors of a website, accurate Google My Business Profile, geodata such as languages ​​and IP addresses, or positive customer reviews.

An overview of the LocalRank procedure:

  • Ranking: The usual data that matches a search term or a search phrase are included as part of the Old Score, which is the basis of the calculation.
  • Re-ranking: A subset of the Old Score is re-arranged in the original dataset, taking into account interconnectivity. The result is described as a local score.
  • Relevance Score: The Old Score and the Local Score are combined to form a new ranking. These results are included in the final ranking. The data from the PageRank and the relevance score ultimately result in the SERPs, which are displayed to the user after entering a search phrase.

Relevance to search engine optimization[edit]

It is unclear whether and to what extent Google uses LocalRank. Doubtless, some aspects of this algorithm are used to calculate the search results because the relevance of a search result obviously depends on many different factors. Site-based information, local Google My Business profiles, and consistent information such as names, addresses, and phone numbers (NAPs) are local ranking factors, for example, and have been proven as such in various studies.[1]

Region-specific domains (ccTLDs), new top-level domains (gTLDs), and geo-based information in the webmaster tools will most likely affect the local score if it is used.[2]

However, what signals are actually used by Google is still unknown. Only the basic operating principle of the LocalRank is described in detail in the patent which was filed.[3] In addition, Google recommends the creation of a complete business profile and various on- and off-line activities that indicate the ownership of a website by a company.[4]


  1. The 2015 Local Search Ranking Factors moz.com. Retrieved on October 27, 2016
  2. Working with multi-regional websites webmasters.googleblog.com. Retrieved on October 27, 2016
  3. Ranking search results by reranking the results based on local inter-connectivity patft.uspto.gov. Retrieved on October 27, 2016
  4. Improve your local ranking on Google support.google.com. Retrieved on October 27, 2016