PageRank, or PR is an algorithm that Google uses to analyze link distribution and connectivity of every website on the Web.
The PageRank algorithm assigns a numeric value from 0 to 10 to every page in its index, which represents how "important" it considers that page. PageRank is calculated by looking at a web page's backlinks, with each link contributing some amount of its own PR.
PageRank is one factor that determines a web page's ranking in Google's search results; however, it has significantly less of an impact than it did several years ago, and is just one of over 200 signals that affect how a website is crawled, indexed and ranked
Named after Google co-founder Larry Page, the original PageRank algorithm was one of Google's early innovations, instrumental to its early success.
PageRank is a probabilistic concept used to represent the likelihood that a person randomly clicking on links will arrive at any particular page. Google considers each link to a web page as a vote; therefore, the more votes cast for a page, the more important the page must be. Pages with many votes and high PageRank will pass along more PR through links.
PageRank is calculated on progression similar to a logarithmic scale. Considering, for the sake of simplicity, that all links are of equal value, this can be demonstrated in table 1:
|PageRank (log base 10)||Votes|
|0||0 - 10|
|1||10 - 100|
|2||100 - 1 000|
|3||1000 - 10 000|
|4||10 000 - 100 000|
|Table 1. PageRank Logarithmic scale|
Google PageRank is a sophisticated algorithm that has evolved since its original version. While most of the mathematical details behind PageRank are unimportant to search engine optimization, some points are worth noting:
Many feel that PageRank is now almost irrelevant—and justifiably so— as Google's ranking algorithms have grown far more sophisticated over the years. As a signal, PR can still be useful for quickly spotting sections of a website where link juice isn't flowing as it should.