PageRank for SEO: When Google was launched back in 1998, they introduced a mechanism for ranking web pages that was radically different from how the established search engines at the time worked.
PageRank for SEO
Up to then, most search engines relied exclusively on content and meta data to determine if a webpage was relevant for a given search. Such an approach was easily manipulated, and it resulted in pretty poor search results where the top ranked pages tended to have a lot of keywords stuffed in to the content.
Google radically shook things up by introducing PageRank as a key ranking factor.
Content still mattered to Google, of course, but rather than just look at which webpage had the keyword included most often, Google looked at how webpages linked to one another to determine which page should rank first.
Google’s theory was that a link from one webpage to another counted as a ‘vote’, a recommendation from that webpage for the page that was linked to. And the more ‘votes’ a webpage had – the more links that pointed to it – the more Google felt it could trust that page to be sufficiently good and authoritative. Therefore, pages with the most links deserved to rank the highest in Google’s results.
It’s interesting to note that the PageRank concept was heavily inspired by similar technology developed two years earlier by Robin Li, who later went on to co-found the Baidu search engine. (Thanks to Andreas Ramos for pointing that out to me!)
More than two decades later Google still relies heavily on PageRank to determine rankings. For a long time, Google allowed us to see an approximation of a webpage’s PageRank through their browser toolbar, which included a PageRank counter that showed the current webpage’s PageRank as a integer between 0 and 10.
The Basic Concept of PageRank
At its core, the concept of PageRank is fairly simple: page A has a certain amount of link value (PageRank) by virtue of links pointing to it. When page A then links to page B, page B gets a dose of the link value that page A has.
Of course, page B doesn’t get the same PageRank as page A already has. While page A has inbound links that give it a certain amount of PageRank, in my example page B only gets PageRank through one link from page A. So page B cannot be seen as equally valuable as page A. Therefore, the PageRank that page B gets from page A needs to be less than 100% of page A’s PageRank.
This is called the PageRank Damping Factor.
In the original paper that Google published to describe PageRank, they set this damping factor to 0.85. That means the PageRank of page A is multiplied by 0.85 to give the PageRank of page B. Thus, page B gets 85% of the PageRank of page A, and 15% of the PageRank is dissolved.
If page B were then to have a link to page C, the damping factor would apply again. The PageRank of page B (85% of page A’s PageRank) is multiplied by 0.85, and so page C gets 72.25% of page A’s original PageRank.
PageRank Damping Factor from webpage A to B to C
And so on, and so forth, as pages link to one another and PageRank distributes through the entire web. That’s the basic idea behind PageRank: pages link to one another, link value flows through these links and loses a bit of potency with every link, so webpages get different amounts of PageRank from every link that points to them.
Pages that have no links at all get a basic starting amount of PageRank of 0.15, as extrapolated from the original PageRank calculation, so that there’s a jump off point for the analysis and we don’t begin with zero (because that would lead to every webpage having zero PageRank).
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