Marketing & Advertising

PageRank: What Is It? And How Do You Calculate It?

PageRank Passing Ranking Power via Links
Google’s PageRank technology plays an important role in how online stores show up in search results. Understanding how this ranking system works will help ecommerce merchants improve their search engine optimization (SEO) and potentially increase website traffic.

PageRank is a proprietary mathematical formula (algorithm) that Google uses to calculate the importance of a particular web page/URL based on incoming links. The PageRank algorithm assigns each web page a numeric value. That value is a particular URL’s PageRank.

The underlying assumption is that links are analogous to “votes” for a page’s importance. The more votes a page has, the more important it is. What’s more, votes from important pages/URLs have more weight than votes from unimportant ones.

In this Ecommerce Know-How, I will (1) discuss why PageRank is important and (2) provide an explanation of how to use a simplified PageRank calculation to make sound SEO decisions about internal linking. In all, this article should give you a foundational understanding of this ranking system. And in future installments of Ecommerce Know-How, we will build on this fundamental PageRank information and apply it to SEO techniques like bot herding or siloing.

The Importance of PageRank

“Using PageRank, we are able to order search results so that more important and central Web pages are given preference. In experiments, this turns out to provide higher quality search results to users,” wrote Google’s founders Larry Page and Sergey Brin (along with Rajeev Motwani and Terry Winograd) in their January 29, 1998 paper, The PageRank Citation Ranking: Bringing Order to the Web.

In spite of this paper and the complex calculations it included, Google’s exact recipe for ranking web pages is not public information. But there is enough data available to make some educated guesses and assumptions about the PageRank algorithm and a search engine’s basic procedures.

Our search assumption goes like this: Jack starts a search for the phrase “golf clubs.” Google first seeks relevant pages that include content matching Jack’s query. Once Google has located the relevant pages, it ranks those pages based on importance—that is PageRank. The first page/URL listed on the Google results page had the most PageRank out of all the pages that were relevant to Jack’s search query. The last page/URL listed had the least.

Good content that matches a search query determines whether a given web page/URL will be included in Google’s results. But PageRank determines the order relevant pages are shown in.

PageRank is important then because it will determine if your site shows up first or last when a potential customers looks for your keywords.

Google’s Search Procedures

  1. A Google user submits a search query.
  2. Google searches all of the pages/URLs it has indexed for relevant content.
  3. Google sorts the relevant pages/URLs based on PageRank scores.
  4. Google displays a results page, placing those pages/URLs with the most PageRank (assumed importance) first.

Simplified PageRank and Ranking Power Estimates

PageRank formula

Google does not disclose its exact PageRank formula. But it is a pretty safe bet that calculating PageRank is not easy math (note the “simple” PageRank formula at left).

The folks at SEOmoz have come up with an excellent guess about the PageRank algorithm in their paper, The Professional’s Guide To PageRank Optimization. And I recommend that paper for site owners that want to know how to estimate a page’s actual Google PageRank and don’t mind spending $39.99.

But when it comes to making certain good choices about SEO (particularly internal linking choices), you don’t really need to know a URL’s actual Google PageRank. Rather, a simple model that estimates the effect of one SEO strategy or another is just as good. For example, you’ll be able to compare two different internal linking strategies, estimating how each one will affect a page’s rank, without having to employ higher mathematics.

Our simplified PageRank modeler looks like this:

PageRank for a given page = Initial PageRank + (total ranking power ÷ number of outbound links) + …

PageRank Figure A
Google assigns every new web page an initial PageRank score. For the sake of our example, that initial PageRank will be 1. If I create two new product pages, page A and page B, those pages would each have an initial PageRank of 1.

A link from page B to page A would effectively be a vote for page A’s importance, and that vote would increase page A’s PageRank to 2—page A’s initial PageRank plus the value of page B’s vote. Page B’s vote is worth its PageRank and is called ranking power.

If we add a new page C, and page B also linked to it, page A’s PageRank would fall from 2 to 1.5 while page C’s PageRank would rise from 1 to 1.5.

Adding more links from page B to either page A or page C will not change things, since only one link from page B to page A distributes ranking power. A second link would not add additional ranking power.

PageRank Figure B

With just this simple model, we can now start to test some SEO tactics for internal linking. Simply plot out two or more scenarios, adding up each page’s PageRank to determine which tactic will work best for a given goal.
For example, let’s imagine that your ecommerce site has five pages, including a home page, a category page, and three product pages, what is the best navigation strategy if your goal is to boost your category page’s rank?
Interconnecting every page would give the category page a total PageRank of 2 as in Figure A.

Linking product pages to the category page only as shown in Figure B, would result in a PageRank of 5 for the category page, making it the better choice.

Summing Up

In this Ecommerce Know-How, I explained why PageRank is important and provided a simple model for estimating PageRank for internal linking tactics. This model is not faultless, but it should help you make informed choices about the SEO tactics you use.

PageRank Video

PageRank Resources

Armando Roggio

Armando Roggio

Bio   •   RSS Feed