Rand Fishkin and SEOmoz polled 132 SEO experts with data from over 10,000 Google search results, and have attempted to rank the importance of ranking signals. It’s not confirmed fact, obviously. Google won’t provide such information, but I suppose the next best thing is the collective opinion of a large group of people who make their livings getting sites to rank in search engines, and Fishkin has put together an impressive presentation.
You can view the entire presentation here, but I’ve pulled out a few key slides that basically sum up the findings.
The factors are actually broken down into the following subsets, where each is ranked against other related factors: overall algorithmic factors, page-specific link signals, domain-wide link signals, on-page signals, domain name match signals, social signals, and highest positively + negatively correlated metrics overall.
The results find that page-level link metrics are the top algorithmic factors (22%), followed by domain-level, link authority features (21%). This is similar to the same SEOmoz poll for 2009, but there is a huge difference in the numbers, indicating that experts are less certain that page-level link metrics are as important. In 2009, they accounted for 43%.
Page-specific link signals are cited as metrics based on links that point specifically to the ranking page. This is how the results panned out there:
According to Fishkin, the main takeaways here are that SEOs believe the power of links has declined, that diversity of links is greater than raw quantity, and that the exact match anchor text appears slightly less well-correlated than partial anchor text in external links.
Domain-wide link signals are cited as metrics based on links that point to anywhere on the ranking domain. Here is what the poll looked like in this department:
The report compares followed vs. nofollowed links to the domain and page, finding that nofollow links may indeed help with rankings:
On-page signals are cited as metrics based on keyword usage and features of the ranking document. Here’s what the poll looked like on these:
Fishkin determines that while it’s tough to differentiate with on-page optimization, longer documents tend to rank better (possibly as a result of Panda), long titles and URLs are still likely bad for SEO, and using keywords earlier in tags and docs “seems wise”.
Here is how the domain name extensions in search results shook out:
Here are the poll results on social-media-based ranking factors (which Google has seemingly been putting more emphasis on of late):
Fishkin suggests that Facebook may be more influential than Twitter, or that it might simply be that Facebook data is more robust and available for URLs in SERPs. He also determines that Google Buzz is probably not in use directly, as so many users simply have their tweet streams go to Buzz (making the data correlation lower). He also notes that there is a lot more to learn about how Google uses social.
The presentation itself has a lot more info about the methodology used and how the correlation worked out.
All of the things covered in the presentation should be taken into consideration, particularly for sites that have experienced significant drops in rankings (because of things like the Panda update or other algorithm tweaks). We recently discussed with Dani Horowitz of Daniweb a number of other things sites can also do that may help rankings in the Post-panda Google search index.
About Chris Crum
Chris Crum has been a part of the WebProNews team and the iEntry Network of B2B Publications since 2003. Follow WebProNews on Facebook or Twitter. Twitter: @CCrum237
source :http://www.webpronews.com/google-ranking-factors-2-2011-06
You can view the entire presentation here, but I’ve pulled out a few key slides that basically sum up the findings.
The factors are actually broken down into the following subsets, where each is ranked against other related factors: overall algorithmic factors, page-specific link signals, domain-wide link signals, on-page signals, domain name match signals, social signals, and highest positively + negatively correlated metrics overall.
The results find that page-level link metrics are the top algorithmic factors (22%), followed by domain-level, link authority features (21%). This is similar to the same SEOmoz poll for 2009, but there is a huge difference in the numbers, indicating that experts are less certain that page-level link metrics are as important. In 2009, they accounted for 43%.
Page-specific link signals are cited as metrics based on links that point specifically to the ranking page. This is how the results panned out there:
According to Fishkin, the main takeaways here are that SEOs believe the power of links has declined, that diversity of links is greater than raw quantity, and that the exact match anchor text appears slightly less well-correlated than partial anchor text in external links.
Domain-wide link signals are cited as metrics based on links that point to anywhere on the ranking domain. Here is what the poll looked like in this department:
The report compares followed vs. nofollowed links to the domain and page, finding that nofollow links may indeed help with rankings:
On-page signals are cited as metrics based on keyword usage and features of the ranking document. Here’s what the poll looked like on these:
Fishkin determines that while it’s tough to differentiate with on-page optimization, longer documents tend to rank better (possibly as a result of Panda), long titles and URLs are still likely bad for SEO, and using keywords earlier in tags and docs “seems wise”.
Here is how the domain name extensions in search results shook out:
Here are the poll results on social-media-based ranking factors (which Google has seemingly been putting more emphasis on of late):
Fishkin suggests that Facebook may be more influential than Twitter, or that it might simply be that Facebook data is more robust and available for URLs in SERPs. He also determines that Google Buzz is probably not in use directly, as so many users simply have their tweet streams go to Buzz (making the data correlation lower). He also notes that there is a lot more to learn about how Google uses social.
The presentation itself has a lot more info about the methodology used and how the correlation worked out.
All of the things covered in the presentation should be taken into consideration, particularly for sites that have experienced significant drops in rankings (because of things like the Panda update or other algorithm tweaks). We recently discussed with Dani Horowitz of Daniweb a number of other things sites can also do that may help rankings in the Post-panda Google search index.
About Chris Crum
Chris Crum has been a part of the WebProNews team and the iEntry Network of B2B Publications since 2003. Follow WebProNews on Facebook or Twitter. Twitter: @CCrum237
source :http://www.webpronews.com/google-ranking-factors-2-2011-06
interesting blog. It would be great if you can provide more details about it. Thanks you
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It proved to be Very helpful to me and I am sure to all the commentators here!
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