seo

There Must be a Better Metric for Blog Influence Measurement

As I noted early this week, there’s a lot to be desired from blog ranking and measurement tools. Technorati’s measure of influence via links is the most common method used, followed closely by Alexa data (which can be badly skewed, particularly when the URL is inside a much larger host).

At SEOmoz, we used several key indicators of value – links, subscribers, tagging and traffic to compile the following comparative list of bloggers in the SEO space:

Influence Score URL
0 http://spaces.msn.com/search-science/blog/
48 http://equitymind.blogspot.com/
61 http://searchquant.blogspot.com/
77 http://www.searchrank.com/blog/
77 http://thelinkspiel.blogspot.com/
89 http://www.chinawhite.net/
95 http://mcanerin.blogspot.com/
105 http://www.insearchofstuff.com/
133 http://www.mikegrehan.com/
134 http://www.grayhatnews.com/
162 http://www.searchenginecollege.com/blog.htm
170 http://www.fantomaster.com/fantomNews/
180 http://www.seoresearchlabs.com/blog/
182 http://www.oilman.ca/
192 http://www.cre8pc.com/blog/
202 http://www.seobythesea.com/
213 http://www.seo-scoop.com
233 http://www.linkbuildingblog.com/
233 http://www.socialpatterns.com/
302 http://www.webguerrilla.com/
312 http://www.jimboykin.com/
327 http://www.davidnaylor.co.uk/
374 http://www.marketingpilgrim.com/
388 http://www.wolf-howl.com/
406 http://www.searchengineblog.com/
419 https://moz.com/blog.php
463 http://www.traffick.com/
493 http://www.stuntdubl.com/
657 http://blog.v7n.com/
693 http://jensense.com/
1,269 http://www.searchenginejournal.com/
1,316 http://www.seobook.com/
1,322 http://www.threadwatch.org/
1,540 http://www.seroundtable.com/
1,904 http://blog.clickz.com/
2,178 http://performancing.com/
2,538 http://www.mattcutts.com/blog/
2,754 http://blog.searchenginewatch.com
2,805 http://www.resourceshelf.com/
2,833 http://blog.outer-court.com/
2,933 http://battellemedia.com/
3,001 http://jeremy.zawodny.com/blog/
3,038 http://scobleizer.wordpress.com/
3,874 http://www.webmasterworld.com/robots.txt

My feeling is that the data we’ve compiled is not particularly valuable, though it may work well for some comparative purposes. The score above is based on Alexa reach data, Alexa page views, Technorati links, Yahoo! links (to the direct blog URL only), the number of del.icio.us tags and the number of subscribers via Bloglines.

Is Todd Malicoat really 5X more influential than Shak? Is Michael Gray 10X more influential than Joe Morin? These aren’t questions with solid answers and I’m not sure that the data above, even if we were to come up with a better equation for the final product, is really valuable for making these types of assumptions.

What this formula does show that I like is a relatively accurate picture of daily readership. My guess is that with a few exceptions, an exact traffic-measured pattern of each site would follow at least the ordering, if not the exact percentages. For example, I’d guess that Jeremey Zawodny and Robert Scoble are slightly better read than John Battelle and Philip Lenssen, and that Donna Fontenot and Bill Slawski get very similar levels of traffic.

Perhaps, in the future, someone will develop a tool that can query enough sources of data and account for enough variables to make this process more valuable. For now, however, we won’t be pursuing a tool to automate this kind of comparison and analysis… the value just isn’t there.

I’d love to hear your thoughts on automated blog comparisons, though and how you feel about the value of the data. For those interested, the full spreadsheet in OpenOffice 2.0 format is available online.

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