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Influence Finder, putting Science into SEO

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The first public presentation of the next generation SEO tool, InfluenceFinder. ...

The first public presentation of the next generation SEO tool, InfluenceFinder.

Using science to filter large lists of URL InfluenceFinder spiders link maps to identify actionable relevant and authoritative sites.

Consider it to be MajesticSEO and Linkscape on steroids

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  • Don’t focus on we found 4 sites…. We found lots of blogs that matter in seconds including these 4. I think this is a really quick slide.

Influence Finder, putting Science into SEO Influence Finder, putting Science into SEO Presentation Transcript

  • Link Building Outside Of The Box The Appliance Of Link Science With
    • To define a scientific methodology that reduces massive lists of potential linking partners…
    • to actionable lists of relevant authorative sites that improve search engine rankings
    Our Objectives
  • Firstly – who’s got most backlink data?
    • Working with Econsultancy
    • We exported the backlink information from Google Webmaster
    • Then looked for commonality of linking domains against MajesticSEO & Linkscape
    Methodology
  • Google Webmaster Tools MajesticSEO Moz Linkscape InfluenceFinder Commonality Linkscape 1,041 Domains 337 In GWM Google Webmaster (GWM) 5,189 Domains MajesticSEO 8,448 Domains 2,051 Domains In GWM 4,123 Domains Refreshed & Enlarged Sub-set Of Majestic SEO 1,681 In GWM
    • Evidence suggests Google Webmaster Backlink Export does not provide all the links that Google knows about
    • We will be producing more research on this as we increase the sample size
    • Either way, the list size is too big
    Learnings
  • Lets clean it with some science Moving Beyond A Big List
    • Fresh Data
      • We had our bots re-index the backlink page data ensuring it’s fresh
      • Our aim is to turn interesting fresh data into useful data for link builders
      • We use a lot of science to filter and clean the list – here are two techniques
    The Science Approach
    • Why
      • Because we know that blogs are good and accessible link targets
    • How
      • Using Decision Trees we can detect blog presence to 94% accuracy
    Finding Blogs
    • When our bots read site source code we use decision trees to maximize the probability of our answer to questions like ‘is this site a blog?’ being correct
    • Statistical techniques like decision trees provide 94% accuracy
    • Using the decision tree technique on the eConsultancy link structure…
    Blog Decision Trees
    • New smaller list
    • 2,723 blogs to be precise (from 8,400 domains examined by our bots)
    • But we wanted to qualify even further
    • We wanted to find those who had a “heartbeat”
    • So lets apply some more science
    Back To Econsultancy Data
    • Filtering sites by their publishing frequency is strong filter
    • So we looked at frequency updates in the eConsultancy linking blogs
    • Also filter by whether feed or natural publisher
    Some Feed, Some Natural Lapsed Bloggers Likely To Be Natural Auto Feed Publishers & Natural High Volume Some Of Our Heartbeat Algorithm
  • Did the science work then?
    • Science can turn large lists of link prospects into accurate, actionable lists.
    • Better lists result in more conversations with the sites that matter
    • Using our science, what took MyDeco a day, took them just an hour
    Conclusion