You must login or register!
Inbound.org uses Twitter to register and create accounts. Your Twitter handle will also be your username here on Inbound and registration/login will enable you to submit content, post comments and create/edit your Inbound profile. Use the button below to verify your Twitter account.
Login or Register
Excellent work here.
Great study.
Thanks for the support Michael.
It's interesting to read, but what exactly are the data correlated *with*? Seems to be some measure of SEO, but I'd like to see the exact metric that's being used mentioned in the charts that display the correlation. All in all, very interesting!
Hi James Sorry for not being more clear, the data is correlated against rankings i.e. how well are exact match domains correlated to ranking well in Google? The way the formula works is you feed in two sets of rankings, one set is obviously the set of rankings in Google e.g. #1,#2,#3,#4, etc. and the second set is the factor you are testing so for exact match domains 1 would represent if it was an exact match domain and 0 if it wasn't.
Only complaint is one factual thing - the co.cc block was a domain-level, not TLD-level penalty. Otherwise classy work detailing the minor downfall of exact-match. Would you also have Clickthrough data to control against