Speed comes from quality
After few month of monitoring Technorati rank progress for few hundreds of blogs I was looking for a way to compare the ones who are making significant positive rank shifts. The way Technorati rank work in is that if the value is going down it means that the blog’s position is improving and there are less blogs ahead of it on the way to the top. It is hard to compare rank moves when the variance in rank is so huge.
So I looked at blogs that had more than 50% positive rank change and I started looking at the speed of their progress.
The way I calculated the (average) speed is:
- Speed = Percentage gain (from baseline) / Duration
- Duration = last rank update date – first rank update date (in whole days)
- The units of this calculation is: percentage change in rank/day (or percent per day).
You can see the full table with the results in here (using Google Docs ). :
Blogger’s Speed results – 6/6/2008 (If WP could support (i)Frame it was possible to see this table embaded inside this post, sigh).
Here is a subset of the table:
|url||speed||gain||# days||start rank|
I highlighted (bolded) few of the lines to show how speedy these bloggers are. There are a couple of bloggers like Doug Haslam and Jennifer Leggio (Mediaphyter) that are showing consistent improvement even if they are not the fastest in their group (they have beautiful positive monotonic rising curve) .
The table is sorted by the starting rank (baseline). The blank lines were added between blocks of bloggers that started in a similar rank range.
Note: I assume that the Technorati ranking system is not liner and somehow things are moving faster where the rank is a really large numbers (i.e. at the bottom of the blogsphere). This make it a little harder to compare between blogs with great disparity in ranks ranges yet it only emphasize how great are the bloggers that manage to move fast even at the top. This is not exact math so please take it with a grain of salt. Maybe one day when somebody come up with a different ranking system he can take my approach in consideration.
A couple of thoughts:
- Speed within category – it will be great to compare how different bloggers are doing within their domain of interest/expertise.
- Acceleration/Deceleration – in this method I actually calculated the average speed moving between the baseline rank and the latest. What that I don’t show here is who’s speed is accelerating and who’s is slowing down. This could be monitored as well. One more thing that I can plot to BlogMon (Twitter)
Since I did not make the links in the table clickable I added them below (you can also click on the link from the Google doc table:
http://travellperkins.com, http://www.multichannelmetrics.com, http://blog.francinekizner.com, http://doughaslam.com, http://www.four20.net, , http://mediaphyter.wordpress.com, http://www.seotops.com, http://www.purplecar.net/, http://www.twitterholics.com, , http://learntoduck.com, http://daisysdeadair.blogspot.com, http://dossy.org/, http://www.prfekt.se, http://gobigalways.com, http://www.socialmediaexplorer.com, http://bing-thegreeninme.blogspot.com, http://sixrevisions.com, http://www.veronicabelmont.com, http://daily.mahalo.com/, http://thenextweb.org, http://www.bloggerbuster.com, http://blog.twitter.com, http://laughingsquid.com, http://www.37signals.com/svn/, http://refueled.net, http://www.blogher.com, http://blogs.abcnews.com/politicalpunch, http://www.designspongeonline.com/, http://blog.makezine.com, http://www.mixx.com
So who do you want to put your bet on?