Best wishes from a Information Visualization blogger and a Multifaith Web analytics’ beginner.

The Excel file only asks for Feedburner (or the equivalent) and Technorati data, where does Alexa enter the equation?

The black hat SEO blog would get many first time visitors but probably not that many return visits which hopefully would show in Alexa rankings.

I have always struggled with how to create a ranking system that is “fair”, one that represents reality.

Any equation I’ve developed fails to represent reality. Technorati tells us what other bloggers think of your content. Alexa tells us what a small sample of folks who use the Alexa toolbar visit. Feedburner stats are intriguing, because it counts subscribers — presumably, the most loyal followers of any blog.

For me, Google represents “customer acquisition”. If Google likes a site, it sends pre-qualified traffic to the site. These visitors might become repeat visitors, e-mail subscribers, or RSS subscribers.

So, there’s lots of important elements that go into a ranking system.

And yet, when you plug in all the “right” pieces of information, you often end up with a ranking system that is very similar to one with a small number of “predictors”.

Ultimately, you try to develop something that is simple, yet captures “what is important”. Hopefully, what Avinash is advocating will provide visibility for the blogs he’s tracking. And at the end of the day, that’s what is really important. It is important to make sure that the folks who provide valuable content get noticed!

Great Work, Guys.

ralf haberich.
http://www.webanalyticsblog.de

Try it. As an example, I just finished several hours counting comments on each of the blogs listed on the top ten.

Thanks Avinash for keeping the conversation respectful and for putting up all the effort that surely goes into producing something like this (not to mention each post you publish).

Alex

Didn’t get a chance to check back into the conversation over the weekend as I’d hoped, but one late observation is that based on the holes in Technorati described by Eric I suspect the margin of error might be higher than 10%, which he mentions above. Yet I do agree with the post someone mentions on his blog that there is no other bar being set to measure your list’s quality against, so this is the best we can get (and it’s really good stuff at that).

But you’ve been given plenty of suggestions for improvement etc, so I’ll let the overall conversation lie (lay?). It does bring up the related question in my mind: Is there a point at which data becomes too imprecise to be any use at all?

If you have a chance to react to that question, great, but not a huge deal if not.

Thanks for the forum,

Nathanael

Further down the road, we could calculate the true influence of comment flow (MIT are doing interesting work in this area) to take away the spammer adder-ons/trackbacks/own replys. Also number of characters in comments total - ie those encouraging real debate end up with lengthy comments on their blogs. And even further on, rating commenters with a visitor generated rating system (thumbs up/thumbs down - for starters). At the end of the day though, I think Avinash’s blog would still be number 1 because he has this unerring ability to make the complex simple :)

Cheers Marianina
http://www.marianina.com

Google does not work. Oh that does not sound any better! My contract is being ripped right now. :)

In this case Google does not work as awesomely as it does in all other cases. Ahhhhh much better. ^)

Seriously though this is a great suggestion (and I think Marshall had suggested this to be a while back), but the problem is that some element of “freshness” is missing.

Both the #1 and #4 blogs in that list have not published anything for the last year (and since both Matt Belkin and Xavier Casanova are thought leaders I think that is our loss not to that their contributions).

I’ll keep a eye out on this and see Google’s algorithm improves for our specific application.

Michael, Judah : Using comments per post is a lovely idea. I am a huge fan of “conversation rate” (more at: How to measure success of your blog.)

The challenge I ran into was that this is easy for me to do on my blog’s wordpress platform but on pretty much all other platforms (blogger, typepad etc) it is really hard for the blog owner to get this number, without actually manually counting it one by one.

You are right about comment “inflation” by blog owner but it is a minor worry. If there is a easy way for blog owners to share their average comments per post in a given time period (say last three months) then I would take it in a giffy.

I’ll ping the blog owners for next round on this one (everyone was exceedingly kind in sharing their feed subs this time, so perhaps this will work after all).

Thanks everyone.

-Avinash.

Judah

Despite the issues I have with Technorati there’s no doubt your blog is #1 no matter how we look at it. :)

I don’t know that I agree with this statement though: “If a blogger chooses to post non-value added content to their blogs then no matter how great they are they will have little “influence”.

I have come across many blogs (not related to web analytics) that have a ton of subscribers and high ranking but no unique content.

Neither Technorati nor Feedburner necessarily say anything about quality. It’s about being in the right place at the right time and about being smart about linking strategy etc. Look at MySpace — you can’t tell me it’s the best, yet it’s huge.

I agree that Dennis should make it to the top ten.

I would like to see your personal top ten favorites as well as the quantitative top ten next time around.

That would add a qualitative aspect to it, even if it’s merely based on your opinion.

=)

Lars

PS. It appears to be a good strategy to write about Google Analytics though there are some clear exceptions to that rule, I don’t think Ian Thomas is writing that much about Google Analytics. ;-)

Certainly an interesting debate.

Here are a few comments by a relatively new comer to this area. I have only recently developed a strong addiction to blog reading (going hand in hand with a personal seismic change from employee to entrepreneur).

Look at how our industry is growing - fantastic to have so many WA blogs. I suspect by next year Avinash would have to publish a Top 50 ranking along side the Top 10.

If the purpose of the ranking is to push everyone to do even better, as Steve suggests, then mission accomplished - great for us readers-only.

The ensuing debate suggests a market opportunity. Aren’t the likes of BuzzMetrics, Cymfony and 1st2c in prime position to set up some standard measurement?

I agree with Eric that accuracy is important.
It seems to me, that reliance on feed subscriptions only wouldn’t necessary give us a true reflection of a blog’s “value” to the reader (I purposefully avoid using the terms “influence” or “engagement” as they will surely land me in trouble).

Sure, TV ratings are predominantly about share of audience – who had more viewers. Reliance on one metric. Is that enough?

Isn’t the recent debate over online measurement all about engagement rather than just visitor numbers. Case in hand – NetRatings adding total minutes per site to their measurements.

Some companies are going to win some might lose. But are we to think that Google is a worse off advertising solution just because on average it gets less total minutes? I don’t think so.

That is why I like Avinash’s idea of using a regression model, relying on more than one variable. I also think that Dennis’ suggestion of Content Relevance should be considered. It makes sense to me.

Avinash, can I suggest adding yet another parameter to your regression formula. How about including the number of comments left by readers? This is a good measurement of interest and engagement with a blog. I’m not sure how easy it would be to collect this data (could be self-reported, same as the feed subscriptions).

I concede that comments may be influenced by short term behaviour as you mentioned in your response to Bhupendra. It will also depend on how active the blogger is responding to readers’ comments and effectively inflating the number of comments.

Actually is that a bad thing? If bloggers start responding even more often to comments than we (the readers) get more of a debate going – surely a good thing.

Am I missing something really obvious? I’m sure you considered this option before.

I intend to post a similar comment on Eric’s blog. So if you do decide to add the comments parameter into your calculation, well, at least my comments would be evenly spread.

Thank you,
Michael

To a large extent, I feel the methods used by yourself Avinash to generate this listing are somewhat secondary. I can make own mind up over which blogs I regularly read and which I unsubscribe from. That doesn’t mean those I unsub are of less value, just of less value *for me*.

Rather, where I feel this Top 10 WA Blogs series offers *real value*, is the explosion of quality blogs in the WA field. And a level of friendly rivalry to help push everyone to do better.
eg Robbin’s efforts to get everyone to shift their feeds and links across. She could have ignored that, but went the extra mile to get everyone to do so. A positive move all round!

This push for excellence. That is the key value we see here.

My 2c of course. :-)

Cheers!

Yes, imagine my glee when Avinash had used linear regression in his new formula, something I think is a pretty good idea. It certainly seems to mitigate at least some of the problems seen in the Technorati-only strategy. But I still think Technorati is far more inaccurate than the 10% suggested in one of the comments above.

Maybe it’s like cookie-based visitor data?

I like your “Content Relevance” suggestion as well — more data is better, plus it lets Avinash use a Google product (oh, except Feedburner is a Google product, never mind ;-) I don’t, however, think Avinash should (or would!) change his methodology because it would make me happy (or Marshall unhappy) … that would be silly!

(But thanks for thinking of me!)

See you in Stockholm and Brussels!

Eric Peterson
http://www.webanalyticsdemystified.com

May I possibly suggest an update for your next list? – that you add a variable derived from the Google Ranking for the search term “Web Analytics Blog” – Assuming there is a decent association, you will be able to provide a list with higher “accuracy” and less dependency on the two variables you have now:

- Influence (Technorati)
- Content Value (FeedBurner)

Google SERP for “Web Analytics Blog”
Matt Belkin’s blog | Inside Web Analytics
Web Analytics Demystified
Web Analytics Blog
Coffee, Sun & Technology
Official Google Blog: The circle of analytics
VisualRevenue | Web Analytics & Affiliate Marketing blog
Web Analytics .be Blog
Occam’s Razor by Avinash Kaushik
Site Visitor Tracking - Web Analytics Blog
Mymotech is Michael Helbling’s web analytics blog

You could call this NEW variable:

Content Relevance (Google)

As this new varibable “punishes” e.g. Marshall – with posts beyond analytics and rewards the somewhat focused posts by Eric. Hence Eric’s 2nd position on the list and Marshall’s 48th position on the list. No offence intended Marshall! (just trying to add a valuable input to the list)

This could principally be valuable on another point as well, namely that this is one list where Occam’s Razor is not at the very top of the list (assuming that your blog is one of those with the highest Technorati and FeedBurner numbers) – and this might even make Eric happy at the same time as well :-)

Dennis R. Mortensen, COO at IndexTools
My Web Analytics Blog

Thank you once again for adding me to your list. This being a not-for-profit (actually with the number of Red-Bull’s consumed to write my blog, it is a for-cost activity) – it is always nice to get some recognition. Keep up the good work!

A comment to Eric Peterson’s comment:

- Hi Eric :-)

When doing regression analysis (and any data analysis in general for that matter) - it is somehow understood that the more observations one provide the better the result (Avinash added, to my knowledge, a large pool of observations beyond the top 10 list itself). At the same time, if using only the FeedBurner dataset, and thus deploying a simple linear regression “analysis” as you suggest - it is again somehow understood that the more variables (that are associated) one can provide the better the result (Avinash added another variable and thus an opportunity to do a multiple regression analysis.

So whether you love Avinash, me or Technorati or think any of them are flawed - does not change much about the fact that from a pure “scientific” point of view – Avinash took the better choice (compared to the old list and also compared to using Feedburner only) and that the list certainly improved.

Cheers
(…And I think I will see you in both Stockholm and Brussels soon, which I am very much looking forward to)

Dennis R. Mortensen, COO at IndexTools
My Web Analytics Blog