Photo Credit: Graeme Lloyd, University of Bristol

This image, a so-called “super-tree”, shows the relationship of 440 of the 600 known species in the Dinosaur family. It was created as part of a study with the goal of determining the various rates of diversification within the tree. You can read a nice summary of the research at Science Daily. But seriously all the chatter about Social Graphs that use a similarly formatted chart and I have to wonder, who has one as cool as this?
 

But I have to wonder…
Is Eric opening a content mall for web analytics?

• 39.13% of respondents own all 3 of Eric’s books
• 39.13% of respondents own two of Eric’s books

Channeling a marketing director I used to work with, I could say, my site has a top two box score of 78.3%. That’s pretty darn good although not the nirvana of 80+%.

• 13.04% of respondents own just one of Eric’s books
• 8.7% of respondents did not own a single book (maybe they do now )

- Respondents are 4.5 times more likely to own two or three books than they are to own none

- Respondents are 3 times more likely to own two or more books than they are to own just one

So when Eric complains that none of my referrals are purchasing books, I can say, “Fine, write a new one, most of my readers already own the others already.”

If we combine respondents that own one, two, or three of the books we’re talking about 91.3% of all respondents. In other words, you dear readers are not the target for Eric’s book selling any more unless he writes a new one.

A big thanks to everyone who took the poll!

Now my sister Ali has started her own blog!

Here’s the list of links for family, friends and anyone else who is interested:

• Hays Travelogue
• The Date Book (It’s not what you think)
• Mom’s Flickr Stream
• Ali Marie’s S.I.N. (Service Industry Network)

I am totally looking forward to Ali’s anecdotes and insights from the front lines of the service industry!

Now if I can just get Nate (and Family), Dad (and Dee) and Grammie (and John) to join the game…

These are in-depth interviews (running over a half hour each) with lots of great gems from Avinash on topics from simple ‘how-tos’ to strategic approaches for measuring these new platforms.

(I’d better go look at my search analytics to see what I should be blogging about)

Here are the links to each podcast – ENJOY!

Web Analytics Association: Best Practices – Avinash Kaushik on Blogs & RSS

Web Analytics Association: Best Practices – Avinash Kaushik on Rich Internet Applications

Disclaimer: I am on the Web Analytics Association Board of Directors

But here’s what’s most intriguing to me…

…Did you notice that as you scroll through the lists of posts that the number of unread items goes down? Now, I’m totally daunted at the thought of trying to deconstruct Google’s JavaScript so I haven’t even attempted to ‘peek under the hood’. However, from a purely presentation point-of-view, it would seem that they might be using ‘onFocus’ to mark each item scrolled/scanned/read as read.

Why is that intriguing? Well it takes me back to a discussion I took part in back at Emetrics in April. The point of the conversation, to put it melodramatically, is that ‘the page view is dead’. One of the discussion participants declaimed that he wasn’t interested in page views because a single page might include multiple news items that he wanted to measure.

So if Google is using something of the sort I describe, couldn’t they easily hook that interaction into Google Analytics with a whole new metric? Something called ‘Post View’ or something less prosaic? Isn’t that we harp about when complaining about measuring Web 2.0/AJAX/RIA?

Here are some questions that pop up in my head while thinking about this:

1. Does onFocus equate to a person actually reading the post? When Eric Peterson launched his new vendor discovery RSS feed over the weekend, I quickly scrolled through about 50 posts in Google Reader but only actually read about 5 because I wasn’t really interested in which random site was using which random analytics tool
2. Are there any studies that show what the average time to read 50, 100, 200, 500, etc. words online is?
3. If such data as the above exists or could be executed with some rigor, could a combination of onFocus and time spent on that focus more accurately measure ‘engagement’ with an individual post?
4. What kind of KPIs might we drive out of the above scenario?

I guess if Peterson ever gets the “Virtual Web 2.0 Measurement Working Group” organized I can ask these questions there, but until then I leave them for you to ponder.

• Manoj Jasra over at Web Analytics World had four guest posters this week, Avinash Kaushik, Jennifer Laycock, Gord Hotchkiss and Rand Fishkin. They all cover different topics and each one is worth the read.
• Robbin Steif has an excellent post on what web analysts do all day at her Lunametrics blog, so if your bosses, peers, family, or friends have a difficult time understanding what you do – point them to Robbin.
• Both Stephen Few and the guys over at Juice Analytics pointed out this new tool for creating sparklines and bullet charts (among other things) in Excel, so I’ve been playing with it. By the way, it’s called Microcharts by BonaVista Systems
• Of course, the Hewlett Packard BoD fiasco has been absolutely fascinating (and horrifying) – Scoble is keeping tabs on it: Day 1, Day 2, Day 3, Day 4
• Mom’s back to blogging, this time from Egypt where they’re on a 2 year teaching stint – check out the new masthead for the blog which is the view from her classroom!

FYI, this data comes from Google Analytics which I’ve had up and running since April 20 so it’s missing roughly six weeks of data but I didn’t feel like buying the premium service from StatCounter.

It boils down to this: “Eric T. Peterson is GREAT for business!” Since historical referral data has been available, Eric is responsible for 28.9% of all referrals.

Notice too, that even though Avinash has only been blogging for about a month at this point, he is already in what I’d call the mid-tier of Referrers.

Organic searches from Google also do quite well at 8.2% but we’ll explore the Google segment at a later time.

Interestingly, two of the folks that I identified as my key ‘Sneezers’ in the last post show up in the small tier – maybe I just like Jeremiah and Robbin so much that I wanted them to be my key sources.

Finally, we can see that directly referred visits are the number one category (just barely beating Eric) at 29.8%.

Oh! And I was surprised at the volume of incidental traffic received from Blogger; which since I am blocking self-generated traffic, must be coming from the ‘Next Blog’ link in the Blogger chrome. I guess I’ll need to segment that blogger traffic and see if there is any value in it.

For the former, I’m not sure how I’d go about testing it – any thoughts?

One thing that I find particularly gratifying about the chart is the nice smooth growth in direct referrals — I’ll have to do a segmentation study to be sure, but — this seems to indicate growth in brand loyalty (boy I hope that’s true) as my visitors are just hitting a bookmark or typing in ‘instantcognition.blogspot.com’ into the address bar.

The basic cycle goes like this:
(1) Seeding. You start a blog, write 8 or 10 interesting posts, and advertise your blog as much as possible (link on your email signature/forums/etc). Soon enough, another blogger will write about you or point to you (blogroll, etc).

(2) Exponential growth. After reaching some critical mass of readers, readership growth accelerates all of the sudden – typically because a popular
blogger has written about you, or there is a press article pointing to your site.

(3) Organic growth. Your base keeps growing but it’s slooooowww. You’re incapable to sustaining the growth rates you had in phase 2.

So let me caviat this by saying that I am looking at page views and not readers – I don’t have a sufficient sample of readers via Feedburner or Bloglines to make the direct comparison but I think that page views are an acceptable stand-in in this case.

At right, is a chart of page views to this blog during its first one hundred days. You’ll notice that it has both daily tallies as well as a cumulative line. I’ve also included what I think are key events. In most cases, these are when “Sneezers” pick me up and spread the word. Although please note that Microsoft’s acquisition of Deep Metrix caused a spike in traffic to this blog (as it did to most blogs in the web analytics community) around May 6. In addition to the actual stats (daily and cumulative) I’ve added a best fit curve (4th order polynomial) which besides having a great correalation to the actual data, resembles Xavier’s theoretical chart above quite closely.

So, following Xavier’s theory, it looks as though Instant Cognition was in the ‘Seeding’ phase from March 7, 2006 through about April 18, 2006. On or about April 19, this blog entered it’s first ‘Exponential’ growth phase (a low exponent to be sure) that was kicked off by my attendance (and possibly my presentation) at Emetrics. Then, soon after Jeremiah Owyang (a blogging and podcasting heavy) added me to his blog roll and Avinash Kaushik started blogging my exponential growth phase comes to an end and I am now in the ‘Organic Growth’ phase until I get picked up by a new community.

For those who are interested, here are the linear slopes for each phase:

Phase I: 16.21
Phase II: 34.67 (more than double Phase I)
Phase III: 22.43

A couple of things that stand out to me here.

• If you walk along the cumulative line, you see what I consider to be micro traffic cycles. Consider for instance, April 19 through April 22 (Emetrics), in fine, this spike event looks just like the theoretical pattern posited by Xavier. The micro cycle repeats itself between May 15 through May 19 and again from May 28 – June 6 — and these are just a few examples.
• Secondly, observation of the daily page views bar chart bears out the growth trend just by eyeballing the density of high-traffic days during each phase. In phase I there is a paucity of high volume days while in Phase II there are many more and then the high volume days settle back in phase III, they are not as few as in Phase I and the low volume days are at a higher average than before so it looks like Phase II had a positive impact on phase III (otherwise the last phase would look a lot more like the first one).

So, what have I learned from this first part of the analysis?

• Well, if Xavier is right, I’ve got a fairly typical blog and am at least doing some things right. We’ll get into more detail later, but for the most part, I’ve picked up the ‘right’ Sneezers: Eric Peterson, Robbin Steif, Avinash Kaushik and Jeremiah Owyang to name a few.
• Also, it’s hard to get out of your own way. At work I’m dealing with numbers that are many orders of magnitude larger. Climbing down off that mountain to look at my blog traffic is tough.
• Oh! And Xavier’s a really bright guy. Ok, I already knew that (and so did all of you probably) but he is being especially kind by letting me reproduce his charts and theory here and by offering up any other data or help I might need as I go down this 100 days path.

Sources:

• StatCounter
• Coffee, Sun & Technology

Special thanks to Xavier Casanova of Perenety for letting me use his Blog Theory and charts for this comparison.

I just read through a very detailed post on Click-to-Landing Page Drop-Off. Which covers the vagaries of search engine marketing measurement from Click Fraud to Visitor Defection and Measurement. Not only does Matt offer a detailed view of the measurement pitfalls but he also offers solid recommendations on how get the most out of your web analytics package, ad vendor and site monitors to get a very wholistic view of those marketing efforts.

If you are a search marketer, or need to help search marketers figure out their campaigns, I’d encourage you to read this post.

Avinash is at the Vanguard of the analytics space so if you want to push the envelope – he has some ideas on where to start.

When he announced his blog to me he said that he is “going to blog about Web Decision Making…” I don’t want to steal his thunder but this is where ‘What’ and ‘How’ meet up with ‘Why’ and that my friends is where the rubber meets the road.

Welcome Avinash! We expect great things from you!