Avinash Kaushik has a very good post, one of his best, on the inaccuracies of time spent per visit measurement and how it's calculated.

My take - that calculation needs to be re thought out entirely; and honestly, I don't like the idea that web analytics platforms can't really get it right and site owners need to come up with their own hacks to compensate for the lack of information.

Taking a step back, going back to the early 1990's or late 1980's, looking at session logs, it's easy to see why analytics vendors came up with the calculation of a metric which left out the instance of only viewing one page (bounce rate) or the last page (without knowing how long the visitor spent on the last page).

It's a reflection of how people browsed the web when the first could browse it - which is similar, maybe, to mobile device that can have, usually, only one window up at a time (but the iPhone can have several pages open at the same time).

Today, people have much more powerful systems and browsing is done in a multitasking mode - maybe linearization, as Avinash suggests, solves much of this problem, and maybe it really doesn't fully - since you don't know the time spent, again on the very last page of a multi-page session.

And the idea of custom hacks for something like this are repugnant - better analytics vendors to build in a solution they agree on. 

Managed to stay on or near the top all year of Web Analytics Blogs, regardless of how they're being measured; in  Top Ten Web Analytics Blogs: July 2007 Avinash Kaushik has Webmetricsguru as the #3 top Web Analytics Blog using a new ranking system designed by Kevin Hillstorm; Avinash adapted Hillstorm's formula somewhat but kept the main part of it.

"..For my best web analytics blogs ranking I am using Technorati and Feed Subscribers. I have come to appreciate the number of feed subscribers as the best success metric for a blog (see: Tips For Measuring Success Of Your Blog).

My feed subscribers is hovering around 1400 right now and I have an average visit count of around 1000 per day (unless I write about something that ends up driving extraordinary traffic - which has happened a lot lately).  I don't pay much attention to my Technorati rank either, to me it's becoming irrelevant - but that's just my opinion.  Here's the top 10 Web Analytics Blogs:

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Rank July ‘07	Rank July ‘06	Top Web Analytics Blogs	Score
1	3	Occam’s Razor by Avinash Kaushik	88
2	New	Google Analytics Blog by Jeff Gills	86
3	1	Web Metrics Guru by Marshall Sponder	79
4	New	Web Analytics World by Manoj Jasra	72
5	New	WebAnalytics.be Blog by Aurélie Pols	53
6	New	Analytics Talk by Justin Cutroni	51
7	4	Unofficial Google Analytics Blog by Shawn Purtell	49
8	New	Lies, Damned Lies… by Ian Thomas	46
9	5	Increasing Your Website’s Conversion Rate by Robbin Steif	46
10	New	The Commerce360 Blog by Craig Danuloff

I read half the blogs on the top list anyway, and can now post to Web Analytics World - just haven't gotten around to it yet! 

Eric Peterson posted a comment to Top Ten Web Analytics Blogs: July 2007 suggesting Avinash drop Technorati Rank out of the equation - I tend to agree with Eric on this - it's not so much that Technorati is wrong - it's that a lot of sites, including mine, have periods of time where Technorati does not update it's records properly. Personally, I'd like to see what the list looks like with out Technorati, with just FeedBurner RSS Subscribers…. but that's just me.

Wow…. Avinash Kaushik is leaving Intuit to form his own Web Analytics Consultancy with his first gig …work directly with the Google Analytics team.  I got this information from the Unofficial Google Analytics Blog - but I see Avinash, himself, has blogged about it.

"…I have recently made the decision to change paths as it relates to my professional career. I’ll be leaving Intuit, and my position there as the Director of Web Research & Analytics, and become an Independent Consultant. "

Good move.

"…For my first assignment I’ll be working with Google as an Analytics Evangelist. In that role I’ll work with Google Marketing and assist them with internal analytics for their marketing programs. I’ll also be working with the Google Analytics team on assignments that span speaking, web analytics education and evolution of the GA tool."

Avinash has functioned as an Evangelist just last week when he asked John Marshall of ClickTracks to make more features available in ClickTracks Appetizer - it's totally in line to work with Google Analytics in an Evangelist role (hint: can Avinash talk Google into buying Quantcast? …..I'd love to see that happen - and all that goes with it).

"…It will probably more likely that I’ll be in your neck of the woods speaking or teaching (or be on YouTube !) and perhaps I’ll get to see more of you and have more direct contact. This is certainly one of the motivating factors behind my decision. "

I hope New York is one of your stops, Avinash.

Actually, what Avinash Kaushik is doing …..reminds me a little of Robert Scoble ….. not so much the Evangelist thing (or maybe  it is the Evangelist thing) or striking out on his own.   Does he have anything to worry about?

Nah - Avinash will have more demand for his services than he'll know what to do with.

This is good news and follows the equally good news that Global Strategies LLC, Bill Hunt's company (who also had Intuit as a client, btw) was acquired by Neo@Oglivy -  GlobalStrategies.com acquired by Neo@Oglivy the other day.

Good Fortune, Avinash.

Thanks to Google Alerts - I feel plugged in when my name appears somewhere on the Web - almost as quickly as it happens, I know about it. 

Anyway, perhaps in response to Eric T. Peterson's question of "what ever happened to Avinash's List" of the Top 10 Web Analytics blogs for each month, Avinash produced one of his lists for January 2007 and Webmetricsguru.com is number 3 on the list.

Avinash seems to be using Technorati Rank as the way to distinguish the ranking of each blog in the list.  Don't have much more to say about it; glad Avinash Kaushik is continuing (because he's the only one I know who's doing this).

Avinash wrote a really good post on how to use /  implement JavaScript tags and one of the things that stuck me was this:

"……In many web analytics implementations on the web you’ll see the tag right at top or in the header or before the <body> tag. This is sub optimal. Your javascript tag should go as close to the </body> tag as possible. The simple reason for this is that the tag should be the last thing to load on the page. In case your analytics server is slow in responding, or has simply died (less likely), then at least the webpage and the content will load quickly. "

That's interesting  - in one implementation that I'm involved with, we're thinking of putting the JavaScript tags in the header / Masthead.  It's not my idea….BTW.  Makes sense though - you don't want to slow down a page loading because the web analytics server is down - that's a really good point.

Also, Avinash talks about Flash Tracking (one of my favorite subjects)

"…Tracking rich web experiences requires a lot of deliberate planning and implementation up front before anything gets released to ensure that via you web analytics tool or via a custom solution you are able to track some semblance of success. ."

I can tell you personally, tracking Flash is difficult to do … especially in a publishing environment (which is where it's often needed the most); and where work is being done on the page right up to the time of publishing. 

More often than not, the people working on the web page and on the copy are totally different than the Web Analyst (which is good because if we were building pages we'd have no time for analysis).

Avinash Kaushik asked me for a list of free tools I like a couple of months back for a blog post on Occam's Razor and I pretty much gave him the list I published at Big Green Blog recently. 

The post went live tonight and I read it - it's FANTASTIC - and I'm enjoying reading how Avanish uses those tools.  I use all those tools often - Avanish did a better job explaining the Microsoft AdLab tools for Demographic Prediction could be used than I have.

I'm glad Avanish is writing a book on Web Analytics - it's going to be quite entertaining - I hope he puts some of this stuff in the new book.  The point of his post on Five Free “Advanced” Web Analytics Examples: Look Outside, Think Different. which I'm sure is going to get DIGGED - use other tools (free one's in this case) beyond your site analytics to gather insight.

One thing I'd add to Kaushik's description of Google AdWords Keyword Expansion, near the end of the post - I use the somewhat differently.  Google's Keyword Research tool is one of the best semantic analysis extraction tools and it's free.  Put in a URL and the tool will tell you what it thinks the page or site is about - it will also give you the other data Avinash talks about in the post.

Often, I've used the keyword data from this tool in Competitive Analysis - comparing the keyword phrases of sites that are competing to find a common set of keywords that I can run a ranking report against - and thereby decide which competitor is doing better for those keywords.

It's a great post , I think it's one of his best, and I'm glad Avinash got around to posting it now.

I was reading Avinash Kaushik's post on The Great Web Capture Debate (logfiles vs. JavaScript tagging) when I noticed Avinash also did a great interview with Mike Moran of IBM (and one of my former bosses a couple of years back).  I'll focus on both posts here.

First off, I want to say that I read Kaushik's entire post on Web Capture using Google Reader on my SideKick 3 and I find I can process the content better on a small PDA like device….maybe it's just me.

I found out reasons to use JavaScript vs. logfile analysis, because I read Avinash Kaushik's Web Capture post, that I did not know about, like:

"….Increasingly we are heading towards doing a lot more measurement and customer experience analysis beyond just clickstream. Two great examples of this are experimentation and testing (especially multivariate testing) and personalization / behavior targeting. In both cases “add-on” solutions are tacked on to the website and testing / targeting happens. Often these solutions come with their own methods of collecting and analyzing data and measuring success…………………….."….Integrating with these add-on solutions (which often also use javascript tags and cookies and url identifiers) is significantly easier if you use javascript tags. It is easy to read cookies in web logs etc, but he pace at which you can integrate and the ease at which you can integrate is faster if you are using javascript tags."

I've tended to accept logfile analysis as a given with JavaScript (single pixels web beacon) as the improvement over logfile analysis but both work, more or less.  Avinash make it clear why you'd want to use one over the other and the need for a third way - something neither data collection method provides.

Ten Minutes With….. Mike Moran, IBM was a good read for me; currently I'm looking at Mike's manuscript, as yet unnamed, about Marketing.  If I were to pick a title - I'd call it "Marketing 2.0" (sorta after "Web 2.0").  Getting back to the interview, Avinash Kaushik focuses on Mike's 4 Patents.  

IBM, in general, really is rich in Patents and when I started at IBM 4 years ago, I was working in the IBM Hawthorne Research facility and there was a wall with all IBM's Patents (including, I'm sure, Mike's 4 Patents).  I can imagine that some of what makes search engines effective (to the extent they are effective) touches one of Mike Moran's Patents in some part of algorithm process.

Avanish focuses the interview with Mike Moran on SEO/SEM - but to me - Mike is much broader than Search Engine Optimization; his experience encompasses Personalization, which his team at IBM.com had a lot to do with architecting.  

A couple of months ago Mike left IBM.com to work for IBM Software Group managing OmniFind - IBM's Search Engine that works with WebSphere. Last week I wrote up OYE! (Vay?) -IBM-Yahoo Search Engine for Enterprise and Internet Search about the OmniFind OYE! edition that was just released.

Avinash's interview with Mike Moran worth a close read; and I'm glad that I know and worked for him (in fact, Mike was one of the 7 or 8 people who interviewed me initially to get into IBM in the first place).

Avinash Kaushik has a couple new Podcasts at the Web Analytics Association on measuring Rich Media Applications (Flash, AJAX, etc).  Among the points Avinash makes:

1. Preplanning: Unlike other things for this area you need to do a lot of pre-planning and make sure your code is included in the rich experience before you get started. On web pages we can recover and tag later etc. In this area it is very hard to do so set a lot of time for planning.
2. Integration of data, hyper important because A) you can’t measure in a silo (so you need to know what the differences are in outcomes based on where different segments of people come from or based on offers or what they might have seen before or after the experience) B) you want to know what people “think”, so in our case it is important to integrate into mechanisms such as website surveys.
3. Testing, testing, testing, testing. You are ready for rich experiences, but are your customers ready? I have a great example of this in the podcast above. Failing faster is a awesome recipe for long term success. 

I have been measuring Rich Media and Podcasts and it's a lot of work….. and there's no clean way to do it.  One thing I do notice….stuff is published without much or any testing and then detailed metrics are expected ….not so easy to deliver when there's been little testing.

Avinash Kaushik brought back some good stuff from London last week - bottled up in his latest post over at Occam’s Razor. 

1) Engagement metric - How is your site doing vs. Customer Expectations.

According to Avinash people now regularly expect "more" than what their website experience (on your site?) delivers:

‘Early in your existence (or when the Internet started) the red line was lower, websites had very robust / delightful capabilities that were way ahead of customer expectations (maybe they were not quite as savvy or they did not care). But as the web has evolved and our customers have become increasingly sophisticated the slope of the yellow line (customer expectations) has a much steeper gradient.

Another thing Avinash picked out of the same presentation - Persona’s are important and some are more important to you than others and that value can be calculated (much as I have calculated the value of a page for some of my clients).

"…I am not sure how Value is computed but you can use Profitability or Customer Loyalty or Net Promoter or Least Likely to Switch (in case of phone company) or Most Amount Spent on Add-on Services or other such metrics. Pick the one that makes most sense for your company."

Avinash pulled from another presentation to highlight cross channel conversions - including offline conversions (How can we measure success in a non-line customer experience world? Tough questions with evolving answers), similar to my example in Measuring Multi Channel Marketing - an open question to the Web Metrics Community of Talladega Nights.

 "…We execute marketing programs and measure effectiveness as if the process is linear. But in reality as the red, green and purple lines indicate customer behavior is very different and we are not very well set-up to measure effectiveness. If you come to the website (the red line above), read reviews, go to the store, look and touch the products, talk to the sales person who totally wow’s you and you go and buy the product (all in one day). Who gets the credit? Your Google PPC program? What if your path was the one shown by the green arrows? Off-line then online then offline then online?

Avinash has been saying for some time that Clickstream data alone, is not enough to measure conversions - and he continues that line of reasoning here:

"…This is all the more reason that your core web success measurement strategy can’t rest on the bedrock of clickstream data, if it was not already limiting before it is very much so now. Taking steps to incorporate other measurement sources such as surveys or remote usability or market research or collecting information via registration etc are going to be critical. And who knows that else is around the corner. [Qualitative data. Survey Best Practices.]"

I would read Avinash’s entire post a couple of times over - and download the presentations.

I read though Avinash Kaushik’s Top Ten Blogging Tips & Insights from a Novice Blogger; can relate to several of the 10 points.   Blogging is time consuming because you need to create a lot of content - hopefully all of it gets crawled.

Also, need to write about things you know and feel strongly about.  I found that traffic does build slowly and I focus on RSS Feeds and return visitors and Avinash’s blog is doing very well even though he does not post all that much (maybe 3 to 5 times a week).

Found DIGG traffic is sudden, but tends, by it self, not to have much effect on your longterm traffic patterns, unless your getting DIGGED often.

The rest is pretty standard fare and it’ s good because Avinash makes it seem real and fun - he never takes himself too seriously.