From Worst to Best: How to Report Metrics & Measures

Bloggers and consultants sometimes take bold contrarian positions to separate themselves from the pack. I am as guilty as anyone, I admit. Sometimes we (as in the royal I) should have sympathy for our readers (as few as they are) and recognize that all this helps make analytics confusing and perplexing when we pundits take opposing views. From time to time we need to help explain how all these different views can be reconciled and what are the true nuggets of truth. No issue is more controversial and yet more fundamental than visitors vs visits.

Sameer Khan on his blog Key Metrics and Web Analytics recently posted:

Most marketers and analyst are too concerned about the best metrics to focus on [how] to get actionable insights. Obsession for metrics does not always guarantee results. It is equally important to exclude the worst metrics from your analysis. Yes, you heard it right, these metrics can suck your time and lead you nowhere.
Top 3 Worst Web Analytics Metrics & Reports posted by Sameer, 9 April 2010

With this statement Sameer proceeds to list and discuss reasons for the top 3 worst metrics being unique visitors, bounce rate, and session duration. Just recently I also discussed these exact same metrics in Visitors vs Visits and argue that unique visitors are fundamental.  How do I reconcile my views with Sameer’s?  Continue reading

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Desperately Tracking Susan: Online / Offline Behavior

For my next post I was going to write something on non-linear methods for detecting novelty in time series data, when a series of posts popped up on my “twiky” from MineThatData. I have just started following Kevin Hillstrom, who is the mind behind MineThatData. He comes from a long and extensive career in data marketing even before there was web analytics. His forte is Online E-Commerce and Retail Brand Marketing, a rather large and important niche in web analytics. I am just now becoming familiar with his work and opinions on things and am looking forward to learning more. Typically I don’t pick someone out of the cloud and start commenting, but in this case his laconic twitter aphorisms have been needling me to the point that I have to respond. In a way – it is germain to my original intent.
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Funnels and the Paths They Make

Funnels are one of the most basic and important tools in web analytics for understanding how online interactions with customers feed into both on-line and off-line business processes and affect the bottom line of a business. Funnels are prominent in all sales organizations and most business processes as a simple but effective form of predictive analytics and method for monitoring impact of new actions. Funnels capture the notion of time that it takes to complete a process or task and effective milestones in the process of moving leads, RFQ, and RFP through to sales, orders or contracts. Continue reading

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Illustration of Skirting Axioms: Unique Visitors

I have presented the 5 fundamental axioms that define web analytics in a previous blog and also have given examples of how analyst and tools attempt to skirt these assumptions. I maintain that many of the differences and confusions that arise from comparing vendors comes from deviations in addressing these five assumptions.  The following gives a more detailed illustration of this point. Continue reading

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Visitors vs. Visits

One would think that Visitors and the Visits they make would go hand in hand, but in some cases that is not  true as implemented in many web analytic solutions.  With visitor metrics we are trying to understand how many and who is coming to our site.  With visits we are trying to understand patterns in the visitor’s activity to answer when and how many times.  Visits, also referred to as Sessions,  have their place in web analytics but not as prominently as one might think. When sessions become the central focus of the analytics and reporting then there are distortions in how visitor behavior is viewed and understood.  Caution: This is a no spin zone!  Let us take a new and honest look at this fundamental concept in web analytic analysis. Continue reading

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The Axioms of Web Analytics

And How Analyst and Tools Attempt to Skirt Them

Axioms are suppose to be immutable and unchallengeable, but hey, in this day and age is there anything that does not go unchallenged?  Axioms are assumptions that can not be proven but if true then subsequent theorems and proofs follow.  In the case of web analytics, the data and what it represents follows from a specific set of assumptions from which all subsequent metrics and reports follow.  These assumptions cannot be proven true and are often challenged as not true, but none the less – all measurement and analysis that  depends upon this data must accept these assumptions as the initial axioms of their analysis.

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A Day Being Mark

Recently I spent a day being Mark.  By that I mean I spent a day setting up and working through the examples from Mark Watson‘s latest book, Scripting Intelligence, Web 3.0 Information Gathering and Processing from APress.  Mark has been a close friend for a very long time and has written or co-authored more than 15 books in artificial intelligence, user agents, and Linux minutia  and uses Java, Common Lisp, Scheme and C/C++ to illustrate his material.   In his latest book, he uses Ruby to illustrate how one can get on board with Web 3.0 web applications.  Where Web 2.0 was about personalization and social media, Web 3.0 is about distributing application services into the cloud and navigating the semantic web to gather and mash-up information and knowledge. Continue reading

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How Web Analytics Sees Reality

I found an interesting question on the Web Analytics Association (WAA) Group discussion board at LinkedIn. Rachel Lewis asks, “How can you modify your site optimization plans to deal with the emergence of plug-ins like Kikin?” The discussion can go in several directions from strategy to planning to techniques, but what peeked my interest was how does Kikin, Cooliris and other plug-ins change what we see and measure on our web sites. I have wondered the same thing as I zip through search result links with Cool Previews from Cooliris, which pops up the web page with a mouse over. Kikin takes the tool bar to a new level by actually inserting not only content but Web 2.0 application into the center of search result pages and providing summaries and links to one’s favorite social media such as Facebook and Twitter and even potential competitors such as Bing, iTunes, Yelp, and Amazon. What does that do to our perception of web not to say also our understanding of marketing channels?

The question seemed to be important enough to dust off my old proxy server code that captures the data stream between the browser client and the site servers to check out what is happening.
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