In just a couple of years, Web analysis concepts have evolved from counting server hits to page views, visits and visitors. Sophisticated web analytics solutions such as Omniture SiteCatalyst, WebSideStory HBX, Coremetrics and others can establish correlations between user behavior and site characteristics to visually present them in powerful, yet simple to understand reports and dashboards. Yet, we've seen a growing concern that the "page view" might not be enough to measure the sophisticated and various ways information can be disseminated and used without the constraints of time, space and medium. The death of the page view is a hot topic in web analytics, and expert groups are looking into other ways to measure success in the era of Web 2.0, RSS, blogs, mashups, YouTube and unexpected or even undiscovered new ways of using information.
At a macroscopic level, numerous methodologies have been conceived and tested to measure the success (and too often the failure!) of ebusiness and emarketing initiatives. Brought back at an individual-level, that is, at the level of the human being interacting with information trough a media/medium; there is little objective ways of measuring the quality of the interaction. Measuring the value of a relationship has become a necessity. The challenge isn't merely to build a customer-value model, but to use it in a sophisticated and evolving analytical environment.
What if we could use a simple marketing classification method such as RFM (Recency/Frequency/Monetary value) that has been used for over 35 years, and add a degree of Attention to drive the relationship value model? In this context, "Attention" can be defined in several ways, but let's simply consider that "attention is a psychological construct describing detection, selection, discrimination of stimuli, as well as allocating of limited processing resources to competing attentional demands".
In the coming weeks, I will explore some analytical concepts, web or otherwise, I first studied four years ago as part of the MBA course "Understanding the digital enterprise", presented by Professor Stéphane Gauvin, from Laval University. I will also demonstrate how the RFM model can be used in web analytics, and add the concept of Attention as presented by Goldhaber and others. But the bulk of the model will be validated with the analysis method elaborated by Davenport & Beck in the book "The Attention Economy".
I can't pretend to be an expert in the field, maybe just a bit more fanatic about web analytics than most people. Considering some very bright people are already at work trying to find ways to measure such things as "engagement", my views might sound too simplistic or theoric at times. I will nevertheless dig the topic for the pure interest of it. In this journey, I will encourage you to share you thoughts and ideas, even if it's to tell me I'm crazy :)
Named one of the most influential industry contributors by the Digital Analytics Association. With over twenty years’ experience empowering organizations to analyze and optimize their online channels, Stéphane has cemented his position as a leading voice for online analytics and optimization.


2 comments:
Hello there - I'm part of John Beck's (author of The Attention Economy) consulting firm, The Attention Company. You might be interested in a new piece of research we have up on Attention Metrics here:
http://blog.attnco.com/2007/03/the_attention_e.html
We measured attention metrics by type of media and found some fairly interesting results!
Thanks,
Adam Carstens
Hi Stéphane,
Well, I'll be watching your next posts very closely! I look forward to seeing how you articulate RFM with Attention. The RFM model will become more and more popular in the Web marketing field, because of the massive arrival of the database marketing framework into the Internet marketing mindset in the coming years, I believe. Very powerful stuff. Tiring of analyzing anonymous data, we will see the "Acquired Emaill address / 1,000 visits@ kind of KPIs becoming more crucial, as important as sales conversion.
People like DGIG are surely already working like hell to link their Web analytics system with the tremendous customer data you guys must have in your back end.
Again, looking forward to reading you.
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