Web Analytics Are Four-Dimensional Now (Or How Many Do You See?)


Share on LinkedIn

How many dimensions do you see when you do web analytics for your business? Three or four? Or more? Don’t stop short!

Back in the 90s web analytics were rather 1 dimensional, namely just traffic stats. Then web analytics became two dimensional. Do you remember “quadrant analysis”? Back then it seemed as if web pages could be described as being divided into four quadrants and web analysts wanted to know where to place links for greatest clickthroughs. A third dimension was added to web analytics, namely depth. We started referring to it as clickstream analysis. Funnel visualizations and tree-shaped visualizations of clickstream paths became available in web analytics solutions such as Omniture, Webtrends, and NetInsight, the solution provided by my employer, Unica.

Web analytics matured within these three dimensions when in 2005 the discussion switched over to key performance indicators (KPIs). You couldn’t listen to a presentation without hearing the advice that KPIs were the single best method for preventing “analysis paralysis”.

It is 2007 now, and web analytics have become four dimensional. What is the fourth dimension? The customer! We came to realize that web analytics is not just about the site after all, but it is really about the prospects and customers that visit our sites. We don’t just want to optimize our web pages, but we want to optimize the interaction with prospects and customers. Oh yes, web designers have known this for a long while. But web analysts still focused on KPIs, paths, funnels, yada, yada. Now, the tides have shifted. Behavioral targeting is in site (ha ha). Coremetrics’ LIVE profiles have been around for a while already. But did you also notice Omniture’s acquisition of TouchClarity, or Unica’s Affinium Interact solution all of which focus on personalizing the site’s interaction with it’s visitors based on previous behavior?

Speaking of previous behavior, it goes without saying that the 4th dimension needs to include the customer’s previous behavior in the offline space as much as possible. Otherwise, how could we hope to achieve customer-centricity and get the personalization right. Do you think?


  1. So when you say 4 dimensions you must be thinking as in 3-d / 4-d, right? Not as in multi-dimensional analysis / OLAP? Because the latter could be umpteen-dimensional, say Products x Customers x Referrers x campaign channel x bla bla.

  2. I am afraid Jessica is missing the point and Arikan’s valuable and clear message about inclusion of the customer’s (prospect’s) previous behaviour has nothing to do with 3D, 4D or whatever you want to choose from that arena.

    It’s about customer behaviour, like he wrote, which in a way can be seen as multidimensional in itself.

    However, the number of dimensions is not that relevant at all .. as long as our speaking of 4D-analytics doesn’t warp the customer out of our B2B-space! 😉

    Let ‘s keep our feet on the ground and speak language that convince customers that we know what we’re talking about.


  3. I think Edwin is right on. Both views of “dimensions” have merrits. They are just different discussions. This essay was really about the customer behavior in all its facets and online+offline as Edwin underlined.

    Jessica is raising a very good point too thinking of OLAP style slicing and dicing of reports across “umpteen” dimensions. Such multi-dimensional segmentation of web analytics behavior is very useful to web analysts in order to find actionable insight. In fact my favorite web analytics solution is very good at that kind of right-click, drill-anywhere, slice by any dimension type analysis. 😎 .

    But I guess Edwin and I are saying that you could slice & dice all day long — if you didn’t include the customer dimension in your point of view — how good can the nuggets be that you will find in the end?

    Right on Edwin!


Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here