Well, not exactly. I attended Jim Sterne’s presentation this morning here in Montreal. First, it was just great to see so many people (over 60) present, and interested in Web Analytics. Very frankly, I started preaching about WA here 6 years ago, and did not get much attention then. This morning was a refreshing sign of how much our field has grown here in both interest and project sophistication.
So, I was looking forward to Jim’s presentation, because of its very title: “An Industry in transition: From Web Analytics to Marketing Optimization”. When I read about it, I thought, “Ah ha!”. I had actually commented about signs of that transition before, and how Jim had re-christened his events “Marketing Optimization Summit”, while leaving Emetrics Summit in small letters. As you know, I strongly believe that, as a stand alone field, Web Analytics won’t probably exist in three years from now. It’ll probably be a part of the general enterprise intelligence (BI), in an all-integrated data environment (OK, that one is still far from realization).
I thought that it was exactly what Jim would be telling us this morning. It was rather a very well put (well, that’s Jim after all) presentation on how much we can do with analytics when we go beyond the usual behavioral analysis applications (WebTrends, Omniture, Google Analytics, etc.), and integrate attitudinal analysis, competitive analysis, etc. This makes a lot of sense, of course, and I share that vision, having established that type of service offering back at Bell Canada in 2005 when I struck deals with iPerceptions and Offermatica.
Yes, Web Analytics without the optimization part, which is just a fancy way of saying “Aren’t you gonna act on that darn analysis!?” is not much of use. And to do that, you need more than just one (too often free) tool; you need a tool box, good people, determination, sweat and tears. OK, I dramatized a little here (can’t help myself), but the point is, you need to be fully committed to it to get the pay back. And you must try stuff, test, learn what works and what doesn’t (and stop reading white papers, and, heck, blogs!!).
At some point, however, it will just make more sense to not only use various Web Analytics tools, but to connect the data to other data sources in the enterprise. And that’s when we will care only about simple, pure Analytics. Who will run the show? BI? Web Analytics (with the importance of the Web channel)? I guess it will very much depend on what the business is at heart, and where the customers will want to interact.
So, no, Jim wasn’t here to proclame the death of Web Analytics, rest assured. He was here to tell us to stand up and start moving our large Marketing behinds, and squeeze way more value out of those frigging Web sites!
Great post! The clients we work with that have been successful, they are few and far between unfortunately and not because of me:), are the one’s who REALLY use the data to make decisions. I can’t tell you how many times we work with clients asking for REPORTS that I know damn well will only satisfy a question from some marketer who will do nothing with it other than stick it in a quarterly powerpoint for a group of folks who will also not do anything with it!! Back to my point about using the data to make decisions. The clients that are integrating the data with other sources are undoubtedly the ones making decisions the most. One reason is they can, since they have the full picture! One simple example. We had survey data about pages, VoC, from Opinion Lab that by itself was good information but the team didn’t know which pages with a poor overall rating to attack first. Well, hello, why don’t we through it all in Excel and pull in the Analytics data (Google, WebTrends, Omniture …) and see which pages had the most traffic. So simple and an easy example, I know, but it allowed the team to actually TAKE ACTION. I slept well that night and it was so simple. What is really exciting is the bigger integrations with Campaign systems, Targeting etc.. but so few companies are there YET.
Hi Rebecca Elizabeth,
Thanks for your great input. I am currently working on a company diagnosis tool which will help me pinpoint which stage an organization is at in the Analytics evolution scale. Having determined KPIs is a major indicator of companies that have gone beyond reporting. I think, based on what you shared, that we should definitely add having started to integrate web data and enterprise data as another criteria of sophistication.
You know, I understand how you feel very well. I am getting quite impatient with organizations that don’t at least TRY do act upon what the analytics says. I mean, I can’t show them how to do reporting for the rest of my life!!!
Thanks again for your contribution.
Jacques –
Many thanks for the kind words about my presentation. Please, please, please let me know when you have your analytics evolution scale available for review. I’d like to put it alongside the work that Bill Gassman has done on his analytics maturity model and see if we can’t get some consensus…
Hi Jim,
I certainly will! I don,t know about Bill Gassman’s work; I’d love to learn about it.
Jacques, I really like this post. I’d love to talk about the evolution scale — the maturity of organizational departments involving an emerging profession was what I concentrated on in graduate school! I also wrote a related blog post a while ago.
Things are moving so fast. I actually think that we’re really not doing a very good job of web analytics in general (sorry to say that) and that enlarging the scope is actually kind of scary, like building a house without waiting for the concrete foundation to cure.
Hi Chris,
Long time no see, and thanks for your comment.
You’re right about the foundation: I just don’t equate Web Analytics with behavioral analysis. I think getting various points of view is good.
However, I totally agree with you when you say that we are still not doing a good job of web analytics yet. In the last year, I have grown more preoccupied with instiling a sense of urgency with my clients. I would rather see them act on what they learned, and try stuff, than developing sophisticated models and implement complex applications.
Strangely, I have found convincing them to be a hard job too…