A response to the Dialogue going on over at Petersen’s Demystified Blog.

I read the entire dialogue, and believe that I understood 80% of it, and misunderstood 20%. Much of what I’ve read, well, I’ve experienced first hand…such as watching LifeCycles appear in my data and recognizing what’s going on. Some of it, I have no experience. Yet, all you can do is try.

Here’s a response of Joseph Carrabis’ thread.

Thanks Joseph for the citation and the dialogue.

I continue to be in awe of Jim Novo’s ability to speak both Sciencese and Businessese. I’ll echo the power of the “R” in RFM. Recency. The notion that a human in habit tends to stay in habit resonates. “Anchor and Adjust” is another way of phrasing it.

I’ll take a stab at the Future of Web Analytics —

You have physical technologies – Omniture, Google, Google Analytics, Summize – on the one hand. On the other, you have social technologies – the Scientific Method, Web Analytics departments, the conference call.

If you examine job postings the WAA site (plug) on the Demystified Yahoo Group (plug), you’ll find a long list of physical technologies listed. “Candidate must have 15 years of Omniture, 12 years of WebTrends, and 5 years of Crystal Reports” – all too often. So many of us, and HR professionals, are obsessed with physical technology.

(If you examine the Critical Mass postings (plug), you’ll only find “SPSS” listed, and that’s not even required. Shaina Boone and I made a decision, a long time ago, that we didn’t care if somebody had an interface memorized – if they didn’t have the soft social skills and a number of traits, we couldn’t grow them)

I don’t believe that most organizations have focused on the social technologies. Worse, it’s the social technology of analytics that’s the hardest part of the slog. Sure, if you think it’s a nightmare to install Google Analytics or Omniture in a very large organization (and it is) – just imagine how hard it is to socialize a culture of analytics in an organization (and it is).

First, there’s fear that data driven insight is going to suck the creativity right out of most of our jobs — that we’re all going to become slaves to the Algorithm in the end. I don’t believe that this will ever be the case. Data driven insights enable data driven learning. It many ways, through the magic of multivariate testing, we can try out high-risk creative without risking catastrophic failure. It’s an innovation enabler in certain risk-adverse organizational and national cultures.

Secondly, there’s a very good reason why the world is populated with few scientists, statisticians, mathematicians, forensic accountants and programmers. Math only really appeals to a minority of the population. So, we have a barrier of skills.

Thirdly, there’s the scientist – business communication gap, discussed at length in previous posts. It takes a scientific mentality, often (not always) to derive very deep insight from a mess of data. In many respects, being a web analyst shouldn’t be so much about running reports, but should be about running the scientific method on very expansive datasets. Then, that scientist has to tell a story that is accessible and usable.

Fourthly, there’s organizational inertia. Organizations are a lot like people, they anchor and adjust too.

Four barriers, all human generated: fear, skills gap, communication gap, inertia.

I predict that the real challenge in the Future of the Web Analytics is going to be more around the social technology implementation and maintenance, and not so much the physical technology. Physical technology will always play a role, it has to by default, but it will become much less pronounced in the future.