Eric asked on Twitter:
"What do you think is holding the #measure industry back? Pls share!"Replies were plenty.
Incidentally, two days earlier, someone for whom I have the utmost respect spent an amazing amount of time shedding light on the web analytics industry. Joseph Carrabis is an amazingly bright person who is somewhat of an outsider to the web analytics industry, and thus, can shed a different light on it. He looked at us, collectively, asked questions, and shared some very interesting thoughts in Part 1 and Part 2 of "The Unfulfilled Promise of Online Analytics". Joseph is an observer, a listener, a thinker, and a very honest and respectful person. Joseph opened up a conversation.
Back to the Twitter thread
@immeria: @erictpeterson wht's holding #measure back? My take is the Web Analtyics Maturity Model http://bit.ly/fAavu Nevr got feedback from U abt it
@erictpeterson: @immeria I'm not a believer in the value of models. I worry that they are the new "Web analytics is easy."
@immeria: @erictpeterson What's holding back #measure? Additional comments in my nod to @JosephCarrabis at http://bit.ly/4CAvEc #measure
@immeria: @erictpeterson never claimed WAMM would make #measure easy, but certainly easier. It's a start, don't you think?
@erictpeterson: @immeria let's agree to disagree, shall we? Either way, glad you got an A+ on the thesis paper. Congrats!
@immeria: @erictpeterson Solving problems when #measure is "hard": 1) acknowledge the problem 2) understand it 3) act to solve it. WAMM helps do that
I waited and thought about this thread because I simply don’t get it. I was to reply privately but decided to post a public response instead. The comment “let’s agree to disagree” is what Wikipedia defines as a "thought-terminating cliché". Hopefully, this will be a way to continue the conversation because without conversation, there is no learning, and no evolution.
So, what's holding back web analytics?
My opinion, based on 18 months of study on top of over 20 years of experience that led me to this industry - looking at other fields of expertise and interviewing practitioners around the globe - it turned out there were some clear patterns. The result is a proposal for the Web Analytics Maturity Model - a document where I ask for feedback and peer review.
I received and continue to receive amazing feedback about it. Even when something looks wrong, people offers very constructive feedback. That's perfect: it's the goal of peer review. Very few people ever said something against this work. "I don't believe in models, they are the new "web analytics is easy"" and bold claims like "I'm a maturity model atheist" are really the exception and as you guess, offer no solution.
There seemed to have a level of consensus in previous research (lets not call them “models”) and among the feedback I gathered.
What's holding back web analytics is:
- A lack of trust, engagement and support from management: the 1st "pillar", or critical success factor.
- Unrealistic or undefined objectives & scope: the 2nd & 3rd key success factors.
- Nonexistent change management, politics and bad communication.
- Lack of process and best practices: the "Team & expertise" dimension of the model.
- Difficulties in taking action, going into a continuous improvement process that brings positive outcomes. The 5th dimension of the model.
- Technology was the least important of the factors leading to a successful, positively accepted web analytics program.
People can tell me I'm off track with the Web Analytics Maturity Model - everyone is entitled to an opinion. But critics should lead to suggestions. The concept of a model - although not perfect and obviously open to improvement - as proven a valuable tool to facilitate assessment of organizations web analytics status and spark constructive discussions. That being said, I repeat, a "model" is NOT a black magic recipe to success. I'm also warning that using the model as a comparison tool between organizations is not necessarily a good use of it.