Your Data: The Best Resource You’re Not Using to Run Your Web Site
An article was recently published claiming “Marketers Find Less than Half of Analytics Useful for Decision-Making!” In full disclosure, I added the exclamation mark to the headline because I felt like the tone of the article implied a minor hysteria over the implication that ‘less than half’ was a staggering figure. In fact the article caught my eye because that seemed to be a higher percentage than I’ve witnessed. Not because companies don’t understand the potential power of analytics but because “analytics” often simply becomes “data collection” which in and of itself, is not useful to anyone really.
Let me back up. I’m a big believer in Avinash Kaushik’s “So What?” analytics philosophy that says if you can’t answer what action or recommendation could result by tracking a certain metric after asking ‘So what?” three times, you shouldn’t bother tracking it. It’s a great philosophy and in theory any organization subscribing to this philosophy should be running a lean, mean analytics discipline. In practice however, most companies don’t ask “So What?” or even “Why?”. Instead they are swimming in a sea of data with the end result being analysis paralysis.
Sometimes this is self-inflicted (tag everything and review hourly!) but in most cases they’ve companies implement an analytics package and now that data is being collected, they just don’t know what to look at or care about. So they end up doing nothing. As a colleague once put it “Your web analytics tool is the best tool you’ve already paid for but aren’t using.”
Here at Fluid we’ve recently overhauled our Analytics practice within our Strategy group to make sure even our approach to data is user-centric. Why? Simple. We want to help our clients:
- Achieve a deeper understanding of customer behavior and motivations
- Answer the “why” behind the “what”
- Make quantitatively as well as qualitatively informed design decisions
- Work within a clear framework for measuring success and proving ROI
- Get past analysis paralysis and turn mountains of data and isolated metrics into insights and actions