“I still can’t figure out what you do”

Comes the common refrain – to be a Web Analyst in…well, anywhere. There are not that many of us. Officially, web analytics is supposed to be about “understanding the behavior of visitors on a website”. I’ve posited a second definition (now I’m previewing June 11) that it’s about “understanding digital behavior”. (We’ll see how that flies.)

I can break web analytics out into 3 broad categories.

There’s a technical side of my job – last week I analyzed log files and the results of javascript executed tags. This week I’m into Omniture and Google Analytics. There are a few flavors of web analysts who make all their money implementing difficult to code tracking on sites. I’m not really one of those flavors, but generally, it’s all about implementing the tool for a site or a campaign. And I’ll emphasize – I can set up some fairly good Google Analytics tags – but Omniture is really just complex. (Cue Hamel with a “I thought it was supposed to be easy” line).

There’s a strategic side of my job. I’m to be that nasty, unpopular voice in a room. When somebody asks “what’s the goal of this campaign” and somebody else says, “to generate awareness”, I ask “how will you know if you succeed?” – and then I go about figuring out a set of measurable criteria, that can actually be measured. Yes – very unpopular. However, it helps us prove our value, even if it doesn’t always ladder up to the holy grail of ROI. (And frequently, a lot of what we do online doesn’t have a direct 1:1 attribution with ROI, but that doesn’t mean that we shouldn’t be cognizant of the goal of something.)

There’s also the whole question of how to measure the different channels, how each one should be measured and managed, and how a site is actually constantly improved. There are also questions of data integration with the broader organization.

So, there are many strategic aspects to how measurement fits into the broader spectrum.

Finally, there’s an analytical aspect of my job – which has a few subsets – including infometrics (how data is presented – which is a non-stop fight) to communication, and then there’s statistical analysis. The statistical analysis is particularly important because it allows you to summarize large amounts of data, as well as (sometimes) isolate causality. If you know what’s causing something to go right or wrong, then you can start intelligently optimizing a website, instead of kind of going at it like a monkey on a keyboard. Many SEM tools have some statistical analysis baked into them, and that’s great. It’s an improvement over what we used to have.

That’s my job. Fully 1/4 to 3/4 of my day is spent simply communicating findings, talking to stakeholders, or working in interdisciplinary teams. Anywhere between 1/4 to 3/4 of my day is spent analyzing, researching, or understanding a website.

For some analysts, the ratios are very much different. Some web analysts spend 95% of their day producing reports (at many organizations that’s the case). Some web analysts I know spend 95% of their day coding. Some web analysts spend 95% of their day project managing (for real). And that’s just fine. 🙂

So, that’s what we do.