The old sporting joke went like this:
“And now for a partial score: Pittsburgh 8″.
It doesn’t mean anything except in relation to other data.
Page views? No: Conversions as a percentage of page views.
Unique visitors? Nice! Better: amount of times (on average) visitors came before converting.
Popular Pages? Good. But what about popular pages as related to what campaigns took them there? And then, how about using that data to craft new messages to the visitors to those popular pages? You figure, if they came to the landing page, then went to the “Punky Brewster” page, then there is a segment of your visitors that should get a new message about Punky Brewster. Seems like common sense. But not done often enough, not nearly so.
Reports are just pixels on a screen. Context is the result of report correlation and implied meaning. Sure, one day humans will retire from this field too, as they have retired from fields like limestone-block hauling and the profession of what used to be called “knacking” (look it up, you’ll find it interesting); but for now we don’t yet have Artificial Intelligence capable of telling people what data means to the business. And that means someone has to look at the reports; ask questions; dig in; make a recommendation.
Action? Naturally this is the outcome of insight. But undirected action is more like energy dissipated than energy focused. Like a spilled cup of chai rather than an arrow from a crossbow.
So, think about context. Think about understanding how the accurately collected data seems in context with other data. Combine measures. Patterns overlay patterns and suggest answers only people can deliver (so far). Dig in and find the meaning. Any executable plan relies on meaningful data. It’s all available in web analytics, but not necessarily in the toolkit all by itself.