Some things are worth repeating. That’s why I think it’s worth revisiting this two-and-a half-year-old blog post by Avinash Kaushik. He’s a respected Web analytics guru and Analytics Evangelist for Google who has good ideas about his field to offer, even if you aren’t a Web analytics professional yourself.
If your job involves sharing information over the Web, whether you’re in marketing, sales, PR or otherwise, you should know about Web Analytics. (It’s that arcane discipline that enables analysts to measure the success of, and establish ways to improve, Web sites.) First and foremost, everyone, including web analysts themselves, needs to accept that it’s a complex discipline.
If all you have is a hammer, everything looks like a nail.
Sure, we all want things buck simple. So it isn’t unexpected that developers, managers and clients want one tool – that “single source of the truth that was God’s answer to everything,” as Avinash describes it – to help them assess their Web sites and make them better. But when there’s several stakeholders/constituencies involved and multiple data sources, one tool isn’t going to solve the problem.
As Einstein said: “Make everything as simple as possible, but not simpler.” In this case, that means accepting complexity and embracing multiplicity.
Avinash’s post does a great job of teasing apart this complexity, though. He offers five types of data sources (everything from voice of the customer and competitive intelligence to clickstreams) and aligns them with a multiplicity of available tools.
To be fair, since Avinash’s post, things have improved. Our available tools are getting easier to use and in many cases cheaper to acquire. On top of that we are seeing analytics tools converging into solutions that offer more integrated feature sets.
The answer is 42. Now what was the question?
So the challenge now is less about getting the data or even summarizing the data. It’s about asking the right questions. And it’s about answering the questions by identifying the most important and relevant bits of data from each of our sources using a range of tools and combining these bits so that we can understand what is happening, why it’s happening, what it means to our business objectives and what we should do about it.
This may seem like a tall order and, like many business challenges, it is. But it’s not an order you can afford to ignore or hide from. Especially for business in a competitive environment where the difference between success and failure depends on seemingly insignificant advantages.