Most people who are not familiar with digital analytics expect it to be self-revealing. That is to say, if I look at the data in Google Analytics or Adobe or similar tools, it will be obvious what is happening in the business. That expectation is similar to a doctor reading data about your blood pressure and temperature and knowing whether you have a healthy lifestyle. It’s directional at best. Like medicine, digital analytics is both an art and a science. So let’s first start with the science, and in my next post, I’ll cover the art.
What Your Technical Set Up Reveals
The first thing I see when I look at your data are the technical problems I know will create roadblocks to meaningful analysis. This tells me immediately whether digital data is really important to your organization, and sometimes whether you have a sufficiently-staffed team. It also tells me the level of analytics sophistication in your team. Configuration errors are often found around campaign tracking, events, goals, and specific tool features not enabled. It is all solvable, but a good configuration gives you trusty data to stand on later.
From your technical set up I can also tell if your internal processes are flowing smoothly which may further indicate a lack of leadership or ownership. I see this through how your data is recorded. Are there multiple lines for the same keywords differentiated only by capitalization or spacing? Or disjointed tracking because a file was updated and someone slightly changed the name? Messy processes usually happen when teams are not working together well.
Often companies install a digital analytics tool without realizing there is a lot of fundamental groundwork. The requirement is actually 90% people and process and 10% tool but most think it is the reverse.
What Your Analytics Set Up Reveals
If the technical configuration looks pretty good, then I can dig into the data. Here we take one step closer to art but are still firmly anchored in science. This is where an experienced eye will see the first hints of business value. I notice directional problems. There’s not enough traffic here. There’s too much traffic there. There is an odd entry point or visitors are flowing in circular paths (which may indicate they are lost). There may also be existing segments, campaign data or reports that stimulate good discussion with an internal analytics team. This is where we start to have some fun.
BUT this is also where most analytic departments get cut off at the knees. Everything was going along so well! The data is in and solid. The analysts can use the data. They understand the patterns, and they create presentations and report out their findings. But no one seems to use the data. Without proper business context – the “art” -- the ability to generate value is limited.
The result? Reports without action. People buried in data. Frustration. My next post will cover how to add the art to strengthen the science.