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There is a trend happening in the media world at the moment which is making me all giddy and excited about the future. It's a shift that I'm seeing within many larger media companies in how they measure their traffic and audiences.
What's happening is that we are moving away from the purely session and visit based analytics, and instead focusing on scored, evaluated and insight-based analytics. And it's just wonderful.
In other words, instead of just looking at a standard analytics dashboard that will tell you that you have this many uniques, this many pageviews, and this percentage of bounces. The new age of analytics is all about how we measure the actual loyalty of our readers, how do we know how our journalists are performing and how do we know if our articles are helping our editorial focus and business models.
It's a much higher level of analytics, which is far more interesting and valuable.
The problem, however, that I often come across is that many publishers don't know how to do this. We talk about it, we see the need, but there is a gap between knowing what we want to measure, and actually figuring out how to make that work.
So in this article, I'm going to fix that, by giving a visual model that you can apply to the way you think about analytics. And by the end of this, you will know how to put things together, and how to think about measuring this more advanced analytics ... but in a really simple way.
Mind you, I'm not saying that doing it will be simple. I'm saying I will make understanding how to do it very simple.
Okay? So let's go.
Before we actually start to work with the data, we need to fix the common problem that publishers simply don't have the right data to begin with.
I see this all the time when I'm hired to do a strategy review. Some of these reviews involve me getting access to publishers raw analytics in order to answer the questions they have, but I often find that they simply didn't collect that data. The problem is either the data just simply wasn't there, or sometimes it is also the way it was collected was done in a way that doesn't fit how we want to use it.
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