There are tons of blog posts and websites that explain the differences between reporting and analysis. Around 343 million according to Google. But there are very few that explains how to make a proper analysis. I am the first to admit, when I first started in the job as a consultant, I thought that reporting was the same as analysis. When it dawned on me that this was not the case, I was totally lost in relation to how I should get started making my first analysis. It was completely new to me and I did not in any way know what I should do or where I should start. Therefore, in the next posts I will take you step by step through one of my analysis, which hopefully can help you get started with some analysis as well.

We can not avoid it. Despite the 350 million pages already explaining about the differences between reporting and analysis, then this first post will focus on just that. Reporting vs. analysis.

If your data warehouse team, says they can automate it…
Then there is no doubt – it’s reporting! A rule of thumb is that if it can be automated, it is reporting. Reporting are in most cases dashboard that are sent out on a daily, weekly, monthly or quarterly basis. In other words, it is based on a push approach. We are pushing data out to stakeholders. Often also referred to as data pukes. I’m sure you regognice the below:

google analytics dashboard

Adobe Analytics dashboard reporting

Both are classic examples of reporting. Despite the fact that we can spice them up and present them differently…

Custom Adobe Analytics dashboard reporting

…its still reporting. We can even call them them boards and feeds…

adobe marketing cloud board sample

…it doesn’t change the fact that it is and always will be reporting. I am the first to admit that when I started 6 years ago, I didn’t think it required more than creating some dashboards and make sure that they were sent to the right people. And not least, that they showed the data which the stakeholders wanted to see. So if you thought that any of the above examples were analysis, you’re not alone. Over the next few posts you will get some concrete steps on how to move forward from reporting and more in to analysis.

Let me just clarify. It’s certainly not because that dashboards and reports are not usable – without reporting we would never enter the analysis stage. But you want to ensure that you don’t spent too much time on reporting. So automate as much as possible and spend the remaining time on analysis. You should be spending at least 25% on analysis. If you until now have only been creating reports, aiming for 25% may be a bit too high, so setting a lower goal is just fine.


Analysis is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it.


All right! What consist an analysis of ?
Elves…… and the extraordinary power of Technology. Or maybe not quite. Where reporting gives us information – bounce rate is 78 %, unique visitors 23.498, etc. Analysis gives us insight and not least, a recommendation – Google definately gives the volume in traffic, yet Yahoo presents an opportunity for more targeted audience showing more Transaction/Visit. Consider testing SEM with Yahoo Audience .

But a lot of words is not equal to analysis. Words instead of the data puke is just a guide line. Be sure to read what it says to make sure that it actually is an analysis and not just a description of what the graph shows. 3 things you can look for to determine if it is an analysis you are looking at:

  1. The first thing you see is not data, but actions for the business to take
  2. If you see more than 3 metrics in the table you are presented with, then it’s probably not an analysis you’re looking at
  3. If there is some kind of moneytization it is most likely an analysis

To make it a little bit more simple and allowing you to compare the two, you can use the table below:

reporting vs analysis

I hope that with the above description you’re better equipped to make a decision about whether you are looking at reporting or analysis. In the next post we will begin our analysis. The analysis will be divided into 4 steps and the first step is – make a long list of rocks to look under!

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