Over the years I have met many marketers that have Adobe Analytics implemented but are unhappy with their reporting. It's such a shame to see so much time and effort invested in such a valuable resource that does generate return. A common mistake that is found over and over again is a poorly structured data model. Adobe offers a mass of customization that can easily be overwhelming. So let's reel it in.
To get started, it makes sense to understand the difference between Custom Traffic and Custom Conversion variables. You can read about these here.
There are 2 types of variables that can be used to measure a user action; Data and Event (metric). Which means there are 2 different ways we can track a key engagement;
1. We can create Events for each action we want to measure and name them accordingly
OR 2. We can create key Event metrics and use a Data field to capture the event description
Because Data variables can capture unlimited values and an Event metric can only count 1 event, it makes sense to capture the value that can change; “text” in a Data variable and use custom Event metrics to measure key engagements, such as; View, Click, Download etc.
Another common mistake is to populate multiple Data variables with the same piece of data
Scattering data this way limits reporting capabilities. If we want to see all the activity for Login ID #123, we need to run 3 different reports!
This is why we always want our Data values stored in one place. Here is an example of a single report that uses key Events to expand the reporting capabilities of our data
Following these best practices for data modelling will ensure:
And most of all SCALABILITY (my word)
It's hard to see the future and predict our analytics needs. Websites grow and content changes. If we build a reliable and scalable solution design, we don't have to predict what may come. We'll be ready for it.
For more tips on solution designing for Adobe Analytics visit 3-top-data-strategies-for-adobe-analytics
I welcome your comments and feedback