Web Analytics with Adobe’s Customer Journey Analytics, Part 8: A new home
This post is the eight and last post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we were creating the connection from Experience Platform to Customer Journey Analytics. In this post, we are going to take a look at our web analytics data and explore some use cases.
Believe it or not, but this series of posts is almost finished! Starting with nothing, we have created a sophisticated schema for our data in Experience Platform, created a tracking implementation using the new Web SDK, enriched our data in Query Service, and pulled all that data into Customer Journey Analytics. If you have been following since the start of the series, I want to say: Thank you, hope you enjoyed the ride!
Now it is time for the finale, where we take a first look at our data and what we can do with it. With all that we have done so far, it should be pretty clear that what we have right now is only an example of how we can collect, enrich, and utilize data in many flexible ways with Experience Platform and Customer Journey Analytics. If you have a different use case in mind, like e-commerce, media, or content use cases, you can model your business’ data in a lot of different ways. But now, let’s start with our data!
Basic web analytics reports
First, let’s take a look at what we can do with the very basic reports we implemented. For example, we can just drag the Page Name dimension into a Freeform Table like we know it from Adobe Analytics:
Thanks to our renamed Metrics, not a lot of people would even be able to see the difference between this table and what we would have in Adobe Analytics. There are two things that stand out: Occurrences now show up as Events (which makes a lot of sense) and the table is not sorted by a metric, but alphabetically by the dimension values. You heard right, Customer Journey Analytics can do that too!
Another pretty basic use case would be to analyze entry- and exit pages. Since we have created those in Query Service before, we can just use it like any other dimension to break down the page report:
One thing that I would love to have, but would take a lot of work, would be to recreate dimensions like the Referrer Type or Device Type ourselves from the Referrer URL or User Agent. Adobe should help us to create those lookups in the future so we can safe ourselves the trouble of creating those. But let’s not linger on what we don’t have and take a look at the other awesome things that we have created in Query Service.
Exploring path reports
To start this part off, let’s first drag the Full Event Path into our Freeform Table. Remember, that Dimensions putts each and every event in the session into a nice chain like this example Visit:
We can see that this Visit had 5 interactions tracked, with two Page Views and three Content Interactions. We have two more pathing reports that we can use as a breakdown here, containing the preceding and following path for each and every event in a session. In this example, I’ve used the Event Path before Event dimension that we created in Query Service:
Here we can see how, with each event, the chain of events that happend before a certain event grows longer and longer. If we feel adventurous, we could even break each of those rows down by the following path like this:
There are a lot of applications I can think of for those kinds of report. For example, we could report on the exact chain of events that lead up to a conversion like a purchase. And if we wanted to analyze where in a user journey a certain event happened, we could use the relative path dimension like this:
Here you can see how the user is really moving along our page with every event of a session. Using this with a success event would allow us to see where in most user journeys those events happen and what happened before and after that. Super helpful for all kind of analysis!
Embracing deeply nested data
Remember how, in the post about the tracking implementation, we tracked interaction with content on a page in a deeply nested way? To do that we defined in our XDM schema that our page has an array of on-page content, which holds an array of interactive elements. Let’s see how that looks in our data with the respective Dimensions and Metrics:
Using the Content Interactions Metric, you can see quite nicely how the extra levels of nested data do not inflate our data. We still have only three interactions with our content, but with two involved Interactive Elements who were part of all three interactions. Now if we add more Metrics, we can get a clearer picture of what those interactions were:
Here you can see the magic of nested, sub-event level data. While we were sending in data for both article teasers in the same event, we only set the swipes to- and swipes from interactive element Metrics on some of them. This is very similar to how the product variable works in Adobe Analytics, but even more powerful! Since every XDM field can be an array or even an array of objects, we have unlimited product or list variables available, where each and every item can have their very own properties! If that doesn’t get you excited, I don’t know what will!
Conclusion
I really liked how this series cam together just nicely in the end. With the awesome options in Customer Journey Analytics, like reusing a Metric as Dimension and vice-versa, and the flexibility of Experience Platform schemas, we can really take our way of measuring and analyzing online behavior to the next level. If Adobe provides some more integrations (like Analytics for Target) for Customer Journey Analytics there is no real reason to stick with old Adobe Analytics. And, coming from me, that should say a lot!
Thank you so much for reading through this series. As always, let me know what you think of the use cases and examples and have a great day!
German Analyst and Data Scientist working in and writing about (Web) Analytics and Online Marketing Tech.