That’s So Meta: Tracking Data Studio, in Data Studio

In my eternal desire to track and analyze all.the.things, I’ve recently found it useful to track the usage of my Data Studio reports.

Viewing data about Data Studio, in Data Studio? So meta!

Step 1: Create a property

Create a new Google Analytics property, to house this data. (If you work with multiple clients, sites or business units, where you may want to be able to isolate data, then you may want to consider one property for each client/site/etc. You can always combine them in Data Studio to view all the info together, but it gives you more control over permissions, without messing around with View filters.)

Step 2: Add GA Tracking Code to your Data Studio reports

Data Studio makes this really easy. Under Report Settings, you can add a GA property ID. You can add Universal Analytics, or GA4.

You’ll need to add this to every report, and remember to add it when you create new reports, if you’d like them to be included in your report.

Step 3: Clean Up Dimension Values

Note: This blog post is based on Universal Analytics, but the same principles apply if you’re using GA4. 

Once you have tracked some data, you’ll notice that the Page dimension in Google Analytics is a gibberish, useless URL. I suppose you could create a CASE formula and rewrite the URLs in to the title of the report…Hmmm… Wait, why would you do that, when there’s already an easier way?!

You’ll want to use the Page Title for the bulk of your reporting, as it has nice, readable, user-friendly values:

However, you’ll need to do some further transformation of Page Title. This is because reports with one page, versus multiple pages, will look different.

Reports with only one page have a page title of:

Report Name

Reports with more than one page have a page title of:

Report Name > Page Name

If you want to report on the popularity at a report level, we need to extract just the report name. Unfortunately, we can’t simply extract “everything before the ‘>’ sign” as the Report Name, since not all Page Titles will contain a “>” (if the report only has one page.)

I therefore use a formula to manipulate the Page Title:

REGEXP_EXTRACT(

(CASE 
WHEN REGEXP_MATCH(Page Title,".*›.*") 
THEN Page Title 
ELSE CONCAT(Page Title," ›")
END)

,'(.*).*›.*')

Step 4: A quick “gotcha”

Please note that, on top of Google Analytics tracking when users actually view your report, Google Analytics will also fire and track a view when:

1. Someone is loading the report in Edit mode. In the Page dimension, you will see these with /edit in the URL.
2. If you have a report scheduled to send on a regular cadence via email, the process of rendering the PDF to attach to the email also counts as a load in Google Analytics. In the Page dimension, you will see these loads with /appview in the URL.

This means that if you or your team spend a lot of time in the report editing it, your tracking may be “inflated” as a result of all of those loads.

Similarly, if you schedule a report for email send, it will track in Google Analytics for every send (even if no one actually clicks through and views the report.)

If you want to exclude these from your data, you will want to filter out from your dashboard Pages that contain /edit and /appview.

Step 5: Build your report

Here’s an example of one I have created:

Which metrics should I use?

My general recommendation is to use either Users or Pageviews, not Sessions or Unique Pageviews.

Why? Sessions will only count if the report page was the first page viewed (aka, it’s basically “landing page”), and Unique Pageviews will consider two pages in one report “unique”, since they have different URLs and Page Titles. (It’s just confusing to call something “Unique” when there are so many caveats on how “unique” is defined, in this instance.) So, Users will be the best for de-duping, and Pageviews will be the best for a totals count.

What can I use these reports for?

I find it helpful to see which reports people are looking at the most, when they typically look at them (for example, at the end of the month, or quarter?) Perhaps you’re having a lot of ad hoc questions coming to your team, that are covered in your reports? You can check if people are even using them, and if not, direct them there before spending a bunch of ad hoc time! Or perhaps it’s time to hold another lunch & learn, to introduce people to the various reports available? 

You can also include data filters in the report, to filter for a specific report, or other dimensions, such as device type, geolocation, date, etc. Perhaps a certain office location typically views your reports more than another?

Of course, you will not know which users are viewing your reports (since we definitely can’t track PII in Google Analytics) but you can at least understand if they’re being viewed at all!