Improved Content Tracking in GA4 Using Event Parameters

Matt Crowley - April 6, 2023

Analyzing the performance of your content is an important part of any successful content strategy. With the release of and migration to GA4, many organizations have had to re-wire their approach to measuring performance. This is due to the change in how Google Analytics collects data.

GA4 Collection Model

As you can see in the illustration below, Google has moved from a collection model based on hits, to one based on events. This requires changing your approach to measuring performance in order to best align to this new collection model. Some see this as a challenge, however, we believe that you should see it as an opportunity.

The Opportunity

The change in the Google Analytics collection model opens up new opportunities to standardize how you measure content performance, primarily through the use of events and their associated parameters.

Parameters are detailed dimensions that you can collect associated with an event. For example, when a user views a page, it triggers a page_view event which is associated with many parameters like page_location (the URL of the page). We can create parameters for just about anything we want to measure, and “attach” them to events (i.e. metrics) that we want to measure.

Think about how much more effective this can be than Universal Analytics (UA). With UA, we didn’t have this structured relationship for all of the data points we wanted to measure. With UA, we had 3 slots to assign to a given event and they were not flexible (we only had “Category”, “Action”, and “Label” fields). Now, with GA4, we have up to 25 parameters (WOW!) that can be passed along with a single event.

Now, we can create a flexible and scalable structure to tie many very specific dimensions of our content with a wide variety of performance metrics. For example, if we wanted to measure the performance of our content, we might want to track signup events (newsletter, blog, webinar, etc…) from our content efforts. Here is an example of how this might have been setup in UA and how we could obtain way more insight with GA4:

      UA Example

      Category: Newsletter

      Action: Subscription Signup

      Label: {Text Clicked by User} / Sign-up for Our Newsletter

      GA4 Example

      Event Name: Newsletter

      Parameter (Action): Subscription Signup

      Parameter (Text Clicked by User): Sign-up for Our Newsletter

      Parameter (Company Name): Acme Company

      Parameter (Company Size): 1,000

      Parameter (page_location): /blog/may-2023-marketing-webinar

In the former example with UA, we can only measure performance of the total number of signups and what the user clicked on. In the GA4 example, we can segment out signups by much more valuable dimensions like company size. This can enable much more valuable and granular data analysis of performance.

How to Take Advantage

Additional new flexibility with software often comes with a “gotcha.” In this case, GA4 brings amazing new features and flexibility, but it requires expertise to create a standardized and scalable strategy for your unique needs, as well as technical talent to customize the platforms to ensure accurate measurement. Taking advantage of the new event + parameter model is best done by:

1. Establishing a comprehensive measurement strategy
2. Defining the ideal data architecture to capture the right data for your strategy
3. Defining the required technical changes to surface and capture the data effectively
4. Implementing technical changes in Google Tag Manager, Google Analytics, and/or your website
5. Testing all changes prior to pushing them live
6. Pushing the changes live and testing again
7. Configuring reporting (which may require a data analysis / dashboard platform like Looker Studio and possibly the use of a data warehouse like BigQuery).

If this is an area you would like to explore further for your organization, please reach out to us at info@morevisibility.com and our expert team of Google Analytics specialists can assist you with building out your measurement and analysis capabilities.