In the ever-evolving world of digital marketing, Google Analytics has been a cornerstone for advertisers. The introduction of Google Analytics 4 (GA4) marks a significant shift in the landscape of conversion tracking. For advertisers, this transition is both an opportunity and a challenge. This comprehensive guide aims to identify and demystify the differences between Google’s now-discontinued Universal Analytics (UA) and the Google Analytics 4 model that replaced it.

1. GA4 Replaces UA’s Sessions Tracking With Event-Based Tracking

One of the most fundamental differences between UA and GA4 is how they approach tracking. UA was session-based, focusing on sessions and pageviews, while GA4 adopts an event-driven model, capturing more granular data about each action a user takes. This shift has profound implications for how advertisers measure user engagement and conversions.

  • UA’s session-based approach primarily focused on sessions and pageviews.
      • Example: Imagine an online bookstore. A user visits, browses through the “Mystery” section, and then checks out the “Romance” section. UA would have tracked this as one session with two pageviews.
  • GA4’s event-driven model captures discrete interactions as individual events.
      • Example: In the same online bookstore, a user’s click on a promotional banner for a new mystery novel and their subsequent addition of the book to the cart are both tracked as distinct events. With this, there is greater potential for precise measurement, but also a greater need for precise setup of tracking conversions.

2. Event Types & Conversion Setup: Manual vs. Automated Tracking

UA required manual setup or integration with Google Tag Manager (GTM) to track specific conversions. GA4, on the other hand, offers a more structured approach to events, categorizing them into automatically collected events, enhanced measurement events, recommended events, and custom events. This makes it easier for advertisers to set up and track certain conversions without extensive manual work.

  • UA required manual setup and GTM integration for many basic conversions, and lacked GA4’s event categorization.
      • Example: To track the download of a free ebook preview, advertisers would have used GTM to set up custom event tracking.
  • GA4’s structured approach to events allows for enhanced and automatic tracking of certain conversions — even without GTM.
      • Example: With GA4, the same ebook download can be tracked as an “Enhanced measurement event” without additional configurations. The same goes for other valuable conversions such as video engagement, outbound clicks, form interactions, page views, and scroll depth.

3. User Entity Modeling & Conversion Paths: Cookie-Based vs. User-Centric Tracking

UA relied on cookies for tracking, which could sometimes result in fragmented user journeys. GA4 adopts a user-centric approach, offering a unified view of the user journey across devices and platforms. This, in hand with GA4’s transition to event-based tracking, is particularly beneficial for advertisers looking to understand the complete conversion path.

  • UA relied on often-inconsistent cookies for tracking.
      • Example: A user clicks on an ad for a book sale, visits the site, but only makes a purchase a week later. UA might have struggled to link these interactions if they occurred on different devices.
  • GA4 offers a unified view of the user journey using all events a given user completes.
      • Example: If the same user browsed the sale on mobile, added a book to the cart on desktop, and finalized the purchase on a tablet, GA4 would present this as a cohesive conversion path.

4. Ecommerce Conversion Tracking: “Transactions” vs. “Purchase”

In UA, ecommerce tracking revolved around “transactions,” which could include details like product ID, quantity, and revenue. GA4 introduces “purchase” conversions as its primary ecommerce metric. This shift not only changes the terminology but also impacts how ecommerce conversions are tracked and analyzed.

Although GA4 ecommerce tracking may allow for more granular purchase measurement when set up properly, it loses some convenient automatic elements of UA’s transaction tracking.

GA4 must be set up specifically on checkout and payment pages, and typically is not added there automatically even when installed by automation on all other pages of a website. With this, where some transaction data could be automatically captured in UA, the process of adding GA4 to payment pages now varies in complexity based on a site’s platform (such as Shopify or Squarespace), and commonly requires the aid of the given platform’s technical support team.

If you are looking to track purchase conversions with GA4, it’s highly recommended that you reach out to your website builder’s support team directly, and request or ensure that your GA4 measurement ID is installed on checkout and payment pages specifically. You may need multiple GA4 measurement IDs installed if you are tracking conversions from different sources, such as Google Ads and sitewide or organic traffic.

  • Universal Analytics “Transactions:”
      • Example: A user purchases three different books. UA would have captured this (potentially automatically) as one transaction, detailing the books and the total amount.
  • Google Analytics 4 “Purchase:”
      • Example: After manually adding GA4 measurement IDs to payment pages, this same transaction would be tracked as a “purchase” event, which captures the books bought, their individual prices, and the total amount.

5. Engagement Rate vs. Bounce Rate: A More Nuanced View of User Interaction

UA used “Bounce Rate” to measure sessions where users viewed only one page. This meant that even if a user read an entire article, taking however long to do so, but didn’t click on any other links before leaving the page, it was recorded as a “bounce.”

GA4 replaces this with “Engagement Rate,” a more nuanced metric that considers various forms of user interaction, including time spent on the site, conversion events, and number of pages viewed. This offers advertisers a more comprehensive understanding of user behavior.

  • UA used “Bounce Rate” to measure sessions where users viewed only one page.
      • Example: If a user landed on a book review page, read for 10 minutes, and left without navigating further, it was considered a bounce in UA.
  • GA4 introduces “Engagement Rate” as a more nuanced metric.
      • Example: If the same user reads the book review for five minutes and then leaves, GA4 would consider this engagement with the review, offering a more accurate picture of user interaction.

6. The Essential Role of Google Tag Manager in GA4: Event-Based Conversions Make GTM More Crucial Than Ever

Given that all conversions in GA4 are event-based, understanding Google Tag Manager (GTM) becomes more crucial than ever, especially for those in digital marketing or ecommerce. While certain automatic events are predefined in GA4, one-size-fits-all events may not actually fit your website and goals. GTM allows for the creation of custom events and dimensions, providing a level of customization that is essential now that 100% of conversions are event-based.

  • With UA, you could create some basic session-based conversions within the platform itself.
      • Example: If you created a destination page on your site, you could link it directly to a conversion in UA.
  • Given that all goals in GA4 are event-based, events must be customized with GTM for precise tracking.
      • Example: To track events like the time spent on each section of a blog, you would need to set up custom events and dimensions in GTM.

7. Changes in Account Structure: Data Streams vs. Views

UA structured accounts into Account, Property, and View levels, allowing for different views to track various user segments. GA4 simplifies this structure to just Account and Property, introducing Data Streams as a replacement for Views. However, Data Streams operate differently, collecting data at a higher level via a unique Data Stream ID.

  • UA structured accounts into Account, Property, and View levels.
      • Example: Different views could be set up to include or exclude internal traffic, or to filter traffic from specific subdomains.
  • GA4 simplifies this to just Account and Property, introducing Data Streams.
      • Example: Instead of separate views, you would use one Data Stream to capture all of your website data, and then filter that collected data through “explorations” and built-in reports (which are also different in GA4 than UA — more on them later).

8. Time on Site Tracking: A Paradigm Shift

UA offered built-in time on site tracking, providing advertisers with a straightforward way to measure this specific type of user engagement. GA4 has the option for time on site tracking, but replaces UA’s built-in offering with the “engagement_time_msec” parameter. While this offers more precise data, it also requires advertisers to adapt to a new method of analysis.

  • UA offered built-in time on site tracking.
      • Example: You could easily see how long users spent browsing your whole site.
  • GA4 replaces this with the “engagement_time_msec” parameter.
      • Example: Depending on how the parameter is set up, the time that a user spends on a given page or a whole site is now considered an event, offering more precise data reporting, but requiring a new approach to setup and analysis.

9. Enhanced Measurement Tracking in GA4: Flexibility and Automation

GA4 offers Enhanced Measurement Tracking, which automatically tracks a variety of user interactions. This feature provides a level of flexibility and automation that was not easily achievable in UA without additional configurations or custom setups.

  • With UA, additional work was needed to track many specific events.
      • Example: Tracking file downloads or video plays required custom setups in UA, such as utilizing Google Tag Manager or inserting code snippets to define actions on your website.
  • GA4 offers Enhanced Measurement Tracking for a (limited) set of commonly tracked conversions.
      • Example: Page views, outbound clicks, and even video engagement can be tracked automatically with GA4, making life easier for advertisers.

10. Data Reporting: From Standard Reports to Explorations

One of the most striking differences between UA and GA4 lies in the realm of data reporting. Universal Analytics was designed with a comprehensive suite of standard reports, making it easy for advertisers to view and analyze data. These reports were automatically structured and readily available within the UA interface.

In contrast, GA4 takes a more customized approach, offering fewer standard reports and requiring users to engage in “explorations” to view specific data, or to utilize external sources like Looker Studio or BigQuery to make data easier to visualize.

  • UA provided a plethora of standard reports that were automatically structured for easy viewing.
      • Example: You could easily access standard reports with different variables and levels of specificity in UA, such as Acquisition reporting by channels, referrals, and source/medium.
  • GA4 leans towards custom reports and data exporting, requiring more initial effort to set up and analyze data.
      • Example: GA4 offers a broader “Acquisition overview” report, requiring further customization for more specific reporting. You can create and customize an “exploration” within the GA4 platform to isolate specific metrics and variables, or use a dashboard platform that can do the same, like Looker Studio.

11. Limitations of GA4: What You Need to Know

While GA4 offers advanced features, it has its limitations. These include the absence of certain reports that were available in UA, the lack of historical data import, and the complexity involved in setting up custom dimensions and metrics.

GA4 also places limits on the number of conversions you can set up in each Data Stream. While UA allowed for the creation of multiple views that could house 20 goals each, a GA4 Data Stream can only track up to 30 unique conversion events. GA4 is also not fully GDPR compliant, so implementation in certain countries may require an additional understanding of consent-based tracking.

  • Custom Dimensions & Metrics:
      • Example: In UA, a custom metric could be set to track the average reading time of a book sample. Transitioning this to GA4 likely requires a more intricate setup, including the use of Google Tag Manager.
  • Historical Data
      • Example:An annual book sale’s performance in UA for the past five years won’t be directly comparable to the current year’s data in GA4, as GA4 doesn’t import historical UA data.

From UA to GA4: A Shift in Programs and Perspectives

The transition from Universal Analytics to Google Analytics 4 presents new insights, challenges, and opportunities. For advertisers, the key lies in understanding the specifics of GA4 and leveraging its capabilities to the fullest. As is the case with many softwares, the more powerful the tool, the more intricate it is and the more setup it requires, but the more promise it offers. This is much the case with the transition from UA to GA4.

The digital marketing realm continues to evolve; staying updated and adaptable is paramount. Whether you’re a seasoned advertiser or just starting, mastering the nuances of GA4 will equip you to navigate the future of conversion tracking with confidence. And Nonprofit Megaphone is here to help. Reach out to us here to learn how we can help your nonprofit achieve, track, and analyze conversions with GA4 and the Google Grant!