Google Analytics 4 (GA4)

Google switched to Google Analytics 4 (GA4) to provide users with a more comprehensive and flexible platform for web analytics. GA4 offers a range of new features and improvements over the previous versions of Google Analytics, including enhanced machine learning capabilities, improved privacy, and support for cross-device tracking.

The switch to GA4 reflects Google's broader focus on privacy, as GA4 includes new features such as improved data retention policies and support for the Privacy Sandbox initiative. This allows users to collect and analyze data more securely and privacy-consciously while still providing insights into their website traffic and user behavior.

There are some concerns, however, on how privacy-friendly GA4 really is. Multiple EU member states (Italy, France, Austria, Denmark) have banned the use of Google Analytics entirely (both the Universal Analytics version and GA4) as it violated privacy laws.

All this aside, let's dig a bit deeper into how GA4 works and answer the most relevant question, hereby focusing on a few different metrics!

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Let’s dive in!

How to migrate to GA4?

To migrate to Google Analytics 4 (GA4) from Universal Analytics, you will need to create a new GA4 property in your Google Analytics account and set up the tracking code on your website.

To create a new GA4 property and set up tracking on your website, follow these steps:

Log into your Google Analytics account and click “Create Property” in the top right corner.
On the next page, scroll down to "Google Analytics 4" and click on it.
Enter a name for your property and select an industry category for it. You can also include any additional settings you’d like here (such as Enhanced Measurement).
Once you have entered all your information, click “Create Property” to create your new GA4 property.
Now that you have created your GA4 property, you will need to set up a tracking code on your website so that data is sent to it from your site. To do this, copy the provided tracking code and paste it into the <head> section of your website’s HTML.

GA4 is a new version of Google Analytics that uses a different tracking code and data model than Universal Analytics, so the data from your Universal Analytics account cannot be transferred directly. However, you can still use the data from your Universal Analytics account to help inform your analysis in Google Analytics 4.

For example, you can use the data from Universal Analytics to set up benchmarks and goals in Google Analytics 4 and use it to compare the performance of your website or app over time.

What are the biggest changes to Universal Analytics?

There are several key differences between Google Analytics 4 (GA4) and Universal Analytics. Some of the most significant differences include the following:

GA4 is introducing User-ID tracking: This feature allows you to track users across multiple devices and identify them as individual customers.
Enhanced data privacy and security measures: GA4 takes a more stringent approach to data privacy and security, with improved measures in place for user authentication and data encryption.
Greater control over data analysis and reporting: You can use Google Analytics 4 to gain deeper insights into customer behaviors and create targeted campaigns based on these insights. Additionally, you can use its machine-learning capabilities to uncover previously hidden trends in your customers’ behavior.
New data collection methods: GA4 utilizes a variety of new data collection methods, including event-based tracking, advertising ID integration, and more. This allows for a more precise measurement of user behaviors.
A more straightforward implementation of custom tags: You can easily customize the tracking code for a website or app events with GA4’s simplified tag library.

Some marketers are unhappy about the switch to Google Analytics 4 (GA4) because it represents a significant change from the previous versions of Google Analytics. This change can be challenging for users who are already familiar with Universal Analytics, as they will need to learn how to use the new features and interface of GA4.

In addition, some marketers are concerned that GA4’s new privacy features may impact their insights. The new data retention controls and support for the Privacy Sandbox initiative may limit the amount of data available for analysis, which could affect the accuracy and usefulness of the insights provided by GA4.

What metrics will I lose when I migrate to google analytics 4?

When you migrate to Google Analytics 4, you may lose access to some of the metrics available in Universal Analytics. Google Analytics 4 uses a different data model and tracking code than Universal Analytics, so the available specific metrics may differ.

Some of the metrics that are different in GA4 include:

Unique Events: GA4 has no metrics for tracking unique events. Instead, you should use Event Count to track the total number of events that occur.
Goal Completions: GA4 does not have any goal completion metrics; instead, it uses Conversion Events to track conversions.
Social Interactions: This metric is unavailable in GA4 since social interactions are tracked through event tracking.

In addition, Google Analytics 4 introduces new metrics, such as “User Engagement” and “Lifetime Value,” previously unavailable in Universal Analytics.

When you migrate to Google Analytics 4, ensure you understand the differences between the metrics each platform offers so that you can properly analyze your data and get the most out of your website analytics. We’ll touch upon these in more depth.

Finally, remember that when you migrate to Google Analytics 4, the new data will take some time to start showing up in your reports. This is because GA4 requires additional setup and data processing steps before any collected data can be displayed in your account. Therefore, make sure you give Google Analytics 4 enough time to process the data before making any decisions based on your reports.

Bounce rate in GA4

As I mentioned earlier, the metrics in GA4 differ from those in Universal Analytics because GA4 uses a new data model designed to provide a complete picture of how users interact with your website or app. This means that the metrics in GA4 may differ from those in Universal Analytics, and you may not be able to directly compare the data from the two systems.

In Universal Analytics, a bounce is counted when a user visits a single page on your website and then leaves without triggering any other events or interactions. This means that if a user visits a page on your website, spends some time on it, and then leaves, it will not be counted as a bounce.
In GA4, a bounce is counted when a user visits a page on your website and then leaves without triggering any other events or interactions within a specified period. This means that if a user visits a page on your website, spends some time on it, and then leaves within the specified period, it will be counted as a bounce.

What is engagement time in GA4?

In Universal Analytics, engagement time and time on page refer to the same thing: the amount of time a user spends on a page on your website. This metric is calculated by subtracting the time the user entered the page from the time that the user left the page.

In GA4, engagement time and time on page are two separate metrics. Engagement time is a new metric that measures the total amount of time a user spends actively interacting with your website or app. This can include time spent on page, but it can also include time spent watching videos, filling out forms, or engaging with other content on your website.

On the other hand, time on page is a legacy metric similar to how engagement time is calculated in Universal Analytics. It measures the amount of time a user spends on a page on your website, but it does not include time spent on other pages or interacting with other content on your website.

What is an audience trigger in Google Analytics 4?

In GA4, an audience trigger is a condition or set of conditions that can be used to define an audience. Users will be added to the audience when they satisfy the conditions of an audience trigger.

They can be based on various factors, such as the user's location, the device they are using, the pages they have visited on your website, or the actions they have taken on your website. In addition, they can be used to create custom segments of users, such as people who have purchased from you in the past. By understanding your customer's behavior, you can use audience triggers to target your marketing campaigns better and optimize your website for higher conversions.

Using audience triggers is a powerful way to gain insights into how your website is being used and what types of visitors are most likely to convert. This can help you create more effective marketing campaigns and tailor content to different customer segments.

Audience triggers also allow you to segment users by various conditions, tracking user engagement over time or comparing the performance of different customer segments. With these insights, businesses can better understand their customer base and make more informed decisions about their digital marketing strategy.

What is a Predictive Audience in Google Analytics 4?

A Predictive Audience in Google Analytics 4 is a group of users predicted to be more likely to take specific action on your website, such as making a purchase or subscribing to a newsletter. This is determined through machine learning algorithms that analyze user behavior and demographics to identify patterns. You can use Predictive Audiences to guide personalized marketing efforts and improve the effectiveness of your online campaigns.

What is an attribution model, and what attribution model does Google Analytics 4 use?

Attribution models are used to track how customers interact with your business across multiple channels, such as organic search, paid search, social media, or email. They measure the effectiveness of each channel and assign a value to each touchpoint in the customer journey toward conversion.

Google Analytics 4 uses an advanced attribution model called data-driven attribution (DDA). This is an algorithm that analyzes customer journeys and assigns values to each touchpoint based on its impact on the conversion. DDA uses machine learning to analyze data from your website, such as pageviews, time spent on a page, and more. It then uses this data to assign a “credit” to each touchpoint in the journey leading up to a conversion. This design helps you understand which channels are most effective at driving conversions and how much value they contribute.

Final Thoughts

Google Analytics is sunsetting Universal Analytics in favor of Google Analytics 4. This brings challenges for marketers that have been using Universal Analytics for quite a long time. The decision to sunset this version finds its roots in an ever-growing need for privacy. However, you can question the legitimacy of this when looking at Google Analytics 4. Some EU Member States have already found the use of Google Analytics (any version) unlawful in their country, and it is expected that more Member states will follow.

With this in mind, plus the fact that Google Analytics 4 is a complex tool that requires a lot of learning, marketers and business owners might question whether they still want to continue using Google Analytics at all.

In an ever-growing competitive landscape, more and more web analytics tools are presenting themselves as an alternative to Google Analytics. The privacy flaws in Google Analytics are also why we built Simple Analytics. A privacy-friendly Google Analytics alternative that is simple to use (hey, what's in the name, right?). Feel free to check our live dashboard to see whether you like it. If this resonates with you, feel free to give us a try!

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