Hits (GA) vs Events (GA4)
One of the most significant changes in GA4 is the shift towards event-based tracking. Unlike UA, which records each interaction on your website as hits, GA4 records each interaction as events.
(Old) Universal Analytics
Uses a hit-based model, which means that each interaction with your website or app is recorded as a separate hit. This includes things like:
- Page views, button clicks, and form submissions. Each hit is then assigned a category, action, and label. For example, a page view might be assigned the category “Page views”, the action “View page”, and the label “Homepage”.
(New) Google Analytics 4
Uses an event-based model, which means that each interaction with your website or app is recorded as an event. Events can be anything that you want to track, such as:
- Button clicks, form submissions, or even scrolling to a certain point on a page. Events are assigned a name, parameters, and a value. For example, a button click might be assigned the name “button_click”, the parameter “button_id”, and the value “123”.
Why event-based model (GA4) is better:
a. It is more flexible.
With the event-based model, you can track any user interaction, regardless of whether it is a standard event, such as a page view, or even a custom event such as a user clicking on a specific button.
b. It is more accurate.
With the hit-based model, it is possible for multiple hits to be generated for the same user interaction. This can lead to inaccurate data. With the event-based model, only one event is generated for each user interaction, which ensures that the data is accurate.
Here is a simple analogy to help you understand the difference between the two models. Imagine that you are a teacher and you want to keep track of your students’ progress. With the hit-based model, you could only track things like how many times each student attended class and how many assignments they turned in. With the event-based model, you could track anything that you wanted, such as how long each student spent on each assignment, what questions they got wrong, and even how often they raised their hand in class.
AI-Powered
By applying Google’s machine learning models, GA4 introduces several new features when compared to Universal Analytics (UA). Two of the new features include Predictive analytics and Analytics Intelligence.
Predictive Analytics
GA4 can analyze your data and predict future actions people may take. For example, GA4 introduces two new predictive metrics:
a. Purchase Probability
Predicts the likelihood that users who have visited your app or site will purchase in the next seven days
b. Churn Probability
Predicts how likely it is that recently active users will not visit your app or site in the next seven days.
Analytics Intelligence
Analytics Intelligence is another set of features that uses machine learning and conditions you configure to help you understand and act on your data. Analytics Intelligence provides two types of insights:
a. Automated insights:
Automated insights are automatically generated by Analytics Intelligence when it detects unusual changes or emerging trends in your data. These insights will be displayed on the Insights dashboard within the Analytics platform and show you things such as user growth from a certain campaign source, which source drove the most conversions, users engagement rate.
b. Custom insights:
Custom insights can generated when you create conditions that detect changes in your data that you think are important to you. For example, you can se the condition to detect a 20% decrease/increase for the past 30 days of your active users. When this condition is triggered, you see the insights on the Insights dashboard and can optionally receive email alerts.
Here is a step-by-step guide on how to create your own custom insights: https://support.google.com/analytics/answer/9443595?hl=en
Bye Bounce (UA), Hi Engagement (GA4)
Another change in GA4 that might confuse you is the lack of bounce rate in the reports section. Although bounce rate is not completely abandoned in GA4, but bounce rate is essentially replaced by the newly updated engagement rate.
Why?
Previously (UA), the calculation and determination of bounce rate relied solely on one factor: the percentage of sessions in which a user visits only one page of the website and leave without any action. However, this approach may inaccurately reflect the actual level of user engagement, particularly when the website being visited consists of a single page, such as a landing page.
What is Engagement rate?
In order to replace bounce rate, the engagement rate is born. It is calculated based on the percentage of engaged sessions out of all sessions visited to your website. Engaged sessions is more accurate and is a better indicator of real engagement level of users on your website because it takes into account whether:
a. the user has visited more than 2 pages.
b. the the user has stayed in the website for more than 10 secs and activated at least 1 conversion event.
These 3 biggest changes of GA4 is setting it up to be a clear upgrade. If you are one of our existing clients, we have upgraded to GA4 to continuously monitor the performance of your campaigns and websites performance.