Get to know Google Analytics 4: –
Data is collected differently, stored differently, and even displayed differently.
All of this change can be frustrating, but GA4 is a bit more advanced than the previous version.
Google Analytics 4 (or GA4) is a completely new version of Google Analytics.
The new version will be rewarded with an analytics tool that provides a better representation of user behaviour, respects user privacy preferences, and allows less time to be spent collecting and aggregating data.
This is possible thanks to three technologies that Google has been working on in recent years:
Firebase Analytics:
Firebase is a suite of products for developing mobile applications that Google acquired.
Firebase Analytics uses something called an “event-driven data model” to better describe behaviour and measure user engagement.
Firebase Analytics is the backend for Google Analytics 4. This means that data captured from both websites and native applications now share a single format.
Google signals:
GA4 is based on Google Signals.
You’ve probably heard of Google Signals before because this is identity software that Google accounts use to recognize logged in users.
It’s the same method that Google uses behind the scenes to build audiences, and Google Analytics 4 can now use this feature to recognize users instead of relying on first-party cookies.
The global site tag:
Google Analytics 4 is also based on the global site tag.
The benefit of this technology is that it allows you to make changes to the user interface that actually change the code that is implemented on the website.
With GA4, a feature can be activated to track when users play a YouTube video, and the code will be automatically deployed to the site without a change to the tag manager.
The event-driven data model:
Sessions are hands down the most important metrics in legacy Google Analytics reports.
From goals to conversion events:
A user completes a goal in Google Analytics when he takes some action during his session.
If the action is performed multiple times during the session, we only count it as single goal achievement.
GA4 has removed the concept of goal and replaced it with conversion events.
A conversion event is simply any event that has been marked as important to the business.
Acquisition versus reclosing:
When evaluating how well your traffic channels are converting, you must now decide whether you are evaluating how well you are acquiring new customers or re-engaging existing customers.
If you choose the “User Acquisition” report, conversions will use first-touch attribution.
But if you choose the “Traffic Acquisition” report, your conversions will use last-touch attribution.
There are three important things paid search administrators need to know about conversion events:
Users can complete multiple conversions within one session.
Each conversion event must have a unique name so that it can be marked as a conversion with the radio buttons I showed just now.
Qualifying for an audience can trigger a conversion event.
Audiences:
Remember that the old version of Google Analytics allowed you to create user segments.
In Google Analytics 4, the concept of the segment has been merged with the concept of audience.
Instead, just create audiences.
Audiences can be applied to any report and can also be shared with Google Ads.
Another thing that is different about audiences is that once one has created one, it is automatically shared with everyone else using Google Analytics 4.
So there is no need to pass links to co-workers so they can download the audience you are using.
Predictive audiences:
Google has released a series of predictive audiences that can be autogenerated for (which are similar to the smart audiences you may be familiar with).
These audiences use Google’s machine learning to rate the likelihood that a user will make a purchase or abandon in the next 28 days so that you can spend the remarketing budget to reach the customers who will have the most impact.
New engagement metrics:
All metrics that were previously calculated based on sessions have changed.
These have been replaced by a new and very important metric that is automatically recorded in GA4 called “interaction time”, which is the amount of time that the user actively viewed your content.
If the user is in a mobile app, this is the time the app was in the foreground.
Google Analytics 4 uses this metric to calculate: Committed sessions.
Participatory sessions and participation rate.
A committed session is a session with more than 10 seconds of participation time.
Divide the number of participation sessions you had during a time period by the total number of sessions to calculate another new “participation rate” metric.
This is the metric you will use in place of the bounce rate in GA4 (read more about the engagement rate here).
Engagement rate is a much more useful metric for measuring user engagement, especially on sites like blogs and media where a successful session can only include a single page view.
Active users:
To point out that Engagement Sessions and Engagement Rate are session-based metrics. Sessions have not disappeared with GA4, despite the increased emphasis on users. But we also have a new metric called Active Users.
An active user is someone who has had at least one interactive session during the date range she selected.
Before continuing, there is one more thing I want to point out about these new engagement metrics.
Improved data import:
Neither of these is affected when you import external data.
The details on this are a bit technical, but this solves a big problem with Universal Analytics.
This was very frustrating for many analysts, but since those events don’t contribute to GA4 engagement time, they have no impact on your engagement metrics.
This makes integrations with Salesforce or calls tracking tools much smoother than before.
Okay, I have three more items to discuss, and they all revolve around user privacy.
New privacy controls:
First of all, Google Analytics 4 provides a long list of new privacy controls that marketers can use to ensure they are compliant with the latest regulations.
Disable ad personalization:
The first is the option to disable ad personalization.
This is useful for marketers who want to use Google Analytics to understand user behaviour, but do not plan to generate audiences for remarketing.
In this case, a user with “Edit” permissions can completely disable audiences for remarketing so that no one in the company can turn it on.
Not for customization:
Within a geographic region where you are using Ad Personalization, specific events that may be private in nature can be excluded so that they cannot be used to generate audiences.
Google Analytics 4 is embracing user privacy:
It is important to note that enabling many of these privacy controls will create data breaches.
Most analytics tools have worked very hard to eliminate data gaps.
These new privacy features in Google Analytics 4 actually move in the other direction: they give you more controls to adopt privacy when the user requests it.
Google is taking the necessary steps to lead us into a world of incomplete data, where we are not so reliant on cookies.
For the past 3 years, Safari and Firefox have taken great steps to limit how long a cookie can exist and to remove cookies that are used to track users across all sites.
For example, most websites now show a higher number of users on Safari than two years ago.
Therefore, Google Analytics has to help marketers prepare for the regulatory restrictions that come from the GDPR and CCPA, but they also have the new burden of helping marketers prepare for the technical restrictions imposed by the browsers.
In response, Google has announced two features coming soon to GA4: Identity Reporting and Conversion Modeling.
Denunciation of identity:
Traditionally, Google Analytics has identified a user on the web by setting a cookie (called a customer ID) or by using something called an application instance ID in a mobile application.
If you are lucky enough to have registered users on your site, you can set your own unique identifier for users (called a user ID).
The benefit is how often users log into the site from different devices.
Go to your property settings and click on “Identity Reports” for two options: “By Device Only” (which means you are only using the Customer ID and have no logged-in users), or ” By user ID, Google Signals, and then device ”.
The feature will be available to users who have signed into a Google account on their device and have opted for ad personalization.
If you enable this feature, GA4 will continue to use the user ID if available, as it is the most accurate way to identify a user.
As a result, you will be able to identify a portion of the users on all devices, even if they are not logged in.
This is important because it means that it will generate very comprehensive data for the small subset of users who have signed in to Google, use Chrome, and have enabled ad personalization.
Having good information about this small subset of your users will help you fill in the data gaps that exist in the rest of the user population.
Conversion modelling:
The conversion model is different from the attribution model.
The idea is for Google to use machine learning to fill in the gaps that we know exist in our data.