According to the developers’ statements, the new version of Google Analytics officially came out of beta in the fall of 2020 and is intended to optimize advertising investments in the long run.
Google Analytics 4 is an analog of Firebase Analytics (an analytics system for mobile applications) but with additional features. The interface and logic of data accounting is also taken over from there.
What are the key benefits of Google Analytics 4, and how does this new version differ from Universal Analytics? Why should we forget about Universal Analytics and move to Google Analytics 4?
Google Analytics 4: Why this particular name?
It’s a good move because it positions the product as a “new GA” rather than something designed exclusively for those who have apps. But why Google Analytics 4? The name can be a little confusing if you’re not familiar with the evolution of Google Analytics. Originally, Urchin (#1) was a company that Google bought in 2005. Classic Analytics (#2) was the next iteration, later replaced by Universal Analytics (#3), which is currently used widely on the majority of websites.
Google Analytics 4: What’s New
It’s scalable, cross-platform analytics that is built around events.
Previously, data tracking was based on sessions, an artificially derived metric. In the new version, Google is focusing on users, so it has consolidated all the analytics around events. You can now track the entire user journey, meaning you can collect the same standardized data across all devices and platforms.
For example, page views, session starts, transactions, etc. are sent as events to GA4. So anything you track in GA4 is an event.
The new resource uses three levels of identification:
- Google Signals
“Google Analytics 4 unifies all the analytics around events, allowing you to collect the same standardized data across all devices and platforms. You’ll have the same set of events on both the website and the app. For example, we have an add-to-cart on both the website and the app. Google Analytics 4 has tracking and customization, so you will be able to track this event as one for both platforms. This will improve the data quality, and you can get a single report for the entire user journey.”
The calculation of many web analytics metrics, such as bounce rate, session duration, and pageview time, has also changed completely.
Machine learning and NLP (Natural Language Processing) functions in the new GA version are available to all users.
Such functionality was partially present in the old counter, but few people were using it. Therefore, the new version will most likely include more extended features. At the moment, the functionality is still being finalized.
Machine learning and NLP features are key advantages of GA4. You will now be able to:
- Predict the probability of conversions and create audiences for Google Ads based on these predictions.
- Find anomalies in reports. Here we’re talking about notifications, which were in Universal Analytics as well. If there are any errors (conversions are not tracked, conversion rates are miscalculated), you’ll know about it immediately.
“Always pay attention to the Bell. These notifications contain a lot of helpful information. For example, we often get requests for bug fixes, and quite often, these notifications help us find them”.
- Predict the likelihood of customer churn to invest money more effectively in retaining them. The Google team plans to further develop this area by adding new predictive metrics. For example, ARPU so that all users of the new resource can adjust their marketing strategy and increase their ROI with ML insights.
- Also, GA will now alert you to significant data trends. For example, items that are increasing in demand due to changes in user needs.
Privacy is a priority
Google says they plan to move away from cookies altogether in the future and focus entirely on tracking by browser ID and mobile devices.
“There are a lot of brands out there right now that have a tracking problem. For example, in the banking niche. A tiny percentage of users are tracked, and the data is hard to work with and almost impossible to make decisions based on it.”
The gtag.js library, which works without cookies, is already being used.
“The latest version of Universal Analytics uses this library, but not many people switched to it because the library has to be inserted into the site code. We don’t recommend switching to gtag.js and continuing to use the standard Universal Analytics, which is installed through Google Tag Manager.”
We can also expect that shortly, Google will abandon Client ID and rely only on internal device and browser IDs and the cross-platform ID that the CRM generates, i.e., the User ID.
IP-anonymization in GA 4 is set by default and cannot be changed. IP-anonymization was not tracked in GA before, but before, it was possible to customize and track; it cannot be done in the new analytics.
Seamless integration with Google tools
So far, the most advanced feature in this section is integration with YouTube. Google is actively working to improve the quality of evaluation of YouTube campaigns. For example, it tracks View-through conversions, which allows you to understand:
- How a YouTube ad campaign affects the achievement of specific engagement metrics.
- How it affects the bounce rate, as well as certain events on the site (not necessarily conversions).
“In the current GA, the analysis of YouTube campaigns is not efficient enough. The new version will be more advanced in terms of functionality, and it will be possible to analyze YouTube statistics in the Analytics interface itself.”
The new analytics version also features deeper integration with Google Ads. With it, you can build audiences, launch campaigns, and attract new customers with more relevant and valuable offers, no matter what device they’re using.
“GA 4 has a direct free data export to Google BigQuery. Previously, the export function was only available in GA 360 and for a fee. In GA 4, it was made free, but now you can use Google BigQuery for free for only three months instead of a year.”
The benefits of Google Analytics 4 from Universal Analytics. Key metrics
- What was before is reduced to a minimum and tracked by four main metrics.
- In Google Analytics 4, analytics is not built around sessions but around events. Because sessions are an artificial concept, Google suggests that you abandon them. However, if you need session data, you can generate it yourself by working with raw data in Google BigQuery.
- There are end-to-end data collection settings for the entire site and those that change with each event. In addition, there are formal events that are tracked basically across all platforms when you install GA.
- GA 4 provides built-in end-to-end reports by User ID. Therefore, you do not need to create a separate view to use User IDs.
- GA 4, similar to Firebase, will have three types of events and their parameters:
- Collected automatically: e.g., pageview, session start, view search results, scroll, file_download. Full list
- Business directions group recommended events. Full list
- Custom or all other events that you would like to implement and track. They are subject to GA4 limits.
“Now, every event can have additional parameters. If before we configured an event, it had a category, action, and label, now the logic is different: there is an event with one name, but you can pass additional parameters with this event. For example, “Adding to Basket,” before it was a separate script, a separate parameter for each value. Now it’s all gathered under one event structure (one event that includes: item name, item cost, size, color, and so on). Custom Dimensions are the transversal parameters and indicators for most reports and help you stay within the GA 4 limits.”
- In Google Analytics 4, there are no such concepts as category, action, and event labels. These properties are mapped to the parameters of the event being configured for existing settings and collected data. If you want to see the properties in GA 4 reports, you need to register them.
- Pageviews have become pageview events. Views used to be pageviews and now it’s a pageview, and with each pageview the preset parameters are passed. This event is collected automatically if you have the “config” fragment of gtag.js implemented.
- There will be four sessions in GA reports, but they will be counted differently than in Universal Analytics:
- The automatically collected session_start event initiates a session.
- The session’s duration is the interval between the first and last events.
- Interactions are recognized automatically (sending an interaction event is not required).
- The timeout of late requests processing is 72 hours (vs. 4 hours in UA Properties).
“If you compare the number of sessions in GA 4 and the Universal Analytics report, you may find that GA 4 has fewer sessions. That’s because hits that were sent after the session ended can be assigned to the correct session for 72 hours. Accordingly, session reports will take longer to generate. In GA 4, it is not possible to adjust the duration of a session.”
- Custom dimensions and metrics. For custom dimensions & metrics to be included in GA 4 reports, they need to be transferred to the new resource according to Google rules. For example, if the hit level and user level parameters have analogs in GA4, there is no equivalent for the session-level parameters. Alternatively, you can define them at the hit level. To use custom product level definitions, they have to be added separately. How this will work is not clear yet. The feature is still in progress, and there are no eCommerce reports containing custom product level definitions.
“Previously, there were four levels of metrics focused on hits, users, sessions, and products. Now, their equivalents are: events and event parameters, user properties, sessions — still unclear, products — eCommerce parameters that have not yet been implemented.”
- GA 4 has a new feature — User Properties. These are definitions that correspond to a specific audience/a particular user: gender, city, a sign of a new or returning customer, a sign of a regular customer, etc. Properties that relate to specific users apply to all of their behavior. For example, audiences are formed to personalize ads based on user properties.
- A new approach to presenting data. For example, this is what the Traffic Sources report looks like now:
- New custom report designer. The My Reports menu item as such no longer exists. Instead, it has been replaced by the promising Analysis, which consists of two tabs: Analysis Center and Template Gallery. Also, the report types have been replaced by Methodologies.
- Sequence analysis. The funnel can be set manually if you have a set of events to form the funnel. First, you need to set up proper tracking, then generate such reports.
In the same report, you can create segments for any step in the funnel
- Creation of conversions in one click. You don’t need to create targets manually anymore, you need to click on events, and those that are tracked will become conversions.
- New editor for creating segments and audiences. You can now add a new part from the funnel steps by clicking on an option from the menu.
Ten reasons to switch to Google Analytics 4 or what you gain when you switch to Google Analytics 4
1. Universal Analytics stops working in 2023. Universal Analytics will stop processing new data in standard resources on 01.07.2023.
2. GA4 provides a web and mobile app platform. You no longer need to switch between GA3 and Firebase. You can combine data from websites and mobile apps into one resource.
3. GA4 pays a lot of attention to the user journey. Now, you can measure user interaction across all platforms and get a holistic view. In other words, if a user from a computer or phone performed some actions on your website and then downloaded your company’s mobile application and made a purchase or other actions, GA4 allows you to combine user actions using different devices and then accurately reflect them in reports.
4. Much more user-centric interface. GA4’s interface is very different from Universal Analytics, giving marketers a more significant advantage in getting user-centric reports.
5. Predictive analytics capability. The ability to use predictive indicators to predict possible user actions. Currently, GA4 supports three predictive indicators: the probability of purchase, churn probability, and revenue forecast.
6. Enhanced analysis reporting. The following analysis methods are currently available:
- Randomized form
- Group study report
- Sequence study report
- Segment overlap report
- User browser report
- Path study report
- User lifetime report
7. Easy configuration of conversion and event tracking. Unlike Universal Analytics, in GA4, you can easily mark any registered event as a conversion.
8. Automatic event tracking. The ability to automate certain types of events with advanced measurements, which is not possible with Universal Analytics.
9. Quick data checking and auditing are built into the user interface. Implementing easy debugging thanks to the real-time DebugView report. This report allows you to monitor real-time data about your website events and customizable parameters and user properties.
10. Free connection to BigQuery. You can export all your raw event data from GA4 and then run queries and export them to an external tool.
How to set up data collection for Google Analytics 4
1. Create and configure a GA resource 4. You cannot merge the old data with the new counter. This is because the resources have different logic.
2. Add tracking code manually or through GTM. We recommend using the Tag Manager because it is more convenient and faster.
3. Think about what events and parameters you want to collect in the new resource type.
4. Use two resource types simultaneously to compare how data is collected.
- you can add ONLY one Firebase project to one GA 4 resource. If you already have a project in Firebase that is tracked;
- you can set up multiple threads from different applications in a single GA 4 resource.
If you need advice or help, our team knows all the intricacies of GA4 setup, and we can help your business migrate to the new Analytics version 4.
Also, our team has expertise in solving a variety of tasks, from basic tracking system settings to building complex data structures, followed by visualization and report automation.
We offer the following solutions to eCommerce businesses:
- Mobile analytics
- Marketing analytics (end-to-end)
- Product analytics (web, mobile)
- Forecasting (machine learning)
- PVC analysis (media analysis)
- Visualization (DataStudio, PowerBI, Tableau)
We are ready to discuss the tasks and begin work as soon as possible with you.