Even if your current Google analytics implementation and setup is close to perfect and you weren’t planning to make changes, you should strongly consider upgrading to Google Analytics 4.
Reasons to Make the Switch:
1. A History of Ongoing Improvement
Google Analytics 4 is the newest version of a tool that first launched 15 years ago
Google acquired Urchin Analytics in 2005. Two years later, the traditional (classic) Analytics code was developed. By 2013, a new version, Universal Analytics, launched into open beta, and became the prevalent platform type. In October 2020, Google Analytics App+Web – now renamed as Google Analytics 4 — launched in the beta stage.
By the way, if you were wondering why it is called GA4 – that name stands for the “Google Analytics v4”, or the fourth version of the source code. Urchin’s code was the v1; Classic Analytics increased the counter to v2; Universal analytics is considered v3 – and the now-current version is, well, “GA4”.
2. Focus on the User
Google Analytics 4, is a complete restructure of the Google Analytics tool offering benefits for both marketing and web analytics. It has revamped measurement, reporting, analysis, audience management, and prediction capabilities.
This new tool is built around the event-based data model which goes beyond the traditional concepts of a session and works better for app tracking. Sessions are put to a backburner and are no longer relevant for reporting. User-centricity becomes the main metric of the model.
Underlying data includes events and their parameters. So, you don’t have different types of hits anymore, e.g. pageview, transaction, social, or screenview. Each hit is treated as an event now and has or may have associated parameters.
This simplifies understanding tracking and reporting specifics and eliminates any confusion with scoping in Google Analytics. Do you remember thinking of selecting a scope for a dimension or trying to determine which dimensions can be paired together in a custom report? Now it’s that easy: there are events with associated parameters and there are users with associated user properties.
The data model shift also means simplified implementation. All events have the same format and code syntax, all user properties are consistent for implementation as well. Ecommerce tracking syntax becomes a bit more straightforward as well.
Google worked on enabling smooth migration to the new platform: if you were using gtag.js code syntax for Universal Analytics you’ll be happy to find out that it’s fully compatible with GA4 instrumentation and requires minimal changes to the code (mostly, adding the GA4 measurement ID). If you are using GTM you can update your Analytics implementation by creating corresponding tags in the UI. Then, based on the complexity of your code in the dataLayer you may or may not need to repurpose the data for GA4 usage. Even when doing so, you’ll have a chance to do all the adjustments within the Tag Manager UI and not touch the code.
Google Analytics 4 even collects some events automaticallyfor you, without any instrumentation, including pageviews, first visits, session starts. The list of events captured by default is bigger for apps. Some events were only available in the past when implemented additionally but now they can be set up just by enabling the Enhanced Measurement toggle in GA4 property settings:
Google Analytics 4 also prescribes a list of recommended events and their associated parameters for more robust reporting, integrations, and to lay the foundation for any future updates once they become available.
In addition, this model was initially designed for mobile apps and was used in Firebase Analytics which means that it’s still highly relevant for app tracking but is now being applied to website measurement. For users who put greater emphasis on using mobile app reporting there is still the Firebase reporting selector in the top left-hand dropdown of the GA navigation panel.
So, the new Analytics solution offers simplified measurement model and instrumentation methods. This frees you up from unnecessary development work for paying more attention to the performance and strategy. The model becomes user-centric and shifts the focus to your userbase, not their sessions.
3. Streamlined Reporting
The ABC reporting flow in Analytics (Acquisition, Behavior, Conversion) remains. What changes: Behavior has been renamed to Engagement, Conversion to Monetization, and Retention has been added reflecting Google’s emphasis.
Acquisition reports are split into User Acquisition and Traffic Acquisition. GA4 provides more user-centric reports with increased importance of visitor-level attributes, including acquisition medium/source, acquisition campaign, and others that are clearly differentiated from session-based dimensions (session source/medium).
In terms of Engagement, Google Analytics has replaced Bounce Rate with Engagement rate. Now a user is considered ‘engaged’ if they spend at least 10 seconds on the site or app, have a conversion event, or view 2 or more pages/screens. Instead of the Session Duration metric, it’s now measuring Engagement Time which provides a clearer picture of how long a user actually interacts with the site or app. The above changes are intended to measure engagement more accurately across platforms.
Events have become a structural unit of the data model and reporting, being available in most of detailed reports as the Event Count metric. You can easily see the count of each event you’re tracking associated with a specific browser, traffic source, or user segment, as you could with goals in Universal Analytics.
Most importantly, GA4 reporting is now providing a unified view of your customer base aggregating multiple web and app streams into a single property. It also enables consistent cross-platform reporting, making it comparable for different technologies and painting a picture of what of your digital assets performs better. Having a deduplicated view of customers across platforms is able to reveal insights into how users switch between web and app when first engaging with the brand, moving towards a goal or converting.
For the first time in history, Google Analytics 4 offers BigQuery integration to all Analytics customers. As Google’s warehousing solution, BigQuery would enable slicing and dicing exported data differently and run analyses unavailable in the Analytics interface. On the other side of things, BigQuery is the right tool for merging online sources with offline datasets, 3rd-party data, or other tools. Even with Analytics reporting being a bit less flexible than Universal Analytics (which won’t last long, I believe) you’ll get access to enhanced analysis capabilities with BigQuery.
4. Better Analysis
The Analysis tool (formerly, Advanced Analysis) has been offering a highly flexible exploration and analytics framework for customers of the enterprise platform version. Now that it’s available to all GA4 customers it included a set of expanded capabilities and techniques: Cohort Analysts, Path Analysis, and User Lifetime.
Cohort Analysis is adding customization and greater level of detail for identifying user retention trends for various customer segments and thus, is reflecting Google’s reconsidered approach to customer retention as a valuable part of a user lifecycle.
Google Analytics 4 has also taken an important step toward user-centric analysis shifting focus from session-level dimensions to ones associated with the lifetime of a user: first visit, first purchase, last interaction, and last purchase. Those dimensions are available for performing analysis in the User Lifetime technique and some other reports, but we’d look forward to having them in audiences as well.
The Path Analysis functionality is taking customer journey exploration to the next level. It helps you look deeper into the steps users take moving through your app or website. In addition to what the Funnels technique provides, Pathing also enables to explore multiple user paths instead of analyzing a pre-defined, pre-configured, rule-based path in the standard funnel visualization.
The new Analytics solution features unprecedented analysis and data exploration capabilities, not only providing them to all customers, but giving access to a few techniques that make it really advanced.
5. Expanded Audience Management
GA4 is also aiming to improve remarketing by building more robust and manageable audiences. So, you may find useful new more granular settings, such as:
– scoping improvements (conditions to match within an event, session, or all user activity);
– time window for metrics (when you can specify if a metric should have a specific value for all lifetime of a user or for a specified time frame);
-time constraints for sequences (when a few or all steps in a sequence should occur within a specified period);
– dynamic evaluation of inclusion (if users matching an excluding condition should be permanently removed or temporarily excluded while they match it).
In GA4 you are also offered to see how your audiences accumulate users by setting up Audience Triggers.
Improvements to audiences in the new solution free you up from manual work on managing remarketing lists in Google Ads and other tools and enable them to work dynamically to deliver perfectly tailored message to the targeted audience.
6. More Sophisticated Prediction
GA4 is leveraging machine learning to expand predictive capabilities of Analytics. A new set of predictive metrics has been released to be used in audiences and Analysis customized reports:
– Purchase probability (how likely a user is to convert in the next 7 days);
– Churn probability (probability that a user will not be active in the next 7 days);
– Revenue prediction (anticipated revenue in the next 28 days).
Google Analytics will enrich data collected about user online activity with predicted metrics to better react to customer intentions and to show a message that will increase their value to the business. For example, you may incentivize customers who are likely to purchase soon or aim your marketing at those who are expected to churn. The predicted revenue may be helpful for planning ROAS to justify spends on certain audiences.
7. Enhanced Privacy and User Controls
The digital environment has been continuously facing new regulations, changes in consumer privacy preferences, and development of new technology standards for a user’s consent to how their data can be used. GA4 has strengthened its position in the industry offering flexible data controls. So, GA4 can help you define when to dynamically disable ads personalization and offers more granularity over data deletion requests. You have greater control over what data you’re collecting and how it can be used, whether to customize your ads against that data or limit it to only reporting purposes. GA4 has progressed beyond Universal Analytics and will continue to evolve meeting industry standards.
8. Future-Proof Solutioning
Technology updates will continue to set the stage for tracking limitations and industry’s attempts to adapt. In this relation, GA 4 is about adjusting measurement, data model and processing to the world with or without cookies. As tracking accuracy is likely to be compromised in the worst-case scenario, the new Analytics version will use data modeling to fill in the gaps based on data-driven signals derived from your own data.
Google Analytics 4 is the latest generation of the web analytics tool meaning that it will be accumulating any future improvements or key updates with Universal Analytics becoming legacy now. Therefore, regardless of your current plans for using it, we recommend that you upgrade and start seeing its evolution until it becomes a full replacement for the current one.
The main idea of the migration is parallel-pathing the current and new Analytics solutions. As a newly created GA4 property collects more data you’ll have a chance to familiarize yourself with the new interface, check incoming data, and compare to the existing profiles. This will help you determine if there are discrepancies, adjust data collection if needed, and finally, be ready to the full switch as GA4 evolves and new integrations become available. Gradually, you’ll notice that Google Analytics 4 is becoming more powerful and meets all your data collection expectations you previously set for Universal Analytics.
From the technical perspective, Google established a process of enabling smooth migration to the new platform:
Step 1. Connect Property
Clicking the Upgrade to GA4 menu in property settings will initiate a setup dialogue where you’ll be able to create a new GA4 property or connect to an existing one.
- If you created an empty GA4 property previously you can use that one.
- You created a GA4 property previously and some data is already streaming into it. If you want to combine that data with the data of the given property, then select that GA4 under “I want to connect to an existing Google Analytics 4 property”.
- If you didn’t create a GA4 property previously select “I need to create a new Google Analytics 4 property”.
Result: this will enable tracking of automatically collected events (pageviews, session starts, outbound clicks etc.) that can be further customized in new GA4 settings
Step 2. Customize Implementation
1. If you were using gtag.js code syntax for Universal Analytics you’ll be happy to find out that it’s fully compatible with GA4 instrumentation and requires minimal changes to the code (mostly, adding the GA4 measurement ID).
2. If you are using GTM you can update your Analytics implementation by creating corresponding tags in the UI. Then, based on the complexity of your code in the dataLayer you may or may not need to repurpose the data for GA4 usage. Even when doing so, you’ll have a chance to do all the adjustments within the Tag Manager UI and not touch the code.
3. If you’re using Universal Analytics codebase syntax (analytics.js) we recommend implementing additional code for GA4 while keeping the existing instrumentation intact.
Please be sure to make this transition gradual as GA4 prepares to be the full replacement of Google Analytics. You can start with just basic connecting to a new GA4 property and instrument additional features (events, ecommerce tracking) as development resources become available.
INTERESTED IN MAKING THE SWITCH TO GOOGLE ANALYTICS 4?
DELVE is here to help
Reach out to Andy Semenihin, DELVE’s Head of Data, at Andy.Semenihin@delvedeeper.com.
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