An In-Depth Look at Google Analytics 4: New Capabilities, Benefits, and Disadvantages

We are living in a new, dynamically developing reality. Everything is changing: users’ behavior, data requirements, the needs of businesses, and the ways they work with data. The old approaches to analytics aren’t working anymore, and they definitely won’t work in the future post-cookie world. It is crucial to start collecting data with Google Analytics 4 as early as possible to benefit from long-term reporting and insights.

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About a year ago, the Google team presented App + Web functionality, which allows you to combine data from websites and mobile applications in one Google Analytics resource. Since then, Google has tested this new type of resource, made changes to it, finalized it, and brought it out of beta under a different name. Meet Google Analytics 4.

In this article, we talk about what Google Analytics 4 is, how it differs from Universal Analytics, what value it gives to businesses, and what problems you can solve with it. We also analyze which companies should start using Google Analytics 4 right away.

What is Google Analytics 4?

Google Analytics is one of the most popular digital analytics software tools that allows you to analyze marketing efficiency and website visitor behavior in depth.

Last year, Google announced the most significant change to Google Analytics ever: Google Analytics 4, a new version that’s very different from the traditional “Universal” Analytics. It was big news but came as no surprise.

The evolution of Google Analytics over the years has led to the development of Google Analytics 4. To create a new Google Analytics account and property, you need to sign in to your Google Analytics account, click on the Admin tab, and follow the prompts to set up a new property with the necessary permissions.

This is not the first time we’ve been introduced to a new platform. In 2005, Google bought the tracking platform Urchin, and since then the company has released several new versions of its analytics service.

However, most of these releases have tracked either websites or app properties — not both.

Previously, businesses needed two platforms — Google Analytics and Firebase — to analyze both websites and apps separately. These products are good ways to get data insights, but it was quite challenging to get a unified picture across apps and websites.

In 2019, Google took a big step and launched a beta property called App + Website. It was Google Analytics for Firebase but with web tracking capabilities. Now it is out of beta, and Google has renamed it Google Analytics 4 (GA4) — plus added tons more new features.

The new Google Analytics 4 comes with a bunch of key features that make it very different from the old version of Universal Analytics, and most people have a lot of questions about the new platform and what it means for the future of analytics.

We answer them in this article.

Benefits of Google Analytics 4

Google Analytics 4 offers advanced features designed to meet the evolving needs of businesses in a privacy-focused, multi-platform world. Data analytics plays a crucial role in modern marketing strategies, helping manage tags through tools like Google Tag Manager (GTM) and guiding decision-making while adhering to privacy regulations.

Tracking all the events is crucial for gaining valuable insights into marketing performance, especially for agencies managing multiple clients across various platforms.

Scalable Cross-platform Analytics

An event-based approach allows you to collect reliable and consistent data across multiple devices and platforms. Data analytics plays a crucial role in managing tags through tools like Google Tag Manager (GTM) and guides decision-making while adhering to privacy regulations.

In the standard web version of Google Analytics, everything is built around user sessions, and in Firebase, everything is built around events. Therefore, it’s difficult to analyze a user’s transition between platforms, since there’s no universal measure of user behavior. Even with raw data, you need to make a great effort to build a high-quality user flow.

Google Analytics 4 combines all analytics around events. This allows you to collect the same standardized data for all devices and platforms, improving the quality of your data and providing you with a single report across the user path.

Machine Learning

One of the main advantages of Google Analytics 4 is its machine learning and natural language processing (NLP) functions, which you can use to:

• predict the probability of conversion and create audience forecasts for Google Ads based on that probability
• warn you about important trends in your data (e.g. products that are in demand due to changing user needs)
• find anomalies in reports
• predict the likelihood of customer outflows so you can effectively invest in retaining customers

The Google team plans to continue developing in this direction and adding new forecasts such as ARPU so all Google Analytics 4 users can adjust their marketing strategies and increase their ROI using machine learning insights.

Privacy is a Top Priority

1. Google Analytics 4 is privacy-focused and uses the gtag. js library, which works without cookies. Accordingly, we can expect that in the near future, Google will abandon Client ID and rely only on the internal device and browser identifiers as well as a cross-platform User ID identifier generated in the CRM.
2. IP anonymization in Google Analytics 4 is configured by default and cannot be changed.

Seamless Integration with Google Tools

So far, the most advanced integration is with YouTube. Google is actively working to improve the quality of evaluation for YouTube campaigns (for example, to allow you to track view-through conversions). This will allow you to find answers to these sorts of questions:

• How does my YouTube ad campaign affect specific audience involvement indicators?
• How does my YouTube campaign affect the bounce rate, events on my website (not necessarily conversions), etc?

With deeper Google Ads integration, you can create audiences and run campaigns that attract new customers with relevant and useful offerings no matter what device they use. Connecting Google Search Console to GA4 is also crucial to gaining insights into organic search data, keyword queries, and overall marketing performance.

In addition, in Universal Analytics, the BigQuery Export feature is available only to users of the paid version, whereas in Google Analytics 4, this feature is free for everyone. You can activate data collection in BigQuery cloud storage in the Google Analytics 4 resource settings.

Cross-platform User Identification

Google Analytics 4 considers individual users who interact with your company, not the devices and browsers they use.

It does this using three levels of identification:

• User_id
• Google Signals
• Device_id

A crucial feature in Google Analytics 4 is the concept of a data stream, which allows the integration of data from both web and app platforms. Correctly configuring these streams is essential for effectively tracking user interactions and behaviors across various devices.

By implementing event-based analytics, Google Analytics 4 enables you to better track a user’s path from first touch to conversion and reorder. Moreover, if a user completes the same event more than once using different devices, the data for this event will be merged into a single touchpoint. For example, if a customer puts an item in the shopping cart on a smartphone and then on a laptop, the “Add to shopping cart” event will only be counted once.

Advanced Funnel and Path Analysis

Google Analytics 4 offers built-in funnel exploration and pathing tools, allowing for more flexible analysis of user journeys. Businesses can visualize how users navigate through their site or app, identifying drop-offs and optimization opportunities. Unlike Universal Analytics, GA4 enables custom funnel creation with real-time insights, helping teams refine conversion strategies effectively.

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Setting Up Google Analytics 4

Setting up Google Analytics 4 (GA4) is a straightforward process that can be completed in a few steps. Here’s a step-by-step guide to help you get started:

Creating a Google Analytics 4 Property

To create a GA4 property, follow these steps:

1. Sign in to your Google Analytics account: Begin by logging into your existing Google Analytics account.
2. Access the Admin panel: Click on the “Admin” button located in the bottom left corner of the page.
3. Create a new property: In the Property column, select “Create Property” from the dropdown menu.
4. Select GA4 as the property type: Choose “Google Analytics 4” as the property type to ensure you are setting up the latest version.
5. Enter property details: Provide a name for your property, select your industry category, and choose your reporting time zone and currency.
6. Proceed to the next step: Click “Next” to continue with the setup process.
7. Review and accept terms: Carefully review the terms of service and click “Create” to finalize the creation of your GA4 property.

By following these steps, you will have successfully created a new Google Analytics 4 property, ready for data collection and analysis.

Enabling GA4 via Google Tag Manager

To enable GA4 via Google Tag Manager (GTM), follow these steps:

1. Sign in to your GTM account: Log into your Google Tag Manager account to begin the setup process.
2. Create a new tag: Click on the “Tags” tab in the top navigation menu and then click on the “New” button to create a new tag.
3. Select the tag type: Choose “Google Analytics: GA4 Configuration” as the tag type.
4. Enter your GA4 property ID: Input your GA4 property ID, which you can find in your GA4 property settings, and click “Save” to save the tag.
5. Set up the trigger: Click on the “Triggers” tab and select “All Pages” as the trigger type to ensure the tag fires on all pages of your website.
6. Save the trigger: Click “Save” to save the trigger configuration.
7. Configure the variable: Navigate to the “Variables” tab and select “Google Analytics: GA4 Configuration” as the variable type.
8. Input your property ID: Enter your GA4 property ID again and click “Save” to save the variable.
9. Publish the changes: Finally, click “Publish” to apply the changes to your GTM container.

By following these steps, you will have successfully enabled GA4 tracking on your website using Google Tag Manager, allowing you to start collecting valuable data.

Is Universal Analytics Going Away, and Should We Switch from Universal Analytics to Google Analytics 4 Right Now?

Universal Analytics has already been discontinued, and all users must transition to Google Analytics 4 (GA4) for continued tracking and reporting. If you haven't switched yet, it's essential to act now to avoid data gaps and ensure a smooth transition.

Data continuity and reporting are important to every business’s success and growth. That’s why we recommend implementing GA4 as an additional analytics tool in your stack and starting to collect data and build out your new Google Analytics 4 property today so you have historical data to properly leverage the platform. Google also recommends this practice on its own website

GA4  has introduced an event-based tracking system, which is fundamentally different from UA’s session-based model. Metrics and reports won’t directly translate, so businesses need time to adapt to the new interface and data structure.

Parallel Tracking Was the Best Practice, But Now GA4 is the Only Option. Previously, businesses were encouraged to run Google Analytics 4 (GA4) alongside Universal Analytics (UA) to get accustomed to the new system while relying on UA for reporting. This approach allowed companies to accumulate historical data in GA4 while still leveraging UA’s familiar session-based model.

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The difference between Google Analytics 4 and Universal Analytics

Let’s compare the key tracking concepts in Universal Analytics and Google Analytics 4:

• Event-Based Tracking Model: GA4 is built around an event-based tracking model, moving away from session-based tracking used in Universal Analytics. Since sessions are considered an artificial concept, GA4 encourages users to focus on event-based interactions. If session data is required, it can be reconstructed using raw data in Google BigQuery.
• Flexible Data Collection Settings: GA4 provides advanced data collection settings at both the website level and individual event level, allowing more control over how data is gathered and processed.
• Built-In User ID Reports: Unlike Universal Analytics, where a separate view was needed for User ID tracking, GA4 includes built-in User ID reports, simplifying cross-device and cross-platform tracking.
• Seamless Integration with Google Marketing Platform: GA4 is designed to work seamlessly with the Google Marketing Platform, unifying data across platforms. It also leverages advanced machine learning insights, making it a powerful tool for modern analytics and marketing.
• Event Types and Parameters: GA4 categorizes events into three types, similar to Firebase. Each event can include custom parameters, allowing for more granular tracking and analysis of user interactions.

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Three Types of Event Tracking and Settings in Google Analytics 4

Collected automatically — example: page_view, session_start, view_search_results, scroll, file_download (See the documentation for a complete list of events.) Recommended events are grouped into business areas: retail and e-commerce, travel, and games (See the full list here.) Custom — all other events you would like to implement and monitor (Limited by Google Analytics 4.)

Event tracking in Google Analytics 4 is significant as it provides detailed insights into customer behavior by allowing an automated collection of user interactions across the entire user journey.

Recommended and custom events are implemented independently.

Each Event can have Additional Definitions

Custom Definitions are dimensions and metrics that are end-to-end for most reports and help you stay within Google Analytics 4 limits.

No Categories, Actions, or Event Shortcuts

Google Analytics 4 doesn’t have such concepts as category, action, and event shortcuts.

For existing settings and collected data, these properties are mapped to event settings. If you want to see properties in Google Analytics 4 reports, you need to register them.

Page Views have Become page_view Events

These events are automatically collected if you have a “config” gtag.js fragment implemented.

The page_view event has these preset parameters:

• page_location
• page_path
• page_title
• page_referrer

Sessions and Session Counting in Google Analytics 4

Google Analytics 4 reports have sessions, but they’re considered differently than in Universal Analytics:

1. A session is triggered by the automatically collected session_start event.
2. The session duration is the interval between the first and last events.
3. Interactions are automatically recognized (no interaction event needs to be dispatched).
4. The late case processing timeout is 72 hours (versus 4 hours in UA Properties). If you compare the number of sessions in a Google Analytics 4 and Universal Analytics report, you may encounter fewer sessions in the former because hits sent after a session is complete can be assigned to the correct session within 72 hours. Accordingly, session reports are issued for a more extended period.
5. The session duration cannot be configured in Google Analytics 4 at this time.

Custom Dimensions and Metrics

For custom dimensions and metrics to be included in Google Analytics 4 reports, they must be transferred to a new resource according to Google’s rules. Whereas hit-level and user-level parameters have analogs in Google Analytics 4, there are no equivalents for session-level parameters. Alternatively, you can define them at the hit level.

To use custom product-level definitions, you must add them separately. It isn’t yet clear how this will work because the feature is still in development and there are no reports on Ecommerce that contain custom product-level definitions.

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User Properties (new)

Google Analytics 4 has introduced a new User Properties feature.

User Properties are definitions that correspond to a specific audience/user: gender, city, new or returned customer, permanent customer, etc.

Properties that affect specific users extend to all their behavior. Based on User Properties, Google Analytics 4 forms audiences for personalizing ads.

Cross-platform tracking (web data stream and apps)

If your business owns websites and mobile apps, you can now conveniently stream data to the same property.

Previously, if you wanted to measure your website data, you needed to work with your Google Analytics property for tracking website data.

If we needed to view traffic in an app, we needed to leverage Google Analytics for Firebase to access the data. Now, all data across your website and app are gathered in one account. Setting up an app data stream through the Firebase SDK is crucial for effective data collection.

The new GA4 combines web and mobile app traffic usage data into one property in one interface.

This is possible with a new architecture that lets us install cross-device tracking and unify data across devices. Also, this includes being able to track a user across devices.

With the help of GA4 and cross-device tracking, marketers can now holistically view the customer journey across devices.

Deeper Google Ads integration

Google Analytics 4 has deeper integration with Google Ads. You can use data from GA4 to build custom audiences that are more relevant to your customers and target them with paid or organic campaigns. Setting the reporting time zone ensures that the data collected aligns with the business's geographical location and reporting preferences, which is crucial for consistent data analysis and decision-making.

Besides, GA4 will report on actions from YouTube-engaged views that occur in-app and on the web.

According to Google: 

With new integrations across Google’s marketing products, it’s easy to use what you learn to improve your marketing ROI.

A deeper integration with Google Ads, for example, lets you create audiences that can reach your customers with more relevant, helpful experiences wherever they choose for user engagement with your business.

Marketers now can have a more global view of their results with the ability to see conversions from Google and non-Google paid channels, YouTube video views, Google search, social media, and email.

AI-powered Predictions and Insights

Google is a leader in machine learning, and it’s no surprise that advanced machine learning, as the primary form of data measurement, has been applied in Google Analytics 4 to detect trends in data and alert users about them.

GA4 can predict user actions and behavior, making planning your next step much easier by making available data that lets you know what to focus on. Knowing where to invest your time and resources is useful and necessary to get the best return.

GA4 uses machine learning to help digital marketers through two features: predictive metrics and automated insights.

Google Analytics 4 supports three predictive metrics: purchase probability, revenue prediction, and churn probability.

These metrics allow you to use all data you collect to forecast your customers’ future actions.

Using AI, Google Analytics 4 can give marketers and users automated insights about their visitors, customers, and customer journeys.

Automated insights are automatically generated and accessible by default in the GA4 reporting view. With their help, GA4 can automatically alert marketers to data trends.

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Free BigQuery Integration

One of the most exciting features in GA4 is the ability to access and export raw data from GA to Google BigQuery (BigQuery linking).

Earlier, BigQuery integration was available only for Google Analytics 360 (the enterprise version of Google Analytics), but in GA4, it’s available to everyone at no additional cost. 

You only pay for your actual data storage and data querying when you exceed the Google Cloud free tier limits, and exporting data is free.

Sampling was always a problem in Universal Analytics, especially when working with huge datasets. With BigQuery integration, you can do your data analysis on entirely raw, unsampled data. As a result, your analysis will be more accurate and powerful than ever.

Here are more advantages of BigQuery integration:

• Connect GA4 data with third-party APIs
• Export all custom event parameters and dimensions
• Connect data from BigQuery with data visualization tools (Data Studio, Power BI, Tableau, or Qlik)
• Correct data errors on past data
• Use cloud infrastructure  
• Build your own custom Channel Grouping

With this native BigQuery connection without an enterprise plan, Google unlocks many promising possibilities for analytics use cases. 

Now, marketers will have all doors open to work without any limits, having unsampled data at all times and being able to use cloud infrastructure with all the powerful tools provided.

Google Signals

Google Signals is an advertising reporting feature that allows marketers to collect cross-device data on individuals who are signed into a Google account for which they have turned on ad personalization.

Google Signals launched in 2018, but this integration between Google Signals and Google Analytics 4 is a huge update — now, this functionality can be used in all reports, while previously it was applied only to a few pre-built reports.

Data from Google Signals is aggregated and GDPR-compliant, as there is no personally identifiable information. 

Here’s what you can gain by activating Google Signals for your property:

• Gather information on your customers’ age, gender, and interests
• Create lists of users to be remarketed to on the Google network
• Get a more integral view of your audience’s behavior across devices

Event-Based Model

Universal Analytics relies on different hit types such as pageview, event, social interaction, and e-commerce.

In GA4, everything is now an event. An events-based model processes each user interaction as an autonomous event across all web and app visits. Creating and managing a web data stream is crucial for tracking these interactions effectively, as it enables features like enhanced measurement for automatic event tracking.

Event building is one of the most significant Google Analytics 4 features.

There are three categories of events that you can create, track, and receive reports on:

• Automatically Collected Events (received from the global site tag; no additional configuration needed)
• Recommended Events (events recommended by Google; must be implemented manually)
• Enhanced Measurement Events (automatically tracked by Enhanced Measurement in GA4)
• Custom Events (events that you name and implement yourself)

Historically, Universal Analytics grouped all data into sessions, and these sessions were the foundation of the whole reporting system.

With GA4, you can still see session data, but GA4 groups all collected data as events.

An event-based data model offers flexibility in collecting data from both web and app platforms. It also supplements a completely new set of reports based on this new data model.

It might not sound like much, but the event-based model is fundamental. It makes a huge difference and a big problem for old reporting based on session-model data.

What does this change mean for Google Analytics users?

Moving to GA4, we’ll all deal with a completely new data structure, session logic, and reporting system. Obviously, all future GA4 users will face the situation in which all reports built on the Universal Analytics session-based data model simply won’t work in GA4 and analysts will be forced to rewrite SQL queries and rebuild all reports. But you are not alone in this problem, and OWOX BI can make your migration to GA4 smooth and trouble-free.

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Challenges of Google Analytics 4 

There are a few drawbacks of Google Analytics 4:

• code is the primary tracing method on your website
• you use Google Tags Manager as your primary tracking method and have many tags in the container (especially if tags are bound to auto events)
• you have a large website with many subdomains, each of which you track separately
• you don’t have a system of metrics — unified names and values ​— for events and their parameters as well as a unified approach to the hierarchy of events (In this case, it isn’t clear what events are more important to add to the GA interface first and what it’s better to postpone.)
• you have a website and applications without a common event hierarchy
• your team hasn’t yet worked with raw data in BigQuery and isn’t familiar with the principles of Firebase Analytics / App + Web and with the upload scheme

If these statements apply to you, we recommend first building general data collection logic and only then implementing Google Analytics 4. Otherwise, you can quickly find yourself without free slots for user parameters.

If you don’t have a built-in data collection scheme, you can collect useless events in BigQuery and face export restrictions in addition to paying to store garbage data that won’t be useful to anyone (for example, data on scrolling events and banner views).

In our opinion, the main drawback of Google Analytics 4 is the scheme for exporting data to Google BigQuery, in which the key parameters of events and users are stored in nested fields. This means that to obtain the necessary information from Google Analytics 4 tables, you’ll need to process more data compared with OWOX BI data streaming.

How to Move to Google Analytics 4

Google and OWOX analysts so far recommend using both versions of Google Analytics resources. 

For this, you’ll need to:

1. create and configure a new Google Analytics 4 resource
2. add a tracking code manually or via GTM (We recommend using Tag Manager because it’s faster and more convenient.)
3. Consider what events and settings you want to collect into the new resource type.
4. Use both resource types at the same time to compare how data is collected
5. Please note: You can add only one Firebase project to a single Google Analytics 4 resource
6. However, you can configure multiple data streams from different applications into a single Google Analytics 4 resource

You need to add a web stream in Google Analytics 4 to track website events like video plays and link clicks. This involves configuring a data source and linking GA4 with other Google products to enhance your marketing strategies.

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How to get Started with GA4 with the Help of OWOX BI

If you work with Google Analytics professionally, you have to deal with reports, data integrations and exporting, and custom tracking. It’s not so simple to just switch to a new system at once. 

As we mentioned before, we recommend you start tracking your GA4 and Universal Analytics properties in parallel starting now. Don’t wait until GA4 is well accepted in the market and its features have been studied and explained more thoroughly by visionary businesses and competitors. 

But if you think you can just start parallel tracking now and switch quickly and easily to GA4 when the time comes, that’s not realistic.

Google Analytics 4 is an entirely new analytics tool with a new data model. The UI has changed. Tracking points and metrics have changed. The data schema has changed. Reporting configurations have changed. 

The upgrade path isn’t so easy and simple as clicking a magic button and having everything work perfectly straight out of the box. There is a lot that goes into a bug-free migration to the new platform.

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There is only a manual way to import ad cost data into Google Analytics 4. You can automate this process and save valuable time using the solution from OWOX BI.

Important! If you plan to import advertising costs to Google Analytics 4, then you need to add the required parameter utm_id (campaign identifier) to the links of your advertisement campaigns.

Key Takeaways

The world still does not know a lot about GA4, its full functionality, all its new capabilities, and its future evolution.

But we know for sure that GA4 is our future and that we shouldn’t postpone the transition but start down the migration path as soon as possible.

With constant changes in the digital world, all marketing specialists should be able to build reports on their own, improve decision-making, analyze all collected data in different slices, and get valuable insights.

GA4 is the analytics upgrade we all needed. It helps clients understand how users interact in their apps and on their websites in a unified way, it respects privacy and is built to address the needs of a cookieless future, it addresses modern-day marketing needs, and it provides marketers with more flexibility.

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