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GA4 Marketing Masterclass

First, a word from Google Bard

“My top tip for helping you understand why as a marketer, you should be interested in GA4 is to think about the future of marketing. GA4 is designed to be more future-proof than Universal Analytics, and it offers a number of features that can help you improve your marketing campaigns.

Here are some of the reasons why you should be interested in GA4 as a marketer:

GA4 is more privacy-focused. GA4 is designed to be more privacy-focused than Universal Analytics, and it uses machine learning to fill in the gaps in data that is not available due to privacy restrictions. This means that you can still get valuable insights from your data, even if you are unable to collect all of the data that you would like.

GA4 is more cross-platform. GA4 is more cross-platform than Universal Analytics, and it can collect data from a variety of sources, including websites, apps, and even offline transactions. This means that you can get a more complete picture of your customers’ behavior, regardless of how they interact with your brand.

GA4 is more predictive. GA4 is more predictive than Universal Analytics, and it can use machine learning to predict future behavior. This means that you can use GA4 to identify trends and opportunities that you may not have been able to see before.

Overall, GA4 is a powerful tool that can help you improve your marketing campaigns. If you are interested in the future of marketing, then you should be interested in GA4.

Here are some additional resources that you may find helpful:

Google Analytics 4: What Marketers Need To Know… And Do… Today!:

How Does GA4 Affect Marketing?:

An In-Depth Guide to Google Analytics 4:

Part One – Migrating from Universal Analytics to Google Analytics 4 (GA4)

Step 1: Understand the Differences Between Universal Analytics and GA4

It’s important to understand that GA4 isn’t just an upgrade from Universal Analytics, but a total reimagining of Google Analytics, focused more on user journeys and engagements than page views. We should all familiarise ourselves with the differences, including data modelling, tracking, and reporting, to understand the benefits and the implications of the migration.

Step 2: Create a New GA4 Property

Log into your Google Analytics account.

Click on the ‘Admin’ option in the bottom-left corner.

In the ‘Account’ column, select the account where you want to create the GA4 property.

In the ‘Property’ column, select the Universal Analytics property you want to link to the new GA4 property.

Click ‘GA4 Setup Assistant’.

Click ‘Get Started’ in the ‘I want to create a new GA4 property’ box.

Follow the prompts to create the new property.

Step 3: Implement GA4 Alongside Universal Analytics

In the transition phase, it’s beneficial to run GA4 parallel to the Universal Analytics. This allows you to collect and compare data between both versions and ensure GA4 is working as intended.

Step 4: Install GA4 on Your Website

If you use Google Tag Manager, you can set up your GA4 configuration tag. If not, you’ll need to add the GA4 tracking code to your website, similar to how you added the Universal Analytics tracking code.

Step 5: Configure GA4 to Meet Your Tracking Needs

GA4 offers many customisation options for tracking user behaviour, such as events and conversions. Take time to understand these features and configure them to meet your marketing analysis needs.

Step 6: Test GA4 Tracking

Make sure GA4 is collecting data as expected. Real-time reports can be helpful for this. It’s also a good idea to compare this data with the data collected by Universal Analytics to ensure consistency.

Step 7: Train Your Team

GA4 is quite different from Universal Analytics. Make sure your team understands how to use it effectively. Google’s Skillshop offers free GA4 training.

Step 8: Gradual Migration

Once you’re comfortable with GA4 and are sure it’s set up correctly, you can start to shift your analysis from Universal Analytics to GA4. However, keep using both for a while to ensure nothing is lost in the transition.

Step 9: Fully Transition to GA4

After the parallel run, and once you’re confident that GA4 is accurately tracking and reporting on the metrics that matter to your business, you can make the full transition from Universal Analytics to GA4.

Remember, this process is not an overnight transition, but a gradual migration to ensure data consistency and accuracy. It’s about learning a new system while still maintaining the old one until the new one is fully ready.

Part Two – Differences between Universal Analytics and GA4

Event-Based Tracking

One major difference between Universal Analytics and GA4 is how they track user interactions. Universal Analytics uses session-based tracking, which is primarily focused on website sessions and page views. GA4, on the other hand, employs an event-driven model, which means it tracks a wider variety of user interactions, not just page views.

Data Modeling

Universal Analytics uses a hit-based data model with hierarchy: users>sessions>hits. GA4, in contrast, uses an event-based data model: users>events. GA4 doesn’t distinguish between hit types. Page views, transactions, and social interactions are all logged as events. This simplifies and unifies data collection, but it also means that certain metrics from Universal Analytics, like bounce rate, aren’t directly available in GA4.


GA4 introduces new features in reporting that provide deeper insights into user behaviour over their lifecycle. The ‘Analysis Hub’ in GA4 allows for a more flexible and customisable way to build reports. This is different from Universal Analytics, which has predefined, standard reports.

Machine Learning and AI

GA4 is built with a greater focus on machine learning and AI to provide smarter insights and improve marketing decisions. It offers features such as predictive metrics, which can predict future actions users might take. This is not available in Universal Analytics.

Privacy and Data Control

GA4 was designed with adaptability to a future where cookies might not be widely available or reliable. It is more resilient in the face of changing privacy regulations and provides users with more flexibility to control how their data is collected.

Part Three – Events, Data Modelling and Reporting

Event-Based Tracking

GA4 utilises an event-based data model, which is a notable departure from the traditional session-based model used in Universal Analytics.

In Universal Analytics, data is organised around sessions, which are determined by the time a visitor spends on your website. Sessions begin when a visitor lands on your site and end after 30 minutes of inactivity, or at midnight. Interactions during a session, like page views, transactions, or form submissions, are treated as “hits”.

GA4, on the other hand, treats everything as an event. This includes not only the interactions that would have been hits in Universal Analytics, but also more granular activities like scrolling, video plays, or clicks on specific elements of your website. This shift allows for more nuanced tracking of visitor behaviour. For example, you could track when a visitor clicks on a specific button, how far they scroll down a page, or whether they engage with a video.

Data Modeling

The data models used in Universal Analytics and GA4 also differ significantly.

In Universal Analytics, data is organised in a hierarchy of users > sessions > hits. Visitors are identified by a unique ID (like a cookie), sessions are groups of interactions that take place on your website within a given time frame, and hits are the interactions themselves, like page views or events.

In GA4, the data model is simplified to users > events. There’s no concept of sessions in GA4. Instead, every action taken by a visitor on your website is treated as an individual event. This change can affect how you track and interpret visitor behaviour. For instance, the bounce rate, a commonly used metric in Universal Analytics, is not available in GA4 because it’s based on sessions.


Reporting in GA4 is quite different from Universal Analytics due to the shift from session-based to event-based tracking.

Universal Analytics offers predefined, standard reports based on the data model of users, sessions, and hits. These reports can be customised to some extent, but the structure is relatively fixed.

GA4 introduces the ‘Analysis Hub’, which offers a more flexible and customisable approach to reporting. Rather than starting with a predefined structure, you can build your own reports from scratch, selecting the users and events you want to analyse and choosing how the data should be visualised. This gives you much more control and flexibility in analysing your data.

In addition, GA4 also provides new default reports designed to give insights into visitor behaviour over their entire lifecycle, from acquisition to conversion and retention. These include the ‘User Acquisition’ report, ‘Engagement’ report, ‘Monetisation’ report, and ‘Retention’ report, which are not available in Universal Analytics.

Part Four – What Next

Step 1: Plan for Event-Based Tracking in GA4

Understand the Event-Based Model: Start by getting a clear understanding of what an event is in GA4. Remember, GA4 treats everything as an event – from page views to clicks on specific elements of your site.

Identify Key Events: Identify the key events that matter to your business. These could be product views, add-to-cart actions, purchases, form submissions, etc.

Map Out Event Tracking: Plan how you will track these events in GA4. Consider whether you will use automatically tracked events, recommended events, or custom events. Remember, unlike Universal Analytics, GA4 allows you to track more granular activities.

Test Your Event Tracking: Once you’ve set up your event tracking in GA4, make sure to test it to ensure it’s working as expected.

Step 2: Transition to the GA4 Data Model

Understand the GA4 Data Model: Familiarise yourself with the user-event model in GA4. Understand how it differs from the user-session-hit model in Universal Analytics.

Revisit Your Metrics: Consider how the shift to the GA4 data model might impact your metrics. Some metrics from Universal Analytics, like bounce rate, are not directly available in GA4. However, there are similar metrics available, and you can also create new, custom metrics.

Prepare for Custom Definitions: In GA4, you can create custom definitions for your data, including custom events, parameters, and user properties. Plan how you might utilise these to better meet your analytics needs.

Step 3: Prepare for GA4 Reporting

Explore the Analysis Hub: Get familiar with the Analysis Hub in GA4, and understand how it allows you to create custom, flexible reports.

Identify Key Reports: Determine which reports are most important for your business. GA4 includes new default reports, such as User Acquisition, Engagement, Monetisation, and Retention reports, which can provide valuable insights.

Create Sample Reports: Practice creating a few reports in the Analysis Hub. Start simple, and gradually get more complex as you get more comfortable.

Compare Data with Universal Analytics: Initially, run GA4 parallel to Universal Analytics and compare the data and reports between both. This will help you ensure that GA4 is set up correctly and capturing the data you need.

Train Your Team: Make sure everyone who will be using GA4 is trained on how to create and interpret reports.

Step 4: Further Learning and Development 

Remember, the transition from Universal Analytics to GA4 is not just about setting up the new tool, but also about adapting your approach to data tracking and analysis. Make sure to take the time to understand and plan for these changes. To learn more beyond this introduction, visit

GA4 Top Tip

In the Analysis Hub, explore ’User Acquisition’ report, ‘Engagement’ report, ‘Monetisation’ report, and ‘Retention’ report, and align these with your actual customer journeys, to explore the reality of your website experience and to identify places in the journey that can be improved.

Important Definitions of GA4 Features

Dimensions: These are attributes of your data. For instance, the page on which a visitor lands or the country where a user is located are both dimensions. In GA4, there are four types of dimensions: Event, Item, User, and User Property. Each has a distinct set of parameters. Event and Item dimensions are associated with events, while User and User Property dimensions are tied to users.

Filters: These are rules you apply to data in order to include only a specific subset of it in a view. For example, you might create a filter to exclude internal traffic or to only include traffic from a specific country. In GA4, you can create filters at the property level to limit the data that is included in your reports. You can also use filters when creating reports to isolate specific segments of your data.

Events: Visitor interactions with content that can be tracked independently from a webpage or a screen load. Downloads, link clicks, form submissions, and video plays can all be tracked as Events.

Parameters: Additional bits of information that can be attached to events to provide more context. Parameters might include the value of a transaction or the name of a piece of content.

User: A unique visitor to the website. Visitor are identified across sessions using a unique identifier.

Session: A group of visitor interactions within a given time frame on your website. A single session can contain multiple page views, events, social interactions, and e-commerce transactions.

User Property: Attributes that describe segments of your visitor base, such as language preference or geographic location.

Engagement Time: A metric that shows the total amount of time visitors are actively engaging with your website or app.

Event Scoped User Property: User properties that only apply to future events after being set.

User ID: A feature that allows you to associate engagement data from multiple devices and multiple sessions with unique IDs.

Conversions: The key actions you’re tracking that users complete on your site. Examples might include completing a purchase, signing up for a newsletter, or submitting a contact form.

Funnels: A series of steps you expect users to take towards a conversion. In GA4, funnels are flexible and can be built retroactively.

Paths: The sequence of events that lead users towards conversion. Paths analysis can help you understand the journey of your visitors.

Segments: Groups of users that share common attributes. In GA4, you can create custom segments for more granular analysis.

Audiences: A group of visitors who share similar characteristics, behaviours, or experiences. You can create custom audiences to understand and engage with specific user groups more effectively.

Attribution Model: Rules that determine how credit for conversions is assigned to different visitor interactions. GA4 includes several default models and also allows for custom attribution models.

Cross-platform tracking: With GA4, you can track user behaviours across different platforms (web, Android, iOS), which provides a more comprehensive view of the customer journey.

Analysis Hub: A section of GA4 where you can conduct advanced analysis of your data, such as exploration, path analysis, segment overlap, and funnel analysis.

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