If you’re a Google Analytics expert, you’re likely familiar with the ongoing debate of Google Analytics UA vs GA4.
To be clear, UA means Universal Analytics while GA4 means Google Analytics 4.
Google already announced that Universal Analytics would be deprecated starting on July 1, 2023.
Hence, it is imperative to migrate to GA4 as soon as possible.
While both versions offer valuable insights into user behavior, they differ significantly in terms of data collection methods, user identity tracking, reporting capabilities, and machine learning features.
In this article, I’ll provide an in-depth analysis of UA and GA4 to help you understand the key differences between these two versions of Google Analytics.
Also, I’ll explain how to properly set up GA4 in your Google Analytics.
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How To Migrate To GA4 From UA Property
If you want to migrate an existing Universal Analytics account to Google Analytics 4, follow the steps below:
Here’s a step-by-step guide to help you migrate from UA to GA4:
Create a new GA4 property
First, you’ll need to create a new GA4 property within your Google Analytics account. You can do this by navigating to the “Admin” section of your account and clicking on “Create Property.”
Enable data sharing
To ensure that your GA4 property can access data from your existing UA property, you’ll need to enable data sharing between the two properties. You can do this by navigating to the “Admin” section of your UA property and clicking on “Property Settings.” From there, click on “GA4 Setup” and follow the prompts to enable data sharing.
Link your UA to your GA4 property
Once you’ve enabled data sharing, you’ll need to link your UA property to your new GA4 property. To do this, navigate to the “Admin” section of your GA4 property and click on “Data Streams.”
From there, click on “Set up a Stream” and select “Web” or “App” depending on the source of your UA data. Follow the prompts to link your UA property to your GA4 property.
Set up data collection
With your UA property linked to your GA4 property, you’ll need to set up data collection for your GA4 property. This involves creating data streams and installing the GA4 tracking code on your website or app. You can find detailed instructions for setting up data collection in the GA4 documentation.
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Further Customization of Your GA4
- Set up custom events and parameters: GA4 uses a new event-driven model that allows you to track custom events and parameters. You’ll need to set up custom events and parameters to track the specific actions and behaviors you want to measure. You can do this by navigating to the “Events” section of your GA4 property and clicking on “Create Event.”
- Compare data between UA and GA4: Once you’ve set up data collection and custom events in GA4, you’ll need to compare data between UA and GA4 to identify any discrepancies and make sure your data is accurate.
- Update reporting and analysis: Finally, you’ll need to update your reporting and analysis to reflect the new data collection and tracking methods used in GA4. This may involve using new reports and dashboards, creating custom reports, or updating existing reports to reflect the new data.
It’s important to note that migrating from UA to GA4 requires careful planning and execution to ensure a smooth transition. Make sure to consult Google’s migration guides and resources to ensure a successful migration.
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How To Set Up A New GA4 Property
Follow these 3 steps to set up a new GA4 property.
1. Create a new GA4 property
To get started with GA4, you need to create a new property in your Google Analytics account. You can do this by navigating to the “Admin” section of your account and clicking on “Create Property.”
2. Set up data streams
Once you’ve created a new GA4 property, you’ll need to set up data streams to start collecting data from your website or app. A data stream is a source of data that you want to track, such as a website or mobile app. You can set up data streams by navigating to the “Data Streams” section of your GA4 property and clicking on “Add Data Stream.”
3. Install the GA4 tracking code
To start tracking data in your GA4 property, you’ll need to install the GA4 tracking code on your website or app. You can find the tracking code by navigating to the “Data Streams” section of your GA4 property and clicking on “Tagging Instructions.” Follow the instructions provided to install the tracking code on your website or app.
Google Analytics UA vs GA4: The Difference
GA4 also offers more advanced features and capabilities, such as cross-device tracking and machine learning capabilities for predictive analytics. However, because GA4 is a newer version, it may have some limitations and challenges in terms of compatibility with existing data and reporting tools.
In this article, I’ll explain the major differences between Google Analytics UA vs GA4 in the following categories:
- Data Collection
- User Identity
- Machine Learning
Let’s go into detail.
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As a Google Analytics expert, you know that data collection is at the heart of effective website and app tracking. The data you collect helps you understand your users, identify trends and make informed decisions about your marketing and business strategies.
In this section, I’ll explain the data collection methods used in Universal Analytics (UA) vs Google Analytics 4 (GA4), and how they differ from each other.
A. Explanation of UA’s data collection methods
- Tracking of user behavior on websites: UA also tracks user behavior on your website or app by collecting data on pageviews, events, and other interactions. This data is then used to create reports and insights that help you understand how users interact with your site and what actions they take.
B. Explanation of GA4’s data collection methods
- Event-driven model: GA4 uses an event-driven model to collect data about user behavior on your website or app. This means that instead of tracking pageviews and other interactions, GA4 tracks events. Events are specific user actions that you want to track, such as clicks, form submissions, or video views. This event-driven model allows you to track more granular user behavior and get more detailed insights into how users interact with your site.
- Collection of data from multiple sources: GA4 also collects data from multiple sources, including your website, mobile apps, and other online and offline sources. This data is then combined to create a more complete picture of your users and their behaviour. GA4 also uses machine learning to analyze this data and identify trends and patterns that can be used to optimize your marketing and business strategies.
- Offline data integration: Finally, GA4 allows you to integrate offline data into your analytics. This means that you can combine data from your online and offline sources to get a more complete understanding of your customers and their behaviour. For example, you could combine online data about user behaviour on your website with offline data about purchases made in your physical store to identify trends and patterns that can help you improve your marketing and business strategies.
As a Google Analytics expert, you understand the importance of tracking user identity in order to gain a better understanding of your audience and their behavior. Here, you’ll understand how user identity tracking differs in Universal Analytics (UA) vs Google Analytics 4 (GA4).
A. Explanation of UA’s user identity tracking
- Use of client: ID UA tracks user identity using a client ID, which is a unique identifier that is stored in a cookie on the user’s device. This client ID is used to associate all activity on the site with a single user.
- Limitations of client ID tracking: Client ID tracking has limitations. For example, it cannot track users who delete their cookies or use multiple devices. This can lead to inaccurate data and a fragmented view of user behavior.
B. Explanation of GA4’s user identity tracking
- Use of user ID: GA4, on the other hand, uses a user ID to track user identity. A user ID is a unique identifier that is associated with a user’s Google account or other login information. This allows GA4 to track users across multiple devices and sessions, even if they delete their cookies.
- Cross-device tracking capabilities: GA4 also has cross-device tracking capabilities, which means that it can track users as they move between devices. This provides a more accurate and complete view of user behavior, which can help you make better data-driven decisions.
A clear and user-friendly reporting interface is crucial for effectively analyzing your data. In this section, you’ll understand how Universal Analytics (UA) vs Google Analytics 4 (GA4) differ in their reporting interfaces.
A. Explanation of UA’s reporting interface
- Complex and difficult to navigate: UA’s reporting interface is known for being complex and difficult to navigate. It can be challenging to find the specific data you’re looking for, and creating custom reports can be a time-consuming process.
- Customizable reports: UA does have the advantage of allowing you to create custom reports. This means that you can choose the specific metrics and dimensions you want to analyze and create reports that are tailored to your business needs.
B. Explanation of GA4’s reporting interface
- More streamlined and user-friendly: GA4’s reporting interface is designed to be more streamlined and user-friendly than UA’s. The interface is organized in a way that makes it easy to find the specific data you’re looking for. You can also easily switch between different types of reports, such as audience, acquisition, behavior, and conversions.
- Pre-built reports and insights: Additionally, GA4 has pre-built reports and insights that provide valuable information about your users and their behavior. These reports can be accessed with just a few clicks, and they provide valuable insights that can help you make data-driven decisions about your business.
You may have heard about machine learning and its potential to provide powerful insights into user behavior. This aspect of the article explains the machine learning capabilities of Google Analytics 4 (GA4) and how they differ from Universal Analytics (UA).
Explanation of GA4’s machine learning capabilities
There are two major aspects of GA4’s Machine learning capabilities as highlighted below:
Granular insights into user behavior
GA4’s machine learning capabilities enable it to provide granular insights into user behavior. For example, it can identify patterns in user behavior, such as which pages are most likely to lead to a conversion, and provide recommendations for improving the user experience.
GA4’s machine learning capabilities also include predictive analytics, which can help you anticipate user behavior and take action before it happens. For example, it can predict which users are most likely to churn and recommend personalized interventions to prevent it.
Comparison of Google Analytics UA vs GA4 in terms of machine learning
While UA also has some machine learning capabilities, they are not as advanced as GA4’s. UA primarily relies on predefined reports and segmentation, whereas GA4 uses machine learning to provide more granular insights and predictive analytics.
In addition, GA4’s machine learning capabilities are more integrated into the reporting interface, making it easier to access and utilize the insights provided by machine learning algorithms.
Overall, GA4’s machine learning capabilities provide a more sophisticated and powerful way to analyze user behavior and make data-driven decisions. As a Google Analytics expert, it’s important to understand these capabilities and incorporate them into your analytics strategy for better insights and outcomes.
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limitations and challenges of UA
Here are some of the limitations and challenges of UA:
Limited cross-device tracking
UA primarily relies on cookies to track user behavior, which can limit the ability to track users across multiple devices. This can result in incomplete and inaccurate data, particularly for users who frequently switch devices.
UA can be challenging to implement, particularly for organizations with complex websites or unique tracking requirements. This can result in incomplete or inaccurate data, or in some cases, data that is not collected at all.
In cases where there is a large amount of data, UA may sample data rather than collect it all. This can lead to inaccuracies in reporting and a lack of insight into certain segments of the user population.
Limited real-time reporting
UA’s reporting interface has limited real-time reporting capabilities, which can make it difficult to identify and respond to issues in real-time.
Limited machine learning capabilities
While UA has some machine learning capabilities, they are not as advanced as GA4’s. This can limit the ability to gain granular insights into user behavior and make data-driven decisions.
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Limitations and challenges of UA
While Google Analytics 4 (GA4) offers advanced tracking and reporting capabilities, as well as machine learning-driven insights, it also has its limitations and challenges. Here are some of them:
Limited third-party integrations
GA4 has limited third-party integrations compared to UA. This can make it difficult to integrate with other tools and platforms used by your organization, potentially resulting in incomplete data.
Limited historical data
GA4 does not have access to historical data from UA, which can make it challenging to track long-term trends and compare data over time.
The new event-driven model used in GA4 requires a new way of thinking about data collection and analysis. This can make it challenging for organizations to adapt to the new platform and take full advantage of its capabilities.
GA4’s reporting interface is more streamlined and user-friendly compared to UA, but it also has fewer customization options. This can limit the ability to create custom reports and dashboards tailored to specific business needs.
Cross-domain tracking limitations
GA4 has limitations in cross-domain tracking, which can make it challenging to track user behavior across different domains or subdomains of your website.
As an experienced Google Analytics user, I highly recommend that you start transitioning to Google Analytics 4 (GA4) as soon as possible if you have not done so.
While Universal Analytics (UA) has served us well in the past, it has its clear limitations and may not keep up with the ever-changing digital landscape.
GA4 offers much more advanced tracking capabilities, machine learning-driven insights, and a streamlined reporting interface that can help you make better business decisions. It also addresses some of the limitations of UA, such as cross-device tracking and data privacy, which are crucial in today’s digital world.
So, my one piece of advice for you is to start planning your transition to GA4. It’s an investment that will pay off in the long run, giving you a competitive edge and helping you stay ahead in the digital world.