Top 5 questions about migrating from Google Universal Analytics to Google Analytics 4
We're following up questions from a recent webinar around migrating to Google Analytics 4.
We're following up questions from a recent webinar around migrating to Google Analytics 4.
In anticipation of the pending end-of-life for Google Universal Analytics (UA) on July 1, 2023, we recently hosted a webinar on how to navigate that transition. Whether you’re planning to migrate to Google Analytics 4 (GA4) or a different analytics platform, it’s good to know about the upcoming changes and how event-based data collection from a customer data platform (CDP) makes for a much easier transition.
If you missed the session, never fear! You can still register here to grab a copy of the recording hosted by our experts, Nik Friedman TeBockhorst (VP of Solutions at McGaw.io) and Kimberley Jones (Growth Product Manager @ Twilio Segment).
We answered the high-level, burning questions about the impending transition during the webinar, but of course there were others that we couldn't get to live. We deeply appreciate the great response from everyone who joined, and recognize that with any change comes uncertainty, so we’ve gathered the next most popular group of questions here:
1. If we don’t manually migrate from Google Universal Analytics to Google Analytics 4, will Google track and switch us automatically?
No, Google will not automatically track and switch your existing Universal Analytics (UA) implementation to Google Analytics 4 (GA4) without your explicit action. GA4 requires a separate tracking implementation and data configuration compared to UA.
While Google encourages users to transition from UA to GA4, it does not automatically migrate your data or tracking settings. It's important to note that GA4 operates on a different data model and provides additional features compared to UA. Therefore, it requires a deliberate effort to implement and configure GA4.
2. What differences do we expect to see between Segment’s GA4 Web vs. GA4 Device mode integrations?
The differences are as follows:
GA4 Cloud:
Offers advanced analytics capabilities beyond GA4 Web such as data modeling, machine learning, and custom analysis, which enable deeper strategic insights.
GA4 Cloud has the scalability to handle large volumes of data. You can analyze data from multiple platforms, as opposed to Web which installs just one website tracking tag.
GA4 Web:
Tracking features and requests specifically designed for web analytics.
Extensive, specific user data can be sent, such as demographics and location.
Combined Web + Cloud:
Leverage the strengths of both modes, benefit from cross-platform insights, and access the complete analytics capabilities available in GA4.
3. What are the best ways to minimize discrepancies in reporting between UA and GA4?
There are two major things to look out for:
Data model differences: The data models between UA and GA4 differ; UA uses a session-based model, whereas GA4 uses an event-based model. This means that certain metrics and dimensions may be calculated differently in each version. Use Google’s documentation to familiarize yourself with the nuances of each data model to anticipate any discrepancies that may arise.
Tagging consistency: Ensure consistent and accurate tagging across your website or app for both UA and GA4. Use a tag management system like Google Tag Manager to ensure that the same events and parameters are being sent to both versions. Consistent tagging helps align the data collected in UA and GA4, reducing discrepancies.
4. Do all tags need to be reset in GA4? In short, it varies:
Tagging approach: UA uses a pageview-based tracking approach, where each pageview triggers a tag. In GA4, the focus is on sending events and parameters to track user interactions. You will need to update your tagging approach to align with the event-based model in GA4. Instead of firing tags on pageviews, you'll define events and fire them based on specific user interactions or actions.
Tag configuration: Review your existing UA tags and consider how they should be mapped to GA4 events and parameters. While some tags may require adjustment or customization, others may have similar counterparts in GA4. For example, if you are using event-based tags in UA, you can typically map them 1:1 to corresponding events in GA4.
Enhanced tracking capabilities: GA4 offers enhanced tracking capabilities compared to UA. Take advantage of these capabilities to collect more granular data by implementing additional event tracking for user interactions that couldn’t previously be tracked in UA. This may require creating new tags in GA4 to capture the desired events and parameters.
Custom dimensions and metrics: In GA4, the concept of custom dimensions and metrics still exists, but they are referred to as custom parameters. Evaluate the custom dimensions and metrics you have set up in UA and determine how they should be migrated or recreated as custom parameters in GA4. Update your tags to include the appropriate custom parameter mappings.
Ecommerce tracking: If you have ecommerce tracking implemented in UA, you will need to adjust your tags in GA4 to capture and send the necessary e-commerce events and parameters. GA4 provides enhanced ecommerce tracking capabilities, so you may need to revise your tagging implementation accordingly.
Container migration: If you are using Google Tag Manager (GTM) for your tagging implementation, you can create a new container for GA4 and maintain your existing container for UA. This allows you to gradually transition and test your GA4 implementation without affecting tracking in UA.
5. What are the main benefits of feeding data into Segment first, before it is then passed into GA4?
Fantastic question! There are tons of great reasons to do so:
Data Centralization: Segment acts as a centralized data hub, allowing you to collect and manage data from various sources and channels. By sending data to Segment first, you can consolidate data from your website, mobile app, backend systems, and other sources into a single platform. This centralization simplifies data management and ensures consistency across your analytics and marketing tools.
Data transformation and enrichment: Segment offers powerful data transformation capabilities, allowing you to clean, enrich, and normalize your data before sending it to GA4. You can use Segment's features to perform tasks like data mapping, event enrichment, identity stitching, and data validation. These transformations help ensure the accuracy, quality, and consistency of your data, leading to more reliable insights and analytics in GA4.
Flexible data routing: With Segment, you can easily route data to multiple destinations, including GA4, without modifying your code. This flexibility allows you to send the same data to other analytics platforms, marketing automation tools, data warehouses, or customer data platforms (CDPs). By utilizing Segment's data routing capabilities, you can integrate GA4 with other tools and platforms in your tech stack, enabling a comprehensive data ecosystem.
Simplified implementation and maintenance: Implementing and managing tracking code across different platforms can be time-consuming and error-prone. By using Segment as an intermediary, you can streamline the implementation process. Once you've integrated Segment's SDKs or tracking code into your website or app, you can easily configure and manage data destinations, including GA4, through the Segment dashboard. This simplifies the implementation and reduces the maintenance effort required for managing tracking codes directly within each platform.
Real-time data activation: Segment allows you to activate and leverage your data in real-time. You can create custom audience segments, apply filters, and trigger real-time actions based on specific events or user behaviors. Segment's real-time capabilities let you leverage the data collected from various sources and immediately activate it within GA4 or other connected tools for personalization, marketing automation, or customer engagement purposes.
Data privacy and governance: Segment prioritizes data privacy and provides built-in features for managing data consent and compliance. By sending data through Segment, you can ensure that your data collection and handling align with privacy regulations like GDPR or CCPA. Segment's privacy features, such as data suppression and consent management, help you maintain data governance and adhere to regulatory requirements when passing data into GA4.
Have further questions about migrating from Google Universal Analytics?
Request a product demo here and one of our experts will be happy to help you walk you through how a CDP can make the transition easier.
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