Google Analytics has been the go-to tool for digital marketers and website owners for tracking website performance and user behavior. However, with the rapid changes in the digital landscape, Google has introduced the latest version of its analytics platform, Google Analytics 4(GA4). In this blog, we will take an in-depth look at GA4, its features, and how it differs from the previous version.
TLDR;
GA4 represents a significant shift in how Google Analytics works, with a new event-based data model, enhanced machine learning capabilities, and improved support for cross-platform tracking. GA4 provides amore comprehensive view of user behavior, allowing you to gain deeper insights into how users interact with your website or app. Additionally, GA4 includes arrange of privacy controls and data controls to help you comply with GDPR, CCPA and other data privacy regulations. Setting up GA4 is relatively straightforward and can provide a wealth of valuable insights into your users' behavior.
Google Analytics 4 (GA4) is the latest version of Google's web analytics platform. It was released in October 2020, and it is built on anew platform and architecture that differs from the previous Universal Analytics version. GA4 is designed to provide a more comprehensive view of user behavior across multiple platforms and devices.
One of the biggest changes in GA4 is the introduction of an event-based data model. In GA4, events are the fundamental building blocks of user activity tracking. This means that instead of tracking pageviews and other predefined actions, you can now track any custom event that you define. This event-based data model provides more flexibility and granularity in tracking user behavior, allowing you to gain a deeper understanding of how users interact with your website or app.
Another major change in GA4 is the focus on machine learning and AI-powered insights. GA4 includes a number of new features that leverage machine learning to provide insights and predictions about user behavior. These features include automatic insights, predictive metrics, and advanced analysis tools.
In addition, GA4 has improved support for cross-platform tracking, including tracking user behavior across web, mobile apps, and offline channels. It also includes new privacy controls and data controls to help you comply with GDPR, CCPA, and other data privacy regulations.
Overall, GA4 represents a significant shift in how Google Analytics works, and it offers a range of new features and capabilities that can help you gain deeper insights into your users' behavior and optimize your website or app accordingly.
The event-based data model is the fundamental building block of user activity tracking in GA4. In the previous version of Google Analytics, Universal Analytics, you had to set up tracking for specific actions such as page views, clicks, and form submissions. However, with the event-based data model in GA4, you can track any custom event that you define.
Events can be triggered by a wide range of user actions, such as clicks, video plays, scroll depth, and form submissions. You can define custom events based on your website or app's unique user behavior. This means that you can track user behavior more accurately, and you can gain deeper insights into how users interact with your website or app.
For example, let's say you have an e-commerce website, and you want to track user behavior related to adding products to the cart. In Universal Analytics, you would have to set up tracking for clicks on the "Add to Cart" button on each product page. However, with GA4'sevent-based data model, you can define a custom event for "Add to Cart," and track that event across all product pages.
The event-based data model in GA4 also allows you to track user behavior across multiple devices and platforms. For example, if a user adds a product to their cart on their mobile device, and then completes the purchase on their desktop computer, you can track that entire user journey as a single event.
GA4 includes a range of machine learning-powered features that provide insights and predictions about user behavior. These features include automatic insights, predictive metrics, and advanced analysis tools.
Automatic Insights: GA4 includes a feature called "Automatic Insights," which uses machine learning algorithms to analyze your data and provide insights into user behavior. Automatic insight scan help you identify trends and patterns in user behavior, such as changes in traffic or user engagement. For example, if your website experiences a sudden increase in traffic from a particular location, Automatic Insights can help you identify that trend and provide insights into why it's happening.
Predictive Metrics: GA4 includes a range of predictive metrics, which use machine learning algorithms to predict user behavior. These metrics include predicted revenue, predicted conversion rate, and predicted engagement rate. Predictive metrics can help you identify potential opportunities for optimization and focus your efforts on the areas that are most likely to drive results.
Advanced Analysis Tools: GA4 includes a range of advanced analysis tools that leverage machine learning to provide deeper insights into user behavior. These tools include path analysis, user journey analysis and user lifetime value analysis. These advanced analysis tools can help you gain a deeper understanding of how users interact with your website or app and identify areas where you can optimize your user experience.
One of the key advantages of GA4 is its improved support for cross-platform tracking. GA4 allows you to track user behavior across web, mobile apps and offline channels, providing a more comprehensive view of user behavior.
For example, if a user visits your website on their desktop computer, and then downloads your mobile app and completes a purchase, GA4 can track that entire user journey as a single event. This provides a more accurate view of user behavior and allows you to optimize your user experience across all platforms and devices.
GA4 includes a range of privacy controls and data controls to help you comply with GDPR, CCPA, and other data privacy regulations. These controls include data deletion, user consent controls, and data retention controls.
Data Deletion: GA4 allows you to delete user data if a user requests it, ensuring that you are compliant with data privacy regulations.
User Consent Controls: GA4 allows you to obtain user consent for data collection and use, ensuring that you are compliant with GDPR and other data privacy regulations.
Data Retention Controls: GA4 allows you to set data retention periods for user data, ensuring that you are compliant with GDPR and other data privacy regulations.
The 3 Cs of search intent are Content, Context, and Clarity. These ensure that your content aligns with the user’s query, the context in which it was searched, and provides clear, actionable information.
You can determine keyword search intent by analyzing the keyword itself, examining the SERP results, and understanding the typical user journey for that keyword. Tools like SEMRush and Ahrefs provide intent data to help guide your keyword research.