Google Analytics 4 represents the present and future of digital analytics.
It is an intelligent solution that leverages machine learning to discover and analyze the customer journey across multiple platforms and devices.
In addition, it allows optimized integrations with Google advertising platforms to improve campaign performance and increase the ROI related to the developed marketing strategy.
As we have already said before, Google Analytics has been facing this change for some time, specifically since October 2020, since the new analytics platform is active. With this update, Google Analytics, as well as the entire Google ecosystem, favors greater automation in reports and events and places greater importance on machine learning.
Therefore, now that we are close to the mandatory transition to Google Analytics 4, it is essential to hurry up and switch to the new version, especially since starting January 2023 GA4 will no longer allow access to historical data (analytical data) in Google Universal Analytics properties.
Google Analytics 4 is not a simple feature update. This is a completely different approach to analysis, so much so that there will no longer be a standard configuration of the service (an immediate and easy-to-use basic dashboard), but rather it will be necessary to create a custom configuration tailored to your needs. needs. This means that each will have a different view depending on the metrics you want to use. Most likely, less experienced users will find it difficult to switch to Google Analytics 4 and get used to this new feature.
16 Main Differences Between Google Universal Analytics and Google Analytics 4
We can describe the evolution of Google Analytics by dividing its history into 4 different phases:
- Urchin (the first name of the platform in 1995 before Google bought it)
- Classic analysis
- Universal Analysis
- google analytics 4
However, the new GA4 is not a kind of “new Google Analytics”, it has nothing to do with Universal Analytics because some logic of use and management of the analytical data that are registered change completely.
Specifically, these are 16 of the main changes to highlight:
- From “session-focused” to “event-focused”
- Google Analytics 4 automatically excludes known bots
- There is the possibility of using up to 500 different event types
- Each event can have around 25 parameters.
- User properties can be created (25 per property)
- There are flows to connect multiple data sources.
- A data filter can be configured to exclude traffic sent in debug mode
- Bounce rate analysis is no more (a bounce rate occurs when the user leaves the site a few seconds after viewing a single web page)
- No sampling (information about sampling)
- The dynamics of permanence and commitment time change
- There are automatic events (file downloads, scrolling, youtube videos, external links)
- Conversion management is simplified (goals no longer exist)
- There is a direct connection with BigQuery and Google Ads
- There are predictive custom audiences
- There is a new measurement model
- User-centric management: there are (in order of priority): User-ID, Google Signal and Client-ID
Why you need to switch to Google Analytics 4
In a survey conducted by Forrester Consulting (a research and analytics agency), many of the marketers interviewed said that improving the use of analytics is a top priority and that current solutions make it difficult to have a complete view of the customer and obtain complete information of your information.
Google Analytics 4 has machine learning and event tracking that can provide actionable insights and offers a comprehensive understanding of customers across devices and platforms. It is focused on privacy and is designed to adapt to a future with or without cookies or identifiers.
Additionally, Google Analytics 4 uses a tiered approach to event and metrics tracking, including automatically collected, recommended, and personalized events and metrics to improve marketing decisions and drive higher ROI.
By applying Google's advanced machine learning models, the new Analytics automatically alerts you to significant trends in the data you collect, such as products experiencing increasing demand due to new customer needs.
It also helps anticipate future actions that customers may take. For example, calculate the probability that a page will be deleted. This happens thanks to new predictive metrics, such as the potential revenue that could be obtained from a particular group of customers. This allows you to create audiences to reach higher-value customers and perform analytics to better understand why some customers are likely to be more likely to buy than others, so you can take steps to improve your results.
How the user journey is analyzed in Google Analytics 4
Analytics 4 can measure interactions between apps and the web together and provide a more complete understanding of user interaction and their journey to becoming customers. For example, viewing conversions from YouTube video views alongside conversions from Google Ads and organic channels like Google Search, social media, and email is key to understanding the combined impact of all your marketing efforts.
Analytics 4 provides customer-centric measurements, rather than fragmented measurements by device or platform. Use multiple identity spaces, including seller-provided user IDs and Google's unique signals from users who have enabled ad personalization.
As we mentioned earlier, GA4 offers a better understanding of customers throughout the entire lifecycle, from acquisition to conversion and retention. This is critical when people's needs change rapidly (as happened in early 2020 during the start of the health emergency) and we are forced to make decisions in real time to acquire new customers or maintain current ones.
Through GA4 you can see which channels are attracting new customers in the “user acquisition report,” and through the “engagement and retention” reports you can understand the actions taken by these customers and their eventual retention after conversion.
