Four questions about stopping Google Analytics

Amplitude returns to key questions for professionals regarding the announced end of Google Universal Analytics and the migration to Google Analytics 4.

Back in March, Google revolutionized the world of the web by announcing the end of Google Universal Analytics as of July 2023, encouraging its users to switch over to Google Analytics 4. However, with more than 70% market share, Universal Analytics, the world’s most popular, uses free web analytics and an advertising platform. Its removal causes an earthquake and raises many questions among professionals. What are the features of this new version? What can bring more or less to marketers? How do you view immigration? An overview of the challenges of this adoption.

Why is Google switching to Google Analytics 4?

The analytics industry has undergone many changes in recent years, marked in particular by the phenomenon of convergence of the web environment and the application domain. In previous decades, companies relied on separate tools for marketing analytics – often referred to as web analytics, experience analytics, and product analytics. With the rise of single-page web applications (SPAs) and cross-platform journeys, the traditional web analytics model, which relies primarily on tracking sessions and pageviews, is no longer suited to business needs. While these metrics are still useful, most digital analytics vendors have gradually moved to an event-based data model.

Firebase, the web and mobile app development platform, was acquired by Google in 2014, in order to offer Universal Analytics user analytics capabilities based on event data through the Apps + Web site. For marketers and developers, the move to GA4 is not a complete surprise, but it is a logical continuation of Apps + Web, indicating the evolution of digital analysis towards user logic focused on customer behavior.

GA4, in response to data privacy issues?

Users are demanding more and more transparency and control over their personal data, in particular in its use for advertising personalization purposes. However, Google Analytics has often been singled out for its non-compliance with personal data protection rules in particular the General Data Protection Regulation (GDPR). GA4 solves the problem by anonymizing IP addresses and limiting data retention to a maximum of 14 months. Thus, it is no longer possible to establish a link between the data collected and the identity of the users, provided that the data sharing option is deactivated in the settings. However, after the official notification to several organizations by the CNIL last February, due to the transfer of data to the United States – which is prohibited by the RGPD – there are still legitimate concerns about the use of certain specific functions in Google Analytics.

This is particularly the case for Google signals, a functionality that Google offers for analytics, in order to identify anonymous visitors and enrich data. To do this, Google Signals takes advantage of other Google products (Chrome and Gmail, for example) with ad personalization. Thus, the solution makes use of the Google Ad Network to perform cross-device user tracking, add demographic information such as age, gender, and advertising points of interest and share it with Google Analytics anonymously. Now, administrators can disable signals in Google Analytics, but most organizations that use the platform have it enabled, and very few Google users know how to disable ad personalization in their accounts. Although the use of signals is currently permitted in the General Data Protection Regulation (GDPR), if all consent requirements are met, a scenario in which the EU forces Google to remove this functionality or make it “common” seems more conceivable. If necessary, Google Analytics will lose an added value, especially in terms of data enrichment and thus user knowledge.

Should we say goodbye to our historical data?

Although Google Analytics remains available until July 2023, companies should plan their strategy for migrating to GA4 now. An approach that can be complex, insofar as GA4 relies on a completely different data structure than that of Google Analytics. So migration can take as much time and resources as moving to a completely new analytics solution. Moreover, the level of difficulty depends on the use cases, some of which include specific steps, such as e-commerce tracking, and still have some compatibility issues. For companies with advanced use of Google Analytics, the change logically involves more stakeholders and requires a structured plan. In particular, this includes a review of existing reports and an assessment of the needs of each team, which will make it possible to select the most appropriate technological solutions and establish an accurate budget and schedule. Like any major technical change, this deadline also provides an opportunity to evaluate its digital analysis strategy in order to determine the optimal configuration to enhance competitiveness and growth.

But one of the main concerns of users is the risk of losing historical data. They will be able to continue to collect and use new data in Google Universal Analytics for less than a year, and retain it for six months after discontinuing the solution. Thus, many organizations fear that they will not be able to use their historical data anymore. But above all, they should ask themselves what their true usefulness is and to what extent their work depends on it. If there is a real fascination with historical data, in fact, few companies really use it. Those that are this case already have internal solutions to store them or have already created external means to store them. However, it is necessary to configure the main properties in GA4 as soon as possible in order to obtain sufficient data accumulation and reduce the loss when failover.

What about data quality and governance?

Most existing Google Analytics users run its implementation from Google Sheets that lists their data classification. But in a context where event-based analytics becomes the gold standard, this can create data management issues. Businesses today need complete confidence in the data they use and activate it for downstream applications. Events must be planned, prepared, validated, organised, transformed, and monitored over time to generate high-quality information that leads to smarter, faster decisions.

Event-driven analytics platforms require significant investments in data management, but are more robust and efficient when it comes to tracking and analyzing customer behavior. Without great governance tools, low adoption rates due to unreliable data and hardware return efforts can quickly become high. This is one of the main reasons why analytics strategies fail. Thus, GA4 and GA360 users are eager to take advantage of features such as integrated follow-up planning, monitoring capability for event validation, a “developer first” experience with for example Jira and SDK integration and stronger data transformation capabilities.

Leave a Comment