Reporting Identity and Consent Mode

2023-08-22 | Article | Insights

In the ever-evolving landscape of digital marketing and data privacy, Google Analytics 4 (GA4) continues to provide marketers with advanced tools to track user interactions and gather insights. One of the crucial features within GA4 is the "Reporting Identity" setting, which helps balance the need for accurate tracking with user privacy concerns. Additionally, the implementation of Consent Mode through Google Tag Manager (GTM) offers a way to manage user consent effectively. In this comprehensive guide, we'll dive into the Reporting Identity setting, explore the differences between "Blended" and "Observed," discuss Consent Mode implementation via GTM, and finally, explain how the data generated by Consent Mode is consumed through reports and in BigQuery.

Understanding GA4 Reporting Identity

The Reporting Identity setting in GA4 plays a significant role in the balance between data accuracy and user privacy. It allows you to choose how Google Analytics associates user data with unique identifiers. This setting is crucial in scenarios where there might be limitations due to data protection regulations like GDPR and CCPA.

There are three ways of defining a User in GA4:

  1. User ID: Uses a customer-supplied ID to differentiate between users and unify events in reporting and exploration. Usually provided by the CRM when the User logs in to the digital platform.
  2. Google Signals: Are session data from sites and applications that Google associates with users who are signed in to their Google Accounts and have ads personalisation turned on.
  3. Device ID: Uses the client ID for websites or the app Instance ID for apps. The ID is randomly generated and saved in the cookies for the websites and by the App Firebase x GA4 implementation.

Those are the three ways of generating user identifiers for our digital audiences, but when the user declines the cookies on the website, how can we still collect anonymous data and how these user identifiers are generated if we cannot make use of cookies?

Differences Between "Blended" and "Observed" in Reporting Identity

In the Admin section of GA4 we can find the Reporting Identity setting, where two options are available, Blended and Observed. For both options, the three ways of identifying the user remain the same (User ID, Google Signals and Device ID), but for Blended we can see an additional alternative called modelled data. Modelled Data is the method used to keep tracking users when they decline Analytics identifiers like cookies. Modelled Data tries to fill this data gap by using the data of similar users who do accept cookies from the same property to model the behavior of the users who decline cookies. In order to enable GA4 machine learning to fill the data gap generated by the users who decline cookie usage on the websites, we need to implement a new GA4 feature called Consent Mode. This way even when the user declines the cookie banner, the tracking keeps in place without using cookies to save the Device ID (clientID). Every page generates a new random Device ID, and combining the userAgent, the timestamp and all the anonymous collected events, GA4 machine learning tries to give back the data we lost when implementing the cookie banner.

To make use of this new GA4 feature we need to:

  1. Select the option "Blended" in the Reporting Identity settings
  2. Implement Consent Mode to keep collecting user navigation data via anonymous events

Implementing Consent Mode via Google Tag Manager

Consent Mode is a powerful feature that enables websites to adapt their tracking behavior based on user consent status. Google Tag Manager simplifies the implementation of Consent Mode, making it more accessible to marketers and developers.

Here's a step-by-step guide to implementing Consent Mode via GTM:

  1. Configure your GA4 Property by enabling the option "Blended" in the Reporting Identity settings.
  2. Get the user's preference from your CMS (Consent Management System) and send it to GTM every time a page is loaded. This user preference reflects the option the user chooses when interacting with the cookie banner.
  3. Create variables in the GTM to collect the user preferences and set the internal variables "analytics_storage" and "ad_storage" based on the information received by the CMS.
  4. Modify the GA4 Configuration Tag and all the Events to enable Consent Mode, so the tags will behave based on the user preference, adding a parameter called GCS in all the GA4 events.
  5. Test and Preview: Utilize the GTM Preview mode to test how Consent Mode behaves based on different consent scenarios.
  6. Publish Changes: Once you're satisfied with the implementation, publish your changes in GTM to apply Consent Mode to your GA4 tracking.

From the moment Consent Mode is implemented correctly, the parameter GCS will be present in all the implemented events by default, saying to GA4 if the User accepted or declined the cookies. Below you can see in the table how the GCS parameter value changes depending on the user preference.

When the events are fired and all the implementation is correct, the GA4 reports will start to fill the data gaps generated by the data privacy laws. Another way of consuming this data and comparing them is having access to the raw data. The third column of the table above shows how it's stored. This data can be consumed by Google Big Query.


In a data-driven world where user privacy is paramount, GA4's Reporting Identity setting and Consent Mode provide a robust solution. By understanding and configuring the Reporting Identity setting appropriately, you can ensure accurate tracking while respecting user privacy preferences. Implementing Consent Mode through GTM offers a seamless way to manage user consent, enhancing both compliance and user experience. Finally, by utilizing this new feature, you can gain valuable insights while maintaining the highest standards of data privacy. Remember, the digital landscape is dynamic, and staying informed about these features will empower you to navigate the intersection of data analysis and user privacy successfully.

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