A fundamental question underpinning even the most basic reports in Google Analytics 4 (GA4) is the question of how data points have come together to form that report. Being able to confidently answer questions from stakeholders like “Are user counts being inflated by cross-device traffic?” or “How are user counts affected by cookie consent?” are necessary to maintain trust in the data coming out of your analytics platform. Unfortunately the answers to those questions are not as simple as they may seem. That’s where this blog post can help.
GA4 represents a significant shift from its predecessor, Universal Analytics, introducing new features and methodologies for identifying unique users. One key aspect of GA4 is its approach to user identification and reporting through the feature known as Reporting Identity. This feature is crucial for marketers and analysts to understand as it affects how your data is aggregated and reported. In this blog post, we’ll break down how Reporting Identity works, how it affects your data, and the considerations for selecting the most appropriate identity for your organization.
Reporting Identity refers to how the platform identifies and attributes user interactions across different sessions and devices. GA4 gives you the ability to select which data point(s), called “identity spaces,” the platform should include in its user identification process. The 3 available identity spaces are:
Note: Google Signals is no longer available to be used as an identity space.
Device ID is an identifier for a user’s particular device. On websites, this is the Google Analytics “client ID,” while on apps this is the app instance ID.
User ID is a user-provided, persistent ID that identifies signed-in users across devices. This is not something Google will assign, but instead would be set by your organization. For example, a library card holder might have a unique “Card ID” identifier that would identify the same user, whether they are logged in on their mobile device or on a desktop.
Modeled data can be used for situations when users decline necessary identifiers, e.g. via a cookie consent banner, and thus their directly observed behavioral data is unavailable. GA4 can help fill in those gaps by using data from similar users who did accept cookies to model the behavior of those who did not. Modeled data is only available for accounts that have Consent Mode enabled and meet certain minimum volume thresholds. We have written more about Consent Mode here. When modeled data is being used in your reports it will be indicated in the data quality indicator.
Now that we’ve covered the available identity spaces, let’s jump into the options you have to incorporate them (or not) into GA4’s user identification process. GA4 has 3 reporting identities that are available to choose from.
In general, the more identity spaces that GA4 is able to leverage, the more valid your data will be. For instance, the biggest weakness of using Device-based reporting identity is that GA4 has no way to stitch together the same user who visits on a mobile device and a desktop, and so will count them as two users.
The most important thing to note related to reporting identity is that it is not permanent or destructive. The option you choose does not affect how data is collected, processed, or stored. It is, just like it sounds, an option for customizing your reporting in the GA4 UI itself. You can switch between the different options whenever you would like without making any permanent alteration to the data.
That being said, do note that reporting identity is set at the property level, so if you make a change without reverting it, anyone else using your property for reporting will have their reporting changed to your selected reporting identity as well. You must be an Editor or above to change the reporting identity.
By default, the Reporting Identity will be set to “Blended.” However, you may want to switch it over to better match your organization’s specific reporting capabilities and needs.
Blended: best for organizations experiencing significant signal loss related to unconsented traffic. This reporting identity helps fill in the gaps that may be causing underreporting due to signal loss. Using this reporting identity means probabilistic (i.e. not directly observed) data will be included in your GA4 reporting. Modeled data is not included in the GA4 export to BQ, so this will cause discrepancies between the UI and BQ. We have written extensively about why your GA4 and BQ numbers might not match here.
Observed: Best for organizations that have a unique identifier that identifies their customers, e.g. a Membership ID. This reporting identity does not use modeled data, so you can have confidence that your reporting will only display observed data.
Device-Based: Best for all other organizations, especially ones where your visitors are not typically returning multiple times across different devices. This reporting identity is closest to how Universal Analytics reporting worked, so will be best to use for UA-GA4 continuity purposes. It also aligns how the data will look in the platform compared to when exported to BigQuery. However, it will also mean users visiting across different devices will not be deduplicated, and could lead to inflated User counts. You will also be unable to run most forms of analysis on users’ cross-device behavior, since Analytics will count each device as its own user.
Reporting Identity in GA4 offers a modern approach to reporting on user behavior across sessions and devices. By utilizing a combination of signals, GA4 can provide a more accurate and unified view of user interactions. For marketers, this translates to enhanced user journey mapping, improved attribution, and more effective personalization of marketing efforts.
You should ensure that all GA4 stakeholders understand and are aligned with the chosen Reporting Identity. This will help you understand your data and accurately convey insights, and mitigate data confusion and/or mistrust.
Choosing the right reporting identity for your organization is one of many choices that will need to be made as part of your transition to GA4. Fully understanding these options and their implications for your reporting before selecting your approach will help you make the most of GA4 and leverage its capabilities to drive better business outcomes.
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