There are several reasons why the same user_pseudo_id might appear across multiple devices in BigQuery:
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Firebase Authentication Linking: If your application uses Firebase Authentication and a user logs into the same account on multiple devices, the user_pseudo_idcan be the same across these devices. This is because Firebase links the user’s identity across different sessions and devices based on their account.
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Data Transfer: When users transfer app data between devices, such as through iCloud or Google’s backup service, the user_pseudo_idassociated with the original device can be carried over to the new device. This happens because this identifier, which is stored locally on the device, is included in the transferred data.
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Cross-device Analysis in GA4: While Google Analytics 4 (GA4) has capabilities for cross-device tracking and analysis, it’s important to note that this is more about data modeling and reporting within the GA4 interface. The user_pseudo_idin Firebase and BigQuery is typically unique to a device or app instance. GA4’s cross-device tracking does not directly alter theuser_pseudo_idin the raw data but may use various signals for analysis purposes.
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Probabilistic Attribution: The user_pseudo_idis generally unique to a device or app instance. However, in certain scenarios like account linking or data transfer, it can span multiple devices. It’s important to understand thatuser_pseudo_iditself is not used for probabilistic attribution in the raw data; such complex attribution is more a feature of analytical processing in tools like GA4.
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Using Additional Identifiers: For more detailed device-level tracking, consider using additional identifiers such as device_idorapp_instance_idalongsideuser_pseudo_id. These can provide more granular insights but must be managed in compliance with privacy regulations and user consent.
While user_pseudo_id can appear across multiple devices due to factors like account linking and data transfer, its primary role is as a unique identifier within the raw data. Cross-device tracking and probabilistic attribution are more related to the analytical capabilities of tools like GA4.