Here’s a breakdown of GA4 User Dimensions and their corresponding BigQuery fields:

Points to consider

Audience name: The GA4 BigQuery export does not directly include audience names as a dimension. Audience membership is typically managed within GA4 and might not be exported directly to BigQuery. Analyzing audience membership over time would require custom implementation.

Solutions for Analyzing Audience Membership:

#1 Custom User Properties

If you have configured audience membership as a custom user property in GA4, this data can be analyzed directly in BigQuery. Custom user properties are exported to BigQuery and can be queried like any other field.

To analyze audience membership:

1. Identify the User Property Key: Determine the key used for audience membership in your GA4 setup.
2. Query the User Property: Use an SQL query to extract and analyze this user property from the user_properties array in your BigQuery dataset.

SELECT
  user_pseudo_id,
  (SELECT value.string_value FROM UNNEST(user_properties) WHERE key = 'audience_membership') AS audience_name
FROM
  `your_project.your_dataset.your_table`

#2 Event Tagging

Configure your GA4 events to include a custom dimension that captures the audience a user belongs to.

Analyze events in BigQuery to see which audience members are performing specific actions.

SELECT
  event_name,
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'audience_name') AS audience_name,
  COUNT(*) AS event_count
FROM
  `your_project.your_dataset.your_table`
GROUP BY
  event_name, audience_name

#3 Post-Processing Data

Consider post-processing your GA4 data outside of BigQuery to include audience information. This might involve exporting relevant data from GA4 and then joining it with audience data from your audience management tool based on the user ID or another common identifier.