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You can calculate the values of the Google Analytics 4 Returning Users metric in BigQuery by counting distinct values of user_pseudo_id whose first interaction date occurs before the specified time period but who generated at least one event within the period.

Use the following SQL (automatically generated via a text prompt in ChatGPT) to track GA4 Returning Users in BigQuery:

-- Calculate Returning Users

SELECT
  COUNT(
    DISTINCT NULLIF(TRIM(user_pseudo_id), '')
  ) AS `Returning Users`
FROM
  `dbrt-ga4.analytics_207472454.events_*`
WHERE
  _TABLE_SUFFIX BETWEEN '20251001' AND '20251031'
  AND NULLIF(TRIM(user_pseudo_id), '') IS NOT NULL
  AND DATE(TIMESTAMP_MICROS(user_first_touch_timestamp)) < DATE '2025-10-01';

I am not a fan of cookie-cutter reports. But if you want one, this one could be for you.

All you have to do is supply your table ID to generate SQL that works for you.


If you want to customize this report according to your unique data analysis requirements then you need to understand the “logic” used behind calculating the various metrics in this report.

Once you understand the logic, customizing this report is easy peasy.


I teach you such logic in my GA4 BigQuery course, where you can learn to automate SQL generation via text prompts in ChatGPT.

There could be ‘N’ use cases, and it won’t be possible to provide ready-made SQL code for every possible case.

So, it is better that you understand the logic to scale SQL generation to the moon.


The future belongs to those who can query raw GA4 data in BigQuery, apply SQL logic, automate SQL generation via AI and drive insights beyond what GA4 UI can offer.
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  20. Tracking Google Analytics 4 Returning Users in BigQuery.