Question from user:
I’m trying to import my cost data file into GA4, but it is showing an unknown status.
Why do you think that is?
Answer from Nabil:
The short answer is:
The “unknown” status usually indicates a major structural or mapping failure with the uploaded file, or a temporary system-level glitch.
The most common causes are a mismatch between the columns in your file and the GA4 dimensions you mapped them to, incorrect date formatting, or a very specific bug where you’re logged into multiple Google accounts in the same browser session.
The long answer is:
The “unknown” status is frustrating because GA4 typically gives a percentage of import success, but when it’s “unknown,” it means the system can’t even start processing or encounters a critical, unhandled error right away.
The primary cause is often an issue with the file format or the mapping you selected during the data source creation, where the data file contains values that don’t match the Analytics dimensions.
The key matching fields GA4 uses for cost data are Source, Medium, and Date, and optionally Campaign ID and Campaign name.
If any of these are formatted incorrectly, have empty (null) values, or aren’t mapped correctly to their corresponding Analytics fields, the entire upload can fail with that vague “unknown” message.
For example, the date field must be in YYYY-MM-DD format, and the cost metric is expected to be a daily value formatted as a number (e.g., 1234.56) and the currency should match your GA4 property currency.
Another less common, but easy-to-fix issue that has been reported by other users is being logged into multiple Google accounts simultaneously while trying to perform the import; logging out of all other accounts and retrying can sometimes solve it.
Finally, if you’re trying to upload data older than the last 90 days, the import will also fail, but it’s not always labeled as “unknown.”
To move beyond the manual or SFTP upload errors and ensure robust, automatic cost data collection, implementing a solution that uses the Google Analytics Data API, Google Tag Manager (GTM), and a server-side environment like Stape or Google Cloud Platform is an excellent approach.
This setup involves using the advertising platform’s API to extract the cost data, transforming it to perfectly match the GA4 schema (specifically the required Source, Medium, and Date keys), and then sending it directly into GA4 via the Measurement Protocol or a controlled SFTP upload job.
This method gives you complete control over the data preparation and avoids the unpredictable errors of manual file uploads.
For instance, you could use GTM’s server-side container to pull the data from Google Cloud Platform or Stape, ensure all your UTM parameters like utm_source and utm_medium are consistently lowercase, and then dispatch the data with high confidence, thus sidestepping the “unknown” status by guaranteeing the data integrity before it reaches GA4.
This level of automation and data cleansing drastically reduces human error and gives you a much more stable and reliable flow of your non-Google ad costs for accurate ROI reporting.
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