Google Analytics Campaign Data Quality & Attribution Reporting Updates

Apr 23, 2025 - 7:11 am 0 by
Filed Under Web Analytics

Google Analytics

A week or so ago, Google Analytics made some updates to how it handles campaign data quality and attribution reporting. Many are now seeing a new label named "Data not available" show up in their GA4 reporting.

Anu Adegbola covered this last week at Search Engine Land, but this is now catching on and Ginny Marvin, Google's Ads Liaison, has been replying to questions about this topic this week.

Google posted the changes over here and wrote, "Google Analytics is elevating data quality and making high-quality data the standard in this dynamic environment."

Google said it enhanced its "data completeness" by saying:

  • Aggregate identifiers: Google started rolling out aggregate identifiers to maintain reporting accuracy in situations where Google Analytics cannot automatically retrieve campaign information from Google Ads using the Google Click Identifier (GCLID). This helps mitigate potential over-attribution of Google Paid channels to Organic.
  • Smart fallback mechanisms: When the Google Click Identifier (GCLID) cannot be used, Google Analytics will utilize aggregate identifiers as a secondary option. Manual tagging (UTMs), and more specifically utm_campaign, can serve as the final fallback to ensure campaign attribution accuracy when other identifiers are unavailable, and helps reduce instances where traffic is incorrectly labeled as “Organic.”

Google also made some updates to its data presentation including:

  • "Data not available": A new label, '(data not available)', will appear in traffic source fields (Source and Medium) when Google Analytics hasn't received or processed the information, often due to delays with processing intervals. This enhancement improves accuracy and helps distinguish between what users can address and what's not addressable as a result of system processing.
  • (not set): The label, '(not set)', appears in your reports as a placeholder name when Google Analytics has not received any information for a specific dimension. This can stem from various reasons, such as tracking implementation or configuration issues, user privacy settings, data processing intervals, or missing parameters. Often there are changes a user can make to reduce rates of (not set) values like enabling auto tagging or linking your Google Ads account and Analytics property.

Here is a screenshot:

Ga4 Data Not Set

The data not available is getting some attention, which Julius Fedorovicius questioned. Ginny Marvin replied to that on LinkedIn:

To clarify a bit here, the value "(data not available)" appears in your reports when data in Google Analytics is unavailable or hasn't been processed for the Source and Medium traffic-source dimensions.

Users generally cannot take action to reduce "(data not available)" values in reports.

This differs from "(not set)" values where corrective actions are often possible (more on that label here).

With these two data labels, we aim to provide a deeper understanding of what data you can and cannot act on.

And thank you for your feedback on the documentation. We recognize it’s light on detail and are planning an update to provide more information.

Google also posted about "deeper insights" explaining:

  • Proactive data quality indicator: The data quality indicator menu, accessed at the top of reports, acts as a proactive early warning system. It helps identify and resolve implementation errors. For example, when a report shows a high rate of missing session_start events, we display an icon that when interacted with will explain the issue detected, the cause and a link to more information, including how to resolve them. These tools provide guidance and resources to help users ensure accurate data collection. Google will continue adding these capabilities for potential incorrect user-ID implementation in the near future.
  • System-generated annotations: Google Analytics has introduced system-generated annotations within reports to inform users about changes that may impact their data. This keeps users informed about the evolving features and how they might affect their analytics. These annotations look similar to user created annotations, except that they can’t be edited or deleted.

Here is Ginny's post on this:

Forum discussion at LinkedIn.

 

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