In GA4, a valuable addition is the ‘Landing Page + query string’ field, which exhibits all query parameters, regardless of their exclusion status. This feature proves particularly beneficial for digital marketers aiming to address a common challenge – the absence or inconsistency of UTMs.

In this guide, I’ll demonstrate how to conduct a comprehensive audit of all landing pages through BigQuery. Although GA4’s Explore feature allows insight into specific pages, aggregating results at scale is not feasible through it. Hence, we’ll utilize the Google Analytics 4 BigQuery dataset for a more scalable approach.

For those seeking a streamlined and automated audit method for their Google Analytics accounts, I highly recommend using the GA4 Audit tool, a tool I recently developed.

Before delving into the BigQuery aspect, it’s crucial to highlight the setting for the Explore report if you opt for it in GA4:


  • Session source / medium
  • Landing page + query string


  • Sessions


  • Landing page + query string containing any of the following strings:
    • fbclid: Facebook click id
    • ttclid: TikTok click id
    • sccid: Snapchat click id
    • twclid: Twitter click id
    • msclkid: Microsoft Ads click id

To audit additional parameters, you can simply add them as needed. After reviewing the report, you’ll have insights into the values for each specific landing page and source/medium. The challenge arises in aggregating data and obtaining an overview of each traffic source. While exporting data to Excel is an option, we’ll leverage BigQuery for automation. The final Explore report should resemble the following:

GA4 BigQuery Dataset

The GA4 BigQuery dataset, by default, encompasses full page location URLs, including query parameters unless not passed to GA4. To analyze this dataset, the following query can be employed. It aggregates results by source/medium, allowing customization for additional click ID fields. Ensure to modify the table suffix based on your desired date range.

For pinpointing landing pages lacking UTM parameters, include “landing_page” in the select clause of the query. This provides visibility into landing pages associated with each click ID, aiding in identifying those lacking UTM parameters. By incorporating this information, your analysis gains a more comprehensive understanding of the extent to which GA4 BigQuery UTMs are missing or inconsistent across landing pages.

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