Google Analytics 4 to BigQuery Mapping Tutorial provides the key to translating all the relevant GA4 dimensions and metrics to their corresponding BigQuery dimensions and metrics.
I have successfully mapped around 90% of all available GA4 dimensions and metrics to their corresponding fields in BigQuery.
It is very important to remember that not every GA4 dimension/metric has its corresponding BigQuery field name.
In fact, most GA4 dimensions and metrics lack corresponding BigQuery field names.
Most of them need to be calculated from SQL or derived from your GA4/GTM tracking setup.
- GA4 Attribution Dimensions to BigQuery Mapping.
- GA4 Google Ads Dimensions to BigQuery Mapping.
- GA4 Demographic Dimensions to BigQuery Mapping.
- GA4 Ecommerce Dimensions to BigQuery Mapping.
- GA4 Event-Scoped Ecommerce Metrics to BigQuery Mapping.
- GA4 Item-Scoped Ecommerce Metrics to BigQuery Mapping.
- GA4 Revenue Metrics to BigQuery Mapping.
- GA4 Event Dimensions to BigQuery Mapping.
- GA4 Event Metrics to BigQuery Mapping.
- GA4 Geography Dimensions to BigQuery Mapping.
- GA4 Link Dimensions to BigQuery Mapping.
- GA4 Page/Screen Dimensions to BigQuery Mapping.
- GA4 Page/Screen Metrics to BigQuery Mapping.
- GA4 Platform/Device Dimensions to BigQuery Mapping.
- GA4 User-Scoped Traffic Dimensions to BigQuery Mapping.
- GA4 Session-Scoped Traffic Dimensions to BigQuery Mapping.
- GA4 Session Metrics to BigQuery Mapping.
- GA4 User Dimensions to BigQuery Mapping.
- GA4 User Metrics to BigQuery Mapping.
- GA4 Advertising Metrics to BigQuery Mapping.
You will encounter BigQuery Field Names (Formulas) that are conceptual and assume that you have fields in your BigQuery dataset that directly correspond to these metrics.
If these fields are not directly available, you may need to create them using custom calculations or ensure your GA4 data collection setup captures this data.
I have added a note wherever you encounter conceptual fields.
#1 GA4 Attribution Dimensions to BigQuery Mapping.
By mapping GA4 attribution dimensions to BigQuery fields, you can see the various touchpoints (e.g., organic search, social media ads, email marketing) that led users to a conversion event (e.g., purchase, sign-up).
This breakdown allows you to identify the most effective channels and campaigns to drive conversions.
Here’s a breakdown of GA4 Attribution Dimensions and their corresponding BigQuery fields:
| GA4 Attribution Dimension | What it is | BigQuery Field Name (Formula) |
|---|---|---|
| Campaign / Campaign ID | Represents the name and ID of a promotion or marketing campaign that led to a key event. | traffic_source.campaign AS campaign_name, traffic_source.campaign_id AS campaign_id |
| Default channel group | Channel groupings are rule-based definitions of your traffic sources. | traffic_source.medium AS default_channel_group (Note: This is a simplification and might not accurately reflect actual channel grouping logic.) |
| Manual campaign ID | Displays the ID of a specific campaign or promotion from the click URL or campaign_details event. | traffic_source.manual_campaign_id AS manual_campaign_id |
| Manual campaign name | Shows the specific campaign or promotion name from the click URL or campaign_details event. | traffic_source.manual_campaign_name AS manual_campaign_name |
| Manual ad content | Indicates the creative content used from the click URL or campaign_details event. | traffic_source.manual_ad_content AS manual_ad_content |
| Manual medium | Represents the marketing medium from the click URL or campaign_details event. | traffic_source.manual_medium AS manual_medium |
| Manual source | Identifies the referrer from the click URL or campaign_details event. | traffic_source.manual_source AS manual_source |
| Manual source / medium | Combines the source and medium from the click URL or campaign_details event. | CONCAT(traffic_source.manual_source, ' / ', traffic_source.manual_medium) AS manual_source_medium |
| Manual source platform | Shows the source platform, noted as ‘Manual’, from the click URL or campaign_details event. | traffic_source.manual_source AS manual_source_platform (Note: This might not accurately represent a platform.) |
| Manual term | Displays the paid keyword from the click URL or campaign_details event. | traffic_source.manual_term AS manual_term |
| Medium | Describes the method of acquiring users. | traffic_source.medium AS medium |
| Source | A representation of where traffic originates. | traffic_source.source AS source |
| Source / medium | Details the source and medium that led a user to your website or application. | CONCAT(traffic_source.source, ' / ', traffic_source.medium) AS source_medium |
| Source platform | Identifies the platform managing buying activity. | traffic_source.source AS source_platform (Note: This might not accurately represent a platform.) |
Some fields, such as ‘Manual source platform’ and ‘Source platform’, do not have a direct corresponding field in the BigQuery export schema.
These dimensions are typically derived from other fields or a combination of fields.
The ‘Default channel group’ is not a direct field; it can be derived from ‘traffic_source.medium’ and other traffic source fields using the rules defined for channel groupings.
#2 GA4 Google Ads Dimensions to BigQuery Mapping.
By mapping GA4 Google Ads Dimensions to BigQuery fields, you can analyze campaign performance in great detail by directly accessing metrics like clicks, impressions, conversions, and cost within BigQuery.
In BigQuery, you can combine Google Ads data with website/app data from GA4 to understand how your ads interact with other user touchpoints.
This holistic view helps you evaluate the overall effectiveness of your marketing efforts.
Here’s a breakdown of GA4 Google Ads Dimensions and their corresponding BigQuery fields: