Requirements
- To grant access to BigQuery tables, you must have the Owner role or sufficient permissions for the BigQuery project that contains the table.
- Tables or views should be updated before each import.
- For offline conversion imports, one table or view is required per conversion event.
- BigQuery views must be fully authorised and the source of the view cannot include external tables. Learn more about authorised views and external data sources.
Set up BigQuery as a data source
Note: If you have access to a large number of tables or projects, you may experience a delay to download and display your tables. Please allow up to five minutes for a list of tables to become available. If the number of tables or projects is very large, the table list may fail to load.
Apply a use case now
The following sections walk you through a single procedure to link a data source to a use case. Click on your use case to expand the steps. To link the data source only and apply a use case later, see Apply a use case later.
Note: It’s recommended that you add an audience segment to a connection that you created. You can either set up an audience segment before you link a data source or you can create an audience segment in the final step of setting up a data source.
Open Tools > Data Manager. Select the connection that you just made from 'Connected products' and under 'Usage', click + Add audience segment.
- In your Google Ads account, click Tools > Shared library > Audience manager > + (Create) > Customer list.
- Under 'Data source', select Connect a new data source, then search and select Google BigQuery from the list of products.
- Select Direct connection, then click Continue.
- If you previously linked a data source from the Data Manager screen that you want to use, select Select an existing source.
- Under 'Select a data type', choose the data type, then click Continue.
- Select the BigQuery project, dataset and table that you want to use. An alert appears.
- Click Apply to grant access, then click Next.
- To map fields, select the data source fields from the drop-down lists that match the Google fields, then click Continue.
- Enter a name for this connection.
- Optional: Edit connection details.
- Click Done.
- Enter a name for the segment, confirm policy compliance, then click Create.
Tip: Upgrade from offline conversion import to enhanced conversions for leads for more accurate reporting, easier data import and engaged-view and cross-device conversion attribution.
To set up enhanced conversions for leads, you can either use an existing offline conversion import conversion action or create a new conversion action.
Note: It’s recommended that you add a conversion action to a connection that you created. You can either set up a conversion action before you link a data source or you can create a conversion action in the final step of setting up a data source.
Open Tools > Data Manager. Select the connection that you just made from 'Connected products' and under 'Usage', click + Add conversion action.
- In your Google Ads account, click Goals > Summary > + Create conversion action.
- Optional: If you already created a conversion and skipped adding a data source, click Tools > Data Manager > + Connect product.
- Click Import.
- Select CRMs, files or other data sources.
- Select a tracking method.
- Under 'Data source', select Connect a new data source.
- If you previously linked a data source from the Data Manager screen that you want to use, select Select an existing source.
- Search and select Google BigQuery from the list of products, then choose Direct connection.
- Select the tick box for the customer data policy to acknowledge that the data was collected and is being shared in compliance with Google's policies, then click Continue.
- Select a conversion goal from the list, then click Set up.
- Click Save and continue.
- Select the BigQuery project, dataset and table that you want to use. An alert appears.
- Click Apply to grant access, then click Next.
- To map fields, select the data source fields from the drop-down lists that match the Google fields, then click Continue.
- Enter a name for this connection.
- Optional: Edit connection details.
- Click Done.
- Click Save and continue.
Apply a use case later
In this type of setup, you complete each part of the connection at different times. This can be useful when you are ready to link a data source, but you are not ready to set up your use case – for example, you aren’t ready to create a customer list.
Consider the following scenario:
- Step 1: Dana is an engineer who manages data for your company. Dana sets up the data source to be used for activation in Google Ads. The data source is ready to be associated with a use case.
- Step 2: Mahan is a media specialist who needs to measure audience activation. Mahan creates a customer list and then associates it to the data source that Dana has previously set up, to use that data for Customer Match.
Step 1. Initiate the connection to the data source
Set up a data source and create a connection to be associated with a use case later.
- In Google Ads, click Tools > Data Manager > + Connect Product.
- Under Data source, search and select a data source from the list of products.
- If prompted, select Direct connection.
- Select your use case, read and accept the customer data policy, then click Continue. If you select Audiences, you are prompted to select the data type at this step.
- Enter your data source location and credentials*, then click Next.
- To map fields, select the data source fields from the drop-down lists that match the destination fields.
- Optional: Apply transformations to your data.
- Click Next.
- Enter a name for this connection.
- Optional: Edit connection details.
- Click Finish.
- Optional: Depending on the use case, you may add an audience segment or conversion action to your connection.
To do this, select a connection from one of your connected products and under Usage, click + Add audience segment or + Add conversion action. Learn more about audience segments and how to Create a conversion.
* Use the same credentials and location details for this data source as described in the first part of this article.
Step 2. Complete the connection by applying a use case
- Open the destination you intend to use – for example, begin to create a new customer list or conversion action using the steps from the previous sections. Return to these steps before completing the data source step.
- Under Data source, select Select an existing source.
- Select the data source that was initiated in Step 1 from the list of data sources.
- Continue to follow the remaining steps for your use case in the first part of this article. Note that you will skip further data source-related steps, such as entering credentials, because you completed these previously.
BigQuery permissions
To grant Google Ads access to your BigQuery project, you must have the role of BigQuery Data Owner on the project. If you don’t use basic roles, you must have the following underlying permissions:
- bigquery.tables.getIamPolicy
- bigquery.tables.setIamPolicy
- resourcemanager.projects.getIamPolicy
- resourcemanager.projects.setIamPolicy
- bigquery.datasets.setIamPolicy
- bigquery.datasets.update
By granting Google Ads access to your BigQuery project, you are providing Google Ads service accounts with the following permissions:
|
Service account type and purpose |
Service account and permissions required in customer-owned BigQuery project |
|---|---|
|
Datafusion service account This service account is used to display fields from a data source in Google Ads UI. |
|
|
Dataproc service account This service account is used to execute the data load pipelines. |
|
To apply these permissions manually in BigQuery, see Grant access to a resource.
Using VPC Service Controls
If you use VPC Service Controls (VPC-SC), this perimeter restricts access to your BigQuery project by all services. To allow Data Manager to import data from your BigQuery project to Google Ads, the project must be configured with ingress and egress rules. You can allow these rules to be configured automatically, or if needed, you can configure them manually. The following sections describe both methods.
Configure automatically
Data Manager can apply the required rules for you. If the rules are not already configured when you begin setting up BigQuery as a data source, you are prompted to apply them during the enablement workflow. When you click Apply, the necessary rules on the required resources are granted on your behalf.
In order to consent to the automatic configuration, you must meet both of these conditions:
- You have the necessary IAM permission to apply the rules
- Your organisation’s VPC-SC configuration allows you to apply the rules
Configure manually
To configure the rules yourself, open Cloud console, then edit the VPC service parameter rules with the following configuration:
| Ingress rules for Google Ads | |||
|---|---|---|---|
| FROM attributes | Identity | ||
| Source | All sources | ||
| TO attributes | Project |
All projects. At minimum, select the project that hosts the table that you want to use. |
|
| Services |
BigQuery API Cloud Resource Manager Cloud Storage API |
All methods | |
| Egress rules for Google Ads | |||
|---|---|---|---|
| FROM attributes | Identity | ||
| TO attributes | Project |
All projects. At minimum, select the project that hosts the table that you want to use. |
|
| Services |
Cloud Storage API |
All methods | |
