Ads Offline Conversions DAGs

Overview

The page will walk you through how to configure the tcrm_bq_to_ads_oc_v2 and tcrm_gcs_to_ads_oc_v2 DAGs, and how to prepare the data.

Sometimes, an ad doesn't lead directly to an online sale, but instead starts a customer down a path that ultimately leads to a sale in the offline world, such as at your office or over the phone. By importing offline conversions, you can measure what happens in the offline world after your ad results in a click or call to your business.

For detail, please refer to About offline conversion imports

Configure Airflow Variables

Create New Necessary tcrm_bq_to_ads_oc_v2 DAG Variables

The following section indicates which variables are needed to run the tcrm_bq_to_ads_oc_v2 DAG. You only need to set up these variables if you plan to use BigQuery as your data source.

Variable Name Example Value Variable Information
tcrm_bq_to_ads_oc_v2_bq_dataset_id my_dataset The name of the BigQuery dataset containing the data.
tcrm_bq_to_ads_oc_v2_bq_table_id my_table The name of the BigQuery table containing the data.
tcrm_bq_to_ads_OC_v2_google_ads_yaml_credentials The authentication info for Google Ads API, please refer to Google Ads API Overview for more information.

Create New Required tcrm_gcs_to_ads_oc_v2 DAG Variables

The following section indicates which variables are needed to run the tcrm_gcs_to_ads_oc_v2 DAG. You only need to set up these variables if you plan to use Google Cloud Storage as your data source.

Variable Name Example Value Variable Information
tcrm_gcs_to_ads_oc_v2_gcs_bucket_name my_bucket Cloud Storage bucket name.
tcrm_gcs_to_ads_oc_v2_gcs_bucket_prefix folder/sub_folder The path to the data folder inside the bucket.
tcrm_gcs_to_ads_oc_v2_gcs_content_type (optional) Either JSON or CSV. Cloud Storage content type.
tcrm_gcs_to_ads_oc_v2_google_ads_yaml_credentials The authentication info for Google Ads API, please refer to Google Ads API Overview for more information.

Prepare Data to Send to Google Ads Offline Conversion

Data field explanations:

customerId is the ID of the customer performing the upload.

conversionActionId is the ID of the conversion action associated with this conversion. You can find the id in the url for a specific conversion. Please refer to the screenshot. To view the page. Click on TOOLS AND SETTINGS on the top menu > click on the Conversion under MEASUREMENT in the popup > click on the Conversion action where the offline click conversions will be sent.

conversionDateTime must be the pattern of yyyy-mm-dd hh:mm:ss+|-hh:mm

To send your data to Google Ads you can choose from the following 3 options:

  1. From BigQuery using the tcrm_bq_to_ads_oc_v2 DAG in SQL table Format.

    Table schema:

    Field name Type
    customerId STRING
    conversionActionId STRING
    gclid STRING
    conversionValue STRING
    conversionDateTime STRING

    Example table:

    customerId conversionActionId gclid conversionValue conversionDateTime
    1234567890 123456789 gclick_id_1 0.1 2022-01-11 18:00:00+0900
    1234567890 123456789 gclick_id_2 0.2 2022-01-12 18:00:00+0900
    1234567890 123456789 gclick_id_3 0.3 2022-01-13 18:00:00+0900
    1234567890 123456789 gclick_id_4 0.4 2022-01-14 18:00:00+0900

  2. From Google Cloud Storage using the tcrm_gcs_to_ads_oc_v2 DAG in JSON Format.

    {"customerId": "1234567890", "conversionActionId": "123456789", "gclid": "gclick_id_1", "conversionValue":"0.1", "conversionDateTime": "2022-01-11 18:00:00+0900"}
{"customerId": "1234567890", "conversionActionId": "123456789", "gclid": "gclick_id_2", "conversionValue":"0.2", "conversionDateTime": "2022-01-12 18:00:00+0900"}
{"customerId": "1234567890", "conversionActionId": "123456789", "gclid": "gclick_id_3", "conversionValue":"0.3", "conversionDateTime": "2022-01-13 18:00:00+0900"}
{"customerId": "1234567890", "conversionActionId": "123456789", "gclid": "gclick_id_4", "conversionValue":"0.4", "conversionDateTime": "2022-01-14 18:00:00+0900"}

  3. From Google Cloud Storage using the tcrm_gcs_to_ads_oc_v2 DAG in CSV Format.

    customerId,conversionActionId,googleClickId,conversionValue,conversionTime
1234567890,123456789,gclick_id_1,0.1,2022-01-11 18:00:00+0900
1234567890,123456789,gclick_id_2,0.2,2022-01-12 18:00:00+0900
1234567890,123456789,gclick_id_3,0.3,2022-01-13 18:00:00+0900
1234567890,123456789,gclick_id_4,0.4,2022-01-14 18:00:00+0900

Run Your DAG

In the Airflow console click on the DAGs option from the top menu bar. Find the DAG you’d like to run in the list on the left. Then run it by clicking the Play button on the right side of the list.

Reading DAG's Logs

Please refer to Reading DAG's Logs in FAQ.