> ## Documentation Index > Fetch the complete documentation index at: https://docs.narrative.io/llms.txt > Use this file to discover all available pages before exploring further. # Delivering Customer Match Audiences to Google Ads via the API > Upload hashed emails to Narrative and deliver them into a new or existing Google Ads Customer Match user list over the API This guide shows you how to build an unattended integration that uploads an audience to Narrative and delivers it into a Customer Match user list in one Google Ads account. You can create a new user list or add to one that already exists. Before you start, complete the [prerequisites](/guides/connector-apis/google-ads#prerequisites) and [set up API access](/guides/connector-apis/google-ads#set-up-api-access). You need the ID of an enabled Google Ads profile. ## 1. Create the dataset The dataset must carry at least one identifier column that Google Ads can match on. [Required columns](#required-columns) lists them. ```bash theme={null} curl -X POST https://api.narrative.io/datasets \ -H "Authorization: Bearer $NIO_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "name": "spring_buyers_google_ads", "display_name": "Spring Buyers (Google Ads)", "description": "Audience for Google Ads Customer Match", "write_mode": "append", "schema": { "file_config": { "type": "json", "normalize_field_names": false }, "type": "object", "properties": { "sha256_hashed_email": { "type": "object", "properties": { "value": { "type": "string" } } } } } }' # → {"id": 12345, "company_id": , "display_name": "Spring Buyers (Google Ads)", ...} ``` Record the `id` in the response. ### Required columns Both interfaces take the same schema. The dataset needs at least one of these identifier columns: | Column | Shape of each value | | - | - | | `sha256_hashed_email` | `{"value": ...}` | | `hashed_email` | `{"value": ..., "type": "..."}` | | `unique_id` | `{"value": ..., "type": "..."}` | | `raw_email` | A string | | `person_name`, `iso_3166_1_country`, and `postal_address`, together | `person_name` is `{"given_name": "...", "family_name": "..."}`, `iso_3166_1_country` is a string, and `postal_address` is `{"postal_code": "..."}` | Each identifier column is named after its Rosetta Stone attribute, and the connector matches on that column name. A column holds either a plain string or an object. In the dataset schema, declare a string column with `"type": "string"`, and declare an object column with `"type": "object"` and its properties: ```json theme={null} { "type": "object", "properties": { "": { "type": "string" }, "": { "type": "object", "properties": { "": { "type": "" } } } } } ``` Send an object column as an object in each row: ```json theme={null} {"": "...", "": {"": "..."}} ``` See your connector's reference page for the attributes it accepts and their exact shapes. A row with one identifier looks like this: ```json theme={null} {"sha256_hashed_email": {"value": ""}} ``` See [Supported identifiers](/reference/connectors/google-ads#supported-identifiers) for how the destination matches each identifier. ## 2. Activate the dataset ```bash theme={null} curl -X POST https://api.narrative.io/datasets/{dataset_id}/activate \ -H "Authorization: Bearer $NIO_API_TOKEN" ``` The response is `201` with the dataset, now `"status": "active"`. Activation locks the schema, so activate only once the shape is settled. ## 3. Upload and ingest your file Each line of the file is one row that matches the schema you declared in [step 1](#1-create-the-dataset). For the columns Google Ads accepts and their shapes, see [Supported identifiers](/reference/connectors/google-ads#supported-identifiers) and [Required columns](#required-columns). You can load a file into a dataset over the API in two ways: * **Signed-URL upload.** Your integration uploads one file of up to 3 GB, then asks Narrative to ingest it. * **Managed S3 bucket.** You write files to an S3 bucket that Narrative manages, and Narrative ingests each batch on its own. Use a managed bucket for files larger than 3 GB, or for files that another system delivers on a schedule. ### Choose a file format The dataset's `file_config.type` sets the format of every file you load into it. Parquet and JSON Lines both hold object columns, which nest properties inside one column: * **Parquet** (`parquet`) is the most compatible format for connector datasets. It stores nested struct columns and their types natively, and Narrative matches columns to the schema by name at every level. * **JSON Lines** (`json`) holds one JSON object per line. Narrative matches each nested object to the schema by name. CSV datasets (`flat`) hold only scalar columns, so they can't carry object columns. ### Upload a file with a signed URL Request an upload URL, then send the file straight to storage: ```bash theme={null} curl -X POST https://api.narrative.io/uploads/my-file.jsonl \ -H "Authorization: Bearer $NIO_API_TOKEN" # → {"path": "", "url": "https://...", "expiry": "..."} curl -X PUT "" --upload-file ./my-file.jsonl ``` The upload URL is valid for 30 minutes and carries its own signature, so send no authorization header with the `PUT`. Keep the `path` from the response. Narrative assigns its own storage path, which does not match the name you requested, and the ingest request needs Narrative's path rather than yours. Then ingest the file into the dataset, passing that `path` as `source_file`: ```bash theme={null} curl -X POST https://api.narrative.io/datasets/{dataset_id}/upload \ -H "Authorization: Bearer $NIO_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"source_file": ""}' ``` Ingestion runs in the background. Watch the record count on the dataset to know when it has finished: ```bash theme={null} curl -s https://api.narrative.io/datasets/{dataset_id} \ -H "Authorization: Bearer $NIO_API_TOKEN" # → .stats.active_dataset_stored_records ``` The count moves from zero to your row count, typically within a couple of minutes. Each ingested file adds a new snapshot to the dataset, and every active connection on the dataset delivers that snapshot. ### Write files to a managed S3 bucket A managed bucket is an S3 bucket that Narrative creates for your company. You write each batch of files into its own folder under the dataset's path in the bucket, then write an empty `_NIO_COMMIT` file into that batch folder. Narrative ingests every file in the batch folder when the commit file appears, so you make no upload or ingest request. A file can be as large as S3 accepts. See [Ingesting Files from a Managed S3 Bucket](/guides/ingestion/ingesting-files-from-a-managed-s3-bucket) to create the bucket, grant your AWS account access, and lay out the folders. ## 4. Confirm Google Ads accepts the dataset Before you create a connection, ask Narrative which connector interfaces the dataset satisfies: ```bash theme={null} curl -s https://api.narrative.io/datasets/{dataset_id}/interfaces \ -H "Authorization: Bearer $NIO_API_TOKEN" # → {"dataset_id": 12345, # "accepted": [{"app_id": , "interface_id": ""}, ...], # "errors": [{"app_id": , "interface_id": "", "details": {...}}, ...]} ``` The response checks the dataset's schema against every interface of the connectors your company has installed, and sorts the results into two lists: * `accepted` lists each interface you can connect the dataset to, by the connector's `app_id` and the `interface_id`. * `errors` lists each interface the schema does not satisfy. Its `details` hold the reason, such as `"required property '' not found"`. Add `?tags=` to check only the interfaces that carry that tag. When the interface you want is under `errors`, the dataset's schema doesn't meet what the interface needs, for example a missing column or property. Activation locks the schema, so create a new dataset that fixes what the error names. For Google Ads, look for the Google Ads Connector (`"app_id": 14`) in `accepted`. Add `?tags=google-ads` to check only the Google Ads interfaces. ```json theme={null} {"app_id": 14, "interface_id": "audience_first_party_new"}, {"app_id": 14, "interface_id": "audience_first_party_existing"} ``` `audience_first_party_new` creates a new Customer Match user list, and `audience_first_party_existing` adds to one you already have. ## 5. Deliver to a new user list Create a connection. The connector creates the user list in the profile's Google Ads account before it answers, so the list exists in Google Ads once you get `201`. ```bash theme={null} curl -X POST https://api.narrative.io/v2/connections \ -H "Authorization: Bearer $NIO_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "type": "connections_dataset", "dataset_id": 12345, "profile_id": "", "quick_settings": { "type": "audience_first_party_new", "name": "Spring Buyers", "description": "Bought in March or April", "membership_duration_days": 30, "historical_data_enabled": true } }' # → 201 {"type": "connections_dataset", "id": "", # "app": {"id": 14, "name": "Google Ads Connector"}, "dataset_id": 12345, # "installation_id": , # "quick_settings": {"type": "audience_first_party_new", "name": "Spring Buyers", # "description": "Bought in March or April", # "membership_duration_days": 30, "historical_data_enabled": true}, # "profile_id": "", "profile": {"id": "", "name": "Example Brand"}, # "status": "active", ...} ``` Both `type` fields are required. The outer one identifies what you are connecting, and the one inside `quick_settings` selects the delivery interface. [What the connection does](/guides/connector-apis/google-ads#what-the-connection-does) describes every field, its allowed values, and its default. Record the connection `id`. You need it to stop the delivery. ## 6. Confirm the connection ```bash theme={null} curl -s https://api.narrative.io/v2/connections/{connection_id} \ -H "Authorization: Bearer $NIO_API_TOKEN" # → {"type": "connections_dataset", "id": "", ..., "status": "active"} ``` To list every connection on a dataset, or every connection through a profile: ```bash theme={null} curl -s "https://api.narrative.io/v2/connections?dataset_id=12345" \ -H "Authorization: Bearer $NIO_API_TOKEN" curl -s "https://api.narrative.io/v2/connections?profile_id=" \ -H "Authorization: Bearer $NIO_API_TOKEN" # → {"records": [{"type": "connections_dataset", "id": "", ...}]} ``` In Google Ads, open **Tools → Shared library → Audience manager**. The user list appears under the name you gave it, and its ID is on the list's page. You use that ID in the next step. ## 7. Deliver to an existing user list To send another dataset into a user list that already exists, whether Narrative created it or not, connect the dataset with the list's numeric ID from Google Ads Audience manager. In the request below, `12346` is an example ID for an existing dataset. Create and load that dataset with [steps 1 to 4](#1-create-the-dataset) before you connect it: ```bash theme={null} curl -X POST https://api.narrative.io/v2/connections \ -H "Authorization: Bearer $NIO_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "type": "connections_dataset", "dataset_id": 12346, "profile_id": "", "quick_settings": { "type": "audience_first_party_existing", "user_list_id": , "historical_data_enabled": true } }' # → 201 {"type": "connections_dataset", "id": "", # "app": {"id": 14, "name": "Google Ads Connector"}, "dataset_id": 12346, # "quick_settings": {"type": "audience_first_party_existing", # "user_list_id": , "historical_data_enabled": true}, # "profile_id": "", "status": "active", ...} ``` `user_list_id` is a number. The list must belong to the Google Ads account on the profile, and it keeps the membership duration it already has. ## Keeping the audience current Write new rows to the dataset with the same upload calls from [step 3](#3-upload-and-ingest-your-file). The connection keeps running, so the new rows reach the same user list without another connection. To hear when each delivery finishes, subscribe to [delivery notifications](/guides/connector-apis/google-ads#delivery-notifications). ## Stopping delivery ```bash theme={null} curl -X DELETE https://api.narrative.io/v2/connections/{connection_id} \ -H "Authorization: Bearer $NIO_API_TOKEN" # → 200 {} ``` Deleting the connection archives it and stops further deliveries. After that, `GET /v2/connections/{connection_id}` returns `404`. The user list stays in Google Ads with its members. Close it in Audience manager if you no longer want it. To delete the dataset when you no longer need it: ```bash theme={null} curl -X DELETE https://api.narrative.io/datasets/{dataset_id} \ -H "Authorization: Bearer $NIO_API_TOKEN" ``` ## Getting help Contact your Narrative relationship manager with your company ID, the dataset ID, the connection ID, and the request and response. *** ## Related content Prerequisites, API access, profiles, and delivery notifications Supported identifiers and audience membership duration Why a dataset connects to an interface rather than a connector Create and rotate keys for programmatic access This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.