# Yahoo Audience Discovery Export Integration

Yahoo! JAPAN will deprecate the API endpoints used in the Yahoo! JAPAN Ads Export Integration on June 30th 2024. Any jobs using the integration's Custom Segment Targeting feature must be migrated to this integration before that date.

Yahoo! JAPAN Audience Discovery (YAD) is a comprehensive service that leverages Yahoo! JAPAN's data combined with companies' data to craft distinct user segments, enabling the addition and targeted distribution of advertisements

This export integration enables the uploading of user identities, such as user emails or IDFA/AAID, together with any user attributes provided, directly to the YAD. From there, it could be linked and used for Display ads delivery on Yahoo! JAPAN Ads

## Prerequisites

- Basic Knowledge of Treasure Data™
- Basic knowledge of the [YAD](https://ads-help.yahoo-net.jp/s/article/H000045962) topic
- Valid Brand ID and Data Source ID issued by Yahoo! JAPAN. Contact your Treasure Data Customer Success representative for details.


## Limitations and constraints

- It could take a maximum of 5 business days to issue the Brand ID and Data Source ID
- Besides the user identifies, the API supports uploading a maximum of 79 additional user attributes
- It can take up to 24 hours for an upload to be processed by the YAD


## Use the TD Console

### Create a new Connection

On TD Console, you must create and configure the data connection before running your query. As part of the data connection, you provide authentication to access the integration following the below steps

1. Open **TD Console.**
2. Navigate to **Integrations Hub > Catalog.**
3. Search for and select **Yahoo! Audience Discovery.**
4. Select **Create Authentication**, and provide the credential information for the integration as described below.
5. Select **Continue,**enter a name for the Authentication, and select **Done**.


### Authentication Fields

| **Field** | **Description** |
|  --- | --- |
| **Brand ID** | Brand ID issued by Yahoo! JAPAN. Please contact your Treasure Data Customer Success representative |


### Configure a Query Result exporting

The TD Console supports multiple ways to export data. Please follow the below steps to export data from the Data Workbench

1. Navigate to **Data Workbench > Queries.**
2. Select **New Query**, and define your query.
3. Select **Export Results** to configure the data exporting.


![](/assets/screenshot-2024-05-27-at-13.08.60.c660e2874c5efd5898076c87205c9c1c3579e1232c32206db66443388b0163ee.9c1a955f.png)

1. Select an existing authentication, or create a new one following the above section.
2. Configure the exporting parameters as described in the [Configuration Parameters](/int/yahoo-audience-discovery-export-integration#h2_2111705584) below, and select **Done.**


### Define your query

Your query must have the first column containing the user identities that match the chosen **User ID Type.** Other columns will be uploaded as additional user attributes. Please do not use a wildcard query as it will cause unexpected behavior of the integration

**Data requirement:**

- Line break and control characters: as the data will be uploaded in TSV file format, data values should not include line break or any control characters that might corrupt the TSV file.


| **Column** | **Description** | **Required / Optional** |
|  --- | --- | --- |
| The first column | The user identities that match the chosen **User ID Type.** Any column name is accepted | Required |
| The second column onward | Additional user attributes. Column names, or alias, will be sent to YAD as-is | Optional |


**Query examples:**

For the raw email, you can send it as is or hash it by SQL before exporting.


```sql
SELECT
  LOWER(TO_HEX(SHA256(TO_UTF8(email))))
FROM
  demo_email
```

If available, values on the second column onward will be uploaded as additional attributes to YAD like `type` and `price` in the below example


```sql
SELECT
  'my@email.com' as uid,
  '012345' as type,
  '2000' as price
```

### Configuration Parameters

| Field | Description |
|  --- | --- |
| User ID Type | Type of user identity, select one of:- Email address
- IDFA
- AAID

 |
| Data Source ID | The Data Source ID issued by Yahoo! JAPAN |


### (Optional) Schedule Query Export Jobs

You can use Scheduled Jobs with Result Export to periodically write the output result to a target destination that you specify.

Treasure Data's scheduler feature supports periodic query execution to achieve high availability.

When two specifications provide conflicting schedule specifications, the specification requesting to execute more often is followed while the other schedule specification is ignored.

For example, if the cron schedule is `'0 0 1 * 1'`, then the 'day of month' specification and 'day of week' are discordant because the former specification requires it to run every first day of each month at midnight (00:00), while the latter specification requires it to run every Monday at midnight (00:00). The latter specification is followed.

#### Scheduling your Job Using TD Console

1. Navigate to **Data Workbench > Queries**
2. Create a new query or select an existing query.
3. Next to **Schedule**, select None.
![](/assets/image2021-1-15_17-28-51.f1b242f6ecc7666a0097fdf37edd1682786ec11ef80eff68c66f091bc405c371.0f87d8d4.png)
4. In the drop-down, select one of the following schedule options:
![](/assets/image2021-1-15_17-29-47.45289a1c99256f125f4d887e501e204ed61f02223fde0927af5f425a89ace0c0.0f87d8d4.png)
| Drop-down Value | Description |
|  --- | --- |
| Custom cron... | Review [Custom cron... details](#custom-cron-details). |
| @daily (midnight) | Run once a day at midnight (00:00 am) in the specified time zone. |
| @hourly (:00) | Run every hour at 00 minutes. |
| None | No schedule. |


#### Custom cron... Details

![](/assets/image2021-1-15_17-30-23.0f94a8aa5f75ea03e3fec0c25b0640cd59ee48d1804a83701e5f2372deae466c.0f87d8d4.png)

| **Cron Value** | **Description** |
|  --- | --- |
| `0 * * * *` | Run once an hour. |
| `0 0 * * *` | Run once a day at midnight. |
| `0 0 1 * *` | Run once a month at midnight on the morning of the first day of the month. |
| "" | Create a job that has no scheduled run time. |



```
 *    *    *    *    *
 -    -    -    -    -
 |    |    |    |    |
 |    |    |    |    +----- day of week (0 - 6) (Sunday=0)
 |    |    |    +---------- month (1 - 12)
 |    |    +--------------- day of month (1 - 31)
 |    +-------------------- hour (0 - 23)
 +------------------------- min (0 - 59)
```

The following named entries can be used:

- Day of Week: sun, mon, tue, wed, thu, fri, sat.
- Month: jan, feb, mar, apr, may, jun, jul, aug, sep, oct, nov, dec.


A single space is required between each field. The values for each field can be composed of:

| Field Value | Example | Example Description |
|  --- | --- | --- |
| A single value, within the limits displayed above for each field. |  |  |
| A wildcard `'*'` to indicate no restriction based on the field. | `'0 0 1 * *'` | Configures the schedule to run at midnight (00:00) on the first day of each month. |
| A range `'2-5'`, indicating the range of accepted values for the field. | `'0 0 1-10 * *'` | Configures the schedule to run at midnight (00:00) on the first 10 days of each month. |
| A list of comma-separated values `'2,3,4,5'`, indicating the list of accepted values for the field. | `0 0 1,11,21 * *'` | Configures the schedule to run at midnight (00:00) every 1st, 11th, and 21st day of each month. |
| A periodicity indicator `'*/5'` to express how often based on the field's valid range of values a schedule is allowed to run. | `'30 */2 1 * *'` | Configures the schedule to run on the 1st of every month, every 2 hours starting at 00:30. `'0 0 */5 * *'` configures the schedule to run at midnight (00:00) every 5 days starting on the 5th of each month. |
| A comma-separated list of any of the above except the `'*'` wildcard is also supported `'2,*/5,8-10'`. | `'0 0 5,*/10,25 * *'` | Configures the schedule to run at midnight (00:00) every 5th, 10th, 20th, and 25th day of each month. |


1. (Optional) You can delay the start time of a query by enabling the Delay execution.


### Execute the Query

Save the query with a name and run, or just run the query. Upon successful completion of the query, the query result is automatically exported to the specified destination.

Scheduled jobs that continuously fail due to configuration errors may be disabled on the system side after several notifications.

(Optional) You can delay the start time of a query by enabling the Delay execution.

## Activate a Segment in Audience Studio

You can also send segment data to the target platform by creating an activation in the Audience Studio.

1. Navigate to **Audience Studio**.
2. Select a parent segment.
3. Open the target segment, right-mouse click, and then select **Create Activation.**
4. In the **Details** panel, enter an Activation name and configure the activation according to the previous section on Configuration Parameters.
5. Customize the activation output in the **Output Mapping** panel.


![](/assets/ouput.b2c7f1d909c4f98ed10f5300df858a4b19f71a3b0834df952f5fb24018a5ea78.8ebdf569.png)

- Attribute Columns
  - Select **Export All Columns** to export all columns without making any changes.
  - Select **+ Add Columns** to add specific columns for the export. The Output Column Name pre-populates with the same Source column name. You can update the Output Column Name. Continue to select **+ Add Columns**to add new columns for your activation output.
- String Builder
  - **+ Add string** to create strings for export. Select from the following values:
    - String: Choose any value; use text to create a custom value.
    - Timestamp: The date and time of the export.
    - Segment Id: The segment ID number.
    - Segment Name: The segment name.
    - Audience Id: The parent segment number.


1. Set a **Schedule**.


![](/assets/snippet-output-connector-on-audience-studio-2024-08-28.a99525173709da1eb537f839019fa7876ffae95045154c8f2941b030022f792c.8ebdf569.png)

- Select the values to define your schedule and optionally include email notifications.


1. Select **Create**.


If you need to create an activation for a batch journey, review [Creating a Batch Journey Activation](/products/customer-data-platform/journey-orchestration/batch/creating-a-batch-journey-activation).

## (Optional) Export Integration Using the CLI

The TD Toolbelt can trigger the Query Result exporting from a CLI. You need to specify the parameters for the exporting job as the `--result` option of the `td query` command. For more information, please refer to [this article](https://docs.treasuredata.com/articles/pd/querying-and-importing-data-to-treasure-data-from-the-command-line).

The format of the option is JSON and the general structure is as follows.


```
{  "type": "yahoo_audience_discovery",  "user_id_type": "MAIL_ADDRESS",  "brand_id": "1234",  "data_source_id": "56789",  "ignore_invalid_records": true}
```

### CLI Parameters

| Name | Description | Value | Default Value | Required |
|  --- | --- | --- | --- | --- |
| type | Describe the name of the service as the destination of export. | yahoo_audience_discovery | N/A | Yes |
| user_id_type | Export user id type. | supported values:   - MAIL_ADDRESS - IDFA - AAID | MAIL_ADDRESS | Yes |
| brand_id | Yahoo brand id. | Yahoo brand id | N/A | Yes |
| data_source_id | Yahoo data source id. | Yahoo data source id | N/A | Yes |
| ignore_invalid_records | Skip invalid records and continue job when set it to true otherwise stop job. | Skip invalid records and continue job when set it to true otherwise stop job. | false | No |


### Example usage


```
$ td query --result '{"type": "yahoo_audience-discovery", "user_id_type": "MAIL_ADDRESS","brand_id": "1234", "data_source_id": "56789", "ignore_invalid_records": true}' -d sample_datasets "select * from sample_table" -T presto
```

# 

## Others

- You can use [Scheduled Job](https://docs.treasuredata.com/articles/pd/scheduling-jobs-using-td-console)  with Result Export to periodically upload data to a target destination
- You can involve this integration in a [TD workflow](/int/using-td-workflow-with-td-integrations) as part of a more advanced data pipeline


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