Mailchimp Export Integration

Copy

• Copy for LLM

  Copy page as Markdown for LLMs
• View as Markdown

  Open this page as Markdown
• Open in ChatGPT

  Get insights from ChatGPT
• Open in Claude

  Get insights from Claude
• Connect to Cursor

  Install MCP server on Cursor
• Connect to VS Code

  Install MCP server on VS Code

Learn more Mailchimp Import Integration.

You can create a Mailchimp list from data stored in Treasure Data. Use cases include:

1. Personalization through Segmentation: Capture user behaviors from websites or mobile apps, collecting all user events into Treasure Data. Then, write personalization logic in SQL, and export the segmented mailing list to MailChimp for targeted campaigns.
2. Customer Retention: For SaaS and subscription e-commerce businesses, customer retention can drive growth. Identify“at-risk” users with user events stored in Treasure Data and pushed to MailChimp. Send targeted promotions to the at-risk users to re-engage them.

For sample workflows on exporting to Mailchimp, view Treasure Boxes.

Continue to the following topics:

Prerequisites

• Basic knowledge of Treasure Data, including the TD Toolbelt.
• A MailChimp account
• Authorized Treasure Data account access to Mailchimp

Use the TD Console to Create Your Connection

You can use the TD Console to configure your connection. You create a new connection or if you already configured a Mailchimp data connector (an input transfer or an authentication), you can skip to Configure Export Results in Your Data Connection.

Create a New Connection

Go to Integrations Hub > Catalog and search. Locate and select the Mailchimp tile.

A dialog opens in which you provide the required credentials. Specify an Authentication Method.

Authenticating Your Connection

The method you use to authenticate Treasure Data with MailChimp affects the steps you take to enable the data connector. You can choose to authenticate using:

• an API
• OAuth

Using an API to Authenticate

You can specify the MailChimp API Key and credential to authorize Treasure Data access. The API key grants full access to your Mailchimp account.

Using OAuth to Authenticate

OAuth method is not supported for JP and IDCF customers.

You can select an existing OAuth connection for MailChimp from the drop-down or select the link under OAuth connection to create a new one.

Create a New OAuth Connection

When you select Click here to connect a new account, you must sign into your MailChimp account in popup window

By signing into MailChimp, you are authenticating. The action of signing into Mailchimp generates an Oauth authentication.

You are redirected back to the Treasure Data Connections page. Repeat the first step (Create a New Connection) and choose your new OAuth connection, then finish creating your connection.

You now have an authenticated connector that you use to complete configuration for output of data in the next step.

Select Continue. Provide a name for your connector.

Configure Export Results in Your Data Connection

You create a query, or use an existing query, that retrieves data to be exported and placed into a Mailchimp list. In the query, you specify the Treasure Data Mailchimp data connector.

Create Your Query

Go to the TD Console and go to the query editor. Access or write the query that you plan to use to export data. Select Output results.

You can see a simple sample query in the following image:

Read more about writing a query for Mailchimp in the Appendix.

When you select the Output Results checkbox and select Save, The Choose Saved Connection dialog opens.

Choose Saved Connection

The Choose Saved Connection dialog opens. Type the connection name in the search box to filter and select your connection.

Select Create New Connection.

Complete Configuration Fields

Here is a sample configuration.

In this example, the default column names are overridden with “last_name” and “first_name”. Also, you can specify the Mailchimp “column name for group detail” as values. In the following example, the column names values are: “region, age”. For more information on Mailchimp groups, see the Appendix: "More About the Mailchimp Group Category".

Specify the parameters.

(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.

4. In the drop-down, select one of the following schedule options:

   Drop-down Value	Description
   Custom cron...	Review 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

 *    *    *    *    *
 -    -    -    -    -
 |    |    |    |    |
 |    |    |    |    +----- 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:

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.

(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.

• 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 Columnsto 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.

6. Set a Schedule.

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

7. Select Create.

Configure Export Results in Workflow

If you work in Treasure Workflow, you can specify the use of this data connector to output data.

timezone: UTC

_export:
  td:
    database: sample_datasets

+td-result-into-target:
  td>: queries/sample.sql
  result_connection: your_connections_name
  result_settings:
    list_id: your_list_id
    email_column: email
    fname_column: first_name
    lname_column: last_name
    update_existing: true
    grouping_columns: age, region

Specify the result_settings parameters.

Learn more about using data connectors in the workflow to export data.

Appendix

Write the Query to Populate a Mailchimp List

Here is an example MailChimp list before the query results are exported to Mailchimp:

The preceding list is configured with two MailChimp Groups: Age and Region. They have the following categories:

Age

• 0-20
• 21-30
• 31-40
• 41 and above

Region

• Americas
• Asia
• EMEA

Back in the Treasure Data Query page, write and run the following query with MailChimp as Result Export:

SELECT email, first_name, last_name, region, age FROM (
  VALUES ('k@gmail.com', 'K', 'T', 'Asia', '41 and above'),
         ('r@gmail.com', 'R', 'P', 'Americas', '21-30'),
         ('m@gmail.com', 'M', 'C', 'EMEA', '41 and above')
)  tbl (email, first_name, last_name, region, age)

The preceding query requires no source table (for the ease of testing out this feature), but you still must choose your database, so pick “sample_datasets” or any other arbitrary table. Also, make sure that Presto is chosen as the SQL dialect.

The query should complete in a few seconds. After that, check Mailchimp’s List:

MERGE Field’s Type is Address

If you have a MERGE field that is using the type address, you must put the values into a JSON type. The following query with MailChimp exports data with the MERGE field’s type address:

SELECT
  'y@gmail.com' as email,
  'y' as fname, 'L' as lname,
  CAST(MAP(ARRAY['addr1', 'city', 'state', 'zip', 'country'], ARRAY['1234', 'mountain view', 'CA', '95869', 'US']) as JSON) as address,
  'US' as location

More About the Mailchimp Group Category

In Mailchimp, from the dashboard, you can access Lists and specify group options.

In Treasure Data, you can specify the groups. The group detail names in Mailchimp are column names in the query.