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Mailchimp + PostgreSQL

Add new PostgreSQL rows to Mailchimp as tagged subscribers

Whenever a new row is created from a custom query in your PostgreSQL, this workflow instantly adds a new subscriber to a specified tag in your Mailchimp. It streamlines your processes, allowing you to easily manage your email marketing efforts without manual data entry. You get to save time and ensure your Mailchimp tags are updated with data from PostgreSQL.

Whenever a new row is created from a custom query in your PostgreSQL, this workflow instantly adds a new subscriber to a specified tag in your Mailchimp. It streamlines your processes, allowing you to easily manage your email marketing efforts without manual data entry. You get to save time and ensure your Mailchimp tags are updated with data from PostgreSQL.

  1. When this happens...
    PostgreSQLPostgreSQL
    New Row (Custom Query)

    Triggers when new rows are returned from a custom query that you provide. Advanced Users Only.

    TriggerPolling
  2. automatically do this!
    MailchimpMailchimp
    Add Subscriber to Tag

    Triggers when a subscriber is added to a segment or tag within an audience.

    ActionWrite
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Supported triggers and actions

    • QueryRequired

    Trigger
    Polling
    Try It
    • Table/ViewRequired

    • Primary KeyRequired

    • Order ByRequired

    • Trigger Column

    Trigger
    Polling
    Try It
    • TableRequired

    • ID ColumnRequired

    Action
    Write
    • Table/ViewRequired

    • Order By

    • Dedupe Key

    Trigger
    Polling
    Try It
    • TableRequired

    Action
    Write
    • TableRequired

    • Lookup ColumnRequired

    • Lookup ValueRequired

    Action
    Search
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About Mailchimp

Share your ideas with Mailchimp email newsletters—then use its landing page and form builders to grow your lists and take marketing further with drip and transactional emails.

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About PostgreSQL

PostgreSQL is a powerful, open-source database engine with a uniquely advanced query optimizer and dozens of built in features, making it an easy choice for production databases.

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