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Mailchimp + PostgreSQL

Mailchimp + PostgreSQL

Mailchimp + PostgreSQL integrations

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.

  1. When this happens...
    New Row (Custom Query)
    New Row (Custom Query)
    New Row (Custom Query)Triggers when new rows are returned from a custom query that you provide. Advanced Users Only.
  2. automatically do this!
    Add Subscriber to Tag
    Add Subscriber to Tag
    Add Subscriber to TagTriggers when a subscriber is added to a segment or tag within an audience.
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More things you can do with PostgreSQL and Mailchimp

Discover other triggers and actions you can use with PostgreSQL and Mailchimp

    • Table/View
      Required
    Trigger
    Polling
    Try It
    • Query
      Required
    Trigger
    Polling
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    • Table/View
      Required
    • Primary_key
      Required
    • Order_by
      Required
    • Trigger_column
    Trigger
    Polling
    Try It
    • Table
      Required
    • ID Column
      Required
    Action
    Write
    • Table/View
      Required
    • Order_by
    • Dedupe_key
    Trigger
    Polling
    Try It
  • PostgreSQL triggers, actions, and search
    New Table

    Triggers when you add a new table.

    Trigger
    Polling
    Try It
    • Table
      Required
    Action
    Write
    • Table
      Required
    • Lookup Column
      Required
    • Lookup_value
      Required
    Action
    Search
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About Mailchimp
Mailchimp is an email and marketing automation platform built for growing businesses. Turn email and SMS into revenue.
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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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