Support · Source connector
Mailchimp ELT Connector
Extract brings Mailchimp support data into data warehouses and databases for analysis with the rest of your business data. Teams use it to measure support workload, service quality, and customer experience. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Support performance reporting
Use Mailchimp data to measure workload, response patterns, resolution trends, and service quality.
Customer health analysis
Combine Mailchimp support activity with customer and product data to identify accounts needing attention.
Workload planning
Analyze Mailchimp volume and issue trends to plan staffing, routing, and operational follow-up.
Flexible reporting cadence
Refresh Mailchimp reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Mailchimp support data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
member_tags | Fields include email_address, id, list_id, _singular_extract_timestamp. | Full refresh |
interests | Fields include id, category_id, list_id, _singular_extract_timestamp. | Full refresh |
lists | Fields include id, _singular_extract_timestamp, beamer_address, campaign_defaults.from_email. | Full refresh |
segments | Fields include id, list_id, _singular_extract_timestamp, created_at. | Full refresh |
email_activity_report | Fields include list_id, campaign_id, email_id, _singular_extract_timestamp. | Full refresh |
campaign_open_report | Fields include list_id, _singular_extract_timestamp, campaign_id, contact_status. | Full refresh |
interest_categories | Fields include id, list_id, _singular_extract_timestamp, display_order. | Full refresh |
members | Fields include id, list_id, _singular_extract_timestamp, consents_to_one_to_one_messaging. | Full refresh |
campaign_clicks_report | Fields include id, _singular_extract_timestamp, ab_split.a.click_percentage_a, ab_split.a.total_clicks_a. | Full refresh |
shortcut_campaigns | Fields include id, _singular_extract_timestamp, send_time, shortcut_type. | Full refresh |
campaign_abuse_report | Fields include list_id, _singular_extract_timestamp, campaign_id, date. | Full refresh |
automations | Fields include id, recipients.list_id, _singular_extract_timestamp, create_time. | Full refresh |
campaigns | Fields include id, recipients.list_id, _singular_extract_timestamp, ab_split_opts.from_name_a. | Full refresh |
member_marketing_permissions | Fields include _singular_extract_timestamp, email_address, enabled, marketing_permission_id. | Full refresh |
list_tags | Fields include id, _singular_extract_timestamp, name. | Full refresh |
segment_members | Fields include id, list_id, _singular_extract_timestamp, email_address. | Full refresh |
unsubscribers_report | Fields include list_id, campaign_id, email_id, _singular_extract_timestamp. | Full refresh |
automation_emails | Fields include id, recipients.list_id, _singular_extract_timestamp, archive_url. | Full refresh |
Schema
Data model at a glance
member_tags
email_addressstringidintegerlist_idstring_singular_extract_timestampstringdate_addedstringnamestring
interests
idstringcategory_idstringlist_idstring_singular_extract_timestampstringdisplay_orderintegernamestringsubscriber_countstring
lists
idstring_singular_extract_timestampstringbeamer_addressstringcampaign_defaults.from_emailstringcampaign_defaults.from_namestringcampaign_defaults.languagestringcampaign_defaults.subjectstringcontact.address1string
segments
idintegerlist_idstring_singular_extract_timestampstringcreated_atstringmember_countintegernamestringoptions.conditionsjsonoptions.matchstring
email_activity_report
list_idstringcampaign_idstringemail_idstring_singular_extract_timestampstringactionstringemail_addressstringipstringlist_is_activeboolean
campaign_open_report
list_idstring_singular_extract_timestampstringcampaign_idstringcontact_statusstringemail_addressstringemail_idstringlist_is_activebooleanmerge_fieldsjson
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Mailchimp in Extract workflows.
Why Extract
Why Extract for Mailchimp
- Rust-native performanceUse Rust-native data movement to refresh Mailchimp reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Mailchimp API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Mailchimp data with customer and finance models, then send approved outputs through a separately configured Reverse ETL destination.
FAQ
Frequently asked questions
How does Extract handle incremental and full Mailchimp syncs?
An incremental sync processes only new or changed data since a stored checkpoint or new date partition, while a full sync processes the complete selected dataset or date range again. By avoiding repeated processing and writes for the full dataset, incremental syncs can reduce destination database updates and warehouse compute costs. Stream schemas define full refresh. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Mailchimp data with Extract?
Historical coverage for Mailchimp: No connector-specific backfill parameter is exposed. Initial historical coverage depends on the stream and provider. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Mailchimp data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Mailchimp API activity, execution steps, and timing. This helps teams distinguish a source-data delay from a failed or incomplete run.
How often can Extract sync data from Mailchimp?
Extract supports schedules every 15 minutes, hourly, daily, or on a custom cadence. Teams can choose a frequency that matches routine reporting, time-sensitive monitoring, or operational activation needs.
What does the Mailchimp data model look like in the destination?
The Available streams table describes the datasets Extract can read from Mailchimp. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.