Marketing · Source connector
Salesforce Marketing Cloud ELT Connector
Extract brings Salesforce Marketing Cloud marketing data into data warehouses and databases for analysis with the rest of your business data. Teams use it to compare channel performance, audience engagement, and campaign trends. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Marketing performance analysis
Compare Salesforce Marketing Cloud channel, campaign, and engagement trends to identify opportunities for improvement.
Audience and content analysis
Use Salesforce Marketing Cloud data to understand which audiences, content, and activities contribute to engagement.
Cross-channel reporting
Combine Salesforce Marketing Cloud metrics with other marketing and business data for consistent performance reporting.
Flexible reporting cadence
Refresh Salesforce Marketing Cloud reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Salesforce Marketing Cloud marketing 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 |
|---|---|---|
list_subscriber | Fields include id, created_date, list_id, modified_date. | Incremental |
triggered_send | Fields include id, auto_add_subscribers, auto_update_subscribers, bcc_email. | Incremental |
send | Fields include id, bcc_email, created_date, duplicates. | Incremental |
asset | Fields include id, asset_type.display_name, asset_type.id, asset_type.name. | Incremental |
campaign | Fields include id, campaign_code, color, created_date. | Incremental |
journey | Fields include id, created_date, defaults.email, description. | Incremental |
activity | Fields include id, configuration_arguments.triggered_send.email_id, journey_id, key. | Incremental |
campaign_asset | Fields include campaign_id, id, created_date, item_id. | Incremental |
subscriber | Fields include id, created_date, email_address, email_address_preference. | Incremental |
list | Fields include id, category, created_date, description. | Incremental |
Schema
Data model at a glance
list_subscriber
idintegercreated_datestringlist_idintegermodified_datestringobject_idstringpartner_keystringstatusstringsubscriber_keystring
triggered_send
idintegerauto_add_subscribersstringauto_update_subscribersstringbcc_emailstringcategory_idstringcc_emailstringcreated_datestringdescriptionstring
send
idintegerbcc_emailstringcreated_datestringduplicatesintegeremail_idintegeremail_namestringexisting_undeliverablesintegerexisting_unsubscribesinteger
asset
idintegerasset_type.display_namestringasset_type.idintegerasset_type.namestringcategory.idnumbercategory.namestringcategory.parent_idnumbercontentstring
campaign
idstringcampaign_codestringcolorstringcreated_datestringdescriptionstringfavoritebooleanmodified_datestringnamestring
journey
idstringcreated_datestringdefaults.emailarraydescriptionstringkeystringmodified_datestringnamestringversioninteger
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Salesforce Marketing Cloud in Extract workflows.
Why Extract
Why Extract for Salesforce Marketing Cloud
- Rust-native performanceUse Rust-native data movement to refresh Salesforce Marketing Cloud reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Salesforce Marketing Cloud API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Salesforce Marketing Cloud 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 Salesforce Marketing Cloud 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 incremental changes, partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Salesforce Marketing Cloud data with Extract?
Historical coverage for Salesforce Marketing Cloud: Initial historical lookback used before a stream has a cursor. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Salesforce Marketing Cloud data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Salesforce Marketing Cloud 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 Salesforce Marketing Cloud?
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 Salesforce Marketing Cloud data model look like in the destination?
The Available streams table describes the datasets Extract can read from Salesforce Marketing Cloud. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.