DatriseAI-first ETL

Salesforce Marketing Cloud to Klipfolio Integration

AI-first ETL from Salesforce Marketing Cloud into Klipfolio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Salesforce Marketing Cloud into Klipfolio

Datrise syncs Salesforce Marketing Cloud's subscribers, data extensions, journeys, sends, email events, and lists into Klipfolio as query-ready tables or feeds Klipfolio reads. Flexible or custom fields land in flattened columns for Klips, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or data feeds, so re-runs update only what changed. Date-partitioned facts for trend Klips. Klipfolio pulls from sources on a refresh interval, so Datrise keeps tables incrementally current to match.

Ideal for real-time KPI dashboards and wallboards.

Endpoints

Salesforce Marketing Cloud: Enterprise email, journeys, and cross-channel messaging.

Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.

How Salesforce Marketing Cloud entities map to Klipfolio

Salesforce Marketing Cloud entityKlipfolio objectNotes
subscriberssalesforce_marketing_cloud_subscribersid PK · custom fields → flattened columns for Klips
data extensionssalesforce_marketing_cloud_data_extensionsid PK · linked to salesforce_marketing_cloud_subscribers
journeyssalesforce_marketing_cloud_journeysid PK · linked to salesforce_marketing_cloud_subscribers
sendssalesforce_marketing_cloud_sendsid PK · linked to salesforce_marketing_cloud_subscribers

FAQ

How does Datrise handle Salesforce Marketing Cloud's custom fields in Klipfolio?

Flexible values are stored as flattened columns for Klips, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Klipfolio types.

How does the Salesforce Marketing Cloud to Klipfolio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or data feeds.

Related pipelines

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