DatriseAI-first ETL

ConvertKit to Looker Studio Integration

AI-first ETL from ConvertKit into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads ConvertKit into Looker Studio

Datrise syncs ConvertKit's subscribers, forms, sequences, tags, broadcasts, and email events into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

ConvertKit: Email marketing built for creators.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How ConvertKit entities map to Looker Studio

ConvertKit entityLooker Studio objectNotes
subscribersconvertkit_subscribersid PK · custom fields → flattened columns for chart fields
formsconvertkit_formsid PK · linked to convertkit_subscribers
sequencesconvertkit_sequencesid PK · linked to convertkit_subscribers
tagsconvertkit_tagsid PK · linked to convertkit_subscribers

FAQ

How does Datrise handle ConvertKit's custom fields in Looker Studio?

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

How does the ConvertKit to Looker Studio sync stay up to date?

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

Related pipelines

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