DatriseAI-first ETL

Mautic to Looker Studio Integration

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

How Datrise loads Mautic into Looker Studio

Datrise syncs Mautic's contacts, segments, campaigns, forms, page hits, and email stats 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

Mautic: Open-source marketing automation with contact tracking.

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

How Mautic entities map to Looker Studio

Mautic entityLooker Studio objectNotes
contactsmautic_contactsid PK · custom fields → flattened columns for chart fields
segmentsmautic_segmentsid PK · linked to mautic_contacts
campaignsmautic_campaignsid PK · linked to mautic_contacts
formsmautic_formsid PK · linked to mautic_contacts

FAQ

How does Datrise handle Mautic'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 Mautic 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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