Jobber → Klipfolio
AI-first ETL from Jobber into Klipfolio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Jobber into Klipfolio
Datrise syncs Jobber's contacts, accounts, deals, activities, and lifecycle events 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
Jobber: Field service CRM for scheduling, jobs, and customer history.
Klipfolio: Dashboard platform for real-time KPIs and metric wallboards.
How Jobber entities map to Klipfolio
| Jobber entity | Klipfolio object | Notes |
|---|---|---|
| contacts | jobber_contacts | id PK · custom fields → flattened columns for Klips |
| accounts | jobber_accounts | id PK · linked to jobber_contacts |
| deals | jobber_deals | id PK · linked to jobber_contacts |
| activities | jobber_activities | date/time columns events |
FAQ
How does Datrise handle Jobber'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 Jobber to Klipfolio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or data feeds.
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