LinkedIn Ads → Mode
AI-first ETL from LinkedIn Ads into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads LinkedIn Ads into Mode
Datrise syncs LinkedIn Ads's B2B campaign metrics, spend, clicks, leads, and audience performance into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
LinkedIn Ads: B2B advertising metrics for pipeline and attribution reporting.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How LinkedIn Ads entities map to Mode
| LinkedIn Ads entity | Mode object | Notes |
|---|---|---|
| B2B campaign metrics | linkedin_ads_b2b_campaign_metrics | id PK · custom fields → flattened columns for SQL and notebooks |
| spend | linkedin_ads_spend | id PK · linked to linkedin_ads_b2b_campaign_metrics |
| clicks | linkedin_ads_clicks | id PK · linked to linkedin_ads_b2b_campaign_metrics |
| leads | linkedin_ads_leads | id PK · linked to linkedin_ads_b2b_campaign_metrics |
FAQ
How does Datrise handle LinkedIn Ads's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the LinkedIn Ads to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for LinkedIn Ads
Early access
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