Connector

Collect LinkedIn Ads Data in Google BigQuery

Own your LinkedIn Ads data in Google BigQuery with OWOX Data Marts. Collect granular, analytics-ready data directly into BigQuery, control schema and refresh logic, and reuse it across BI tools and AI Insights.

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Marketplace users

175K+

teams running OWOX from the Google Workspace Marketplace

G2 rating

4.9

296 verified reviews on G2

Connector downloads

156K+

open-source connector installs via npm

GitHub stars

231

the platform is open source — star it, fork it, self-host it

S01 · Step 1

Step 1: Create a Google BigQuery Data Storage

Start by connecting your own Google BigQuery project as a data storage.

  • Use your own BigQuery project and datasets
  • Keep full ownership of LinkedIn Ads data
  • No third-party data warehouses

Connect BigQuery

S02 · Step 2

Step 2: Create a LinkedIn Ads Data Mart

Create a new Data Mart and choose Connector as the definition type.

  • Select LinkedIn Ads as the data source
  • Authorize access using your LinkedIn Ads account

Create Linkedin Data Mart

S03 · Step 3

Step 3: Select Fields & Configure Data Import

Choose exactly which LinkedIn Ads data you want to store in BigQuery.

  • Select the appropriate LinkedIn Ads API endpoint
  • Pick required fields such as impressions, clicks, spend, and conversions
  • Define the destination dataset and table name in BigQuery

Configure Data Import

S04 · Step 4

Step 4: Run & Schedule LinkedIn Ads Data Collection

Once published, control how and when LinkedIn Ads data is imported.

  • Incremental load to import current day data
  • Backfill (custom period) to load historical data
  • All runs are logged and visible in Run History

Run Data Mart

S05 · Step 5

Step 5: Use LinkedIn Ads Data Across BI Tools & AI Insights

Your LinkedIn Ads data is now available in Google BigQuery.

  • Analyze data in Google Sheets or Looker Studio
  • Join LinkedIn Ads data with Facebook Ads, CRM, GA4, or revenue tables
  • Enable AI Insights to ask questions or receive alerts

Activate Your Data

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What users are saying

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