Marketing · Source connector
Google Search Console ELT Connector
Extract brings Google Search Console marketing data into data warehouses and databases for analysis with the rest of your business data. Teams use it to compare channel performance, audience engagement, and campaign trends. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Marketing performance analysis
Compare Google Search Console channel, campaign, and engagement trends to identify opportunities for improvement.
Audience and content analysis
Use Google Search Console data to understand which audiences, content, and activities contribute to engagement.
Cross-channel reporting
Combine Google Search Console metrics with other marketing and business data for consistent performance reporting.
Flexible reporting cadence
Refresh Google Search Console reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Google Search Console marketing data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
page_performance_detailed_page | Fields include country, date, device, page. | Incremental |
page_performance_detailed_page_and_query | Fields include country, date, device, page. | Incremental |
page_performance_detailed_query | Fields include country, date, device, site_url. | Incremental |
sitemaps | Fields include path, site_url, contents, errors. | Full refresh |
sites | Fields include site_url, permission_level. | Full refresh |
property_performance_accurate | Fields include country, date, device, site_url. | Incremental |
property_performance_detailed_query | Fields include country, date, device, query. | Incremental |
page_performance_accurate | Fields include country, date, device, site_url. | Incremental |
Schema
Data model at a glance
page_performance_detailed_page
countrystringdatestringdevicestringpagestringsite_urlstringtypestringclicksnumberctrnumber
page_performance_detailed_page_and_query
countrystringdatestringdevicestringpagestringquerystringsite_urlstringtypestringclicksnumber
page_performance_detailed_query
countrystringdatestringdevicestringsite_urlstringtypestringclicksnumberctrnumberimpressionsnumber
sitemaps
pathstringsite_urlstringcontentsstringerrorsintegeris_pendingbooleanis_sitemaps_indexbooleanlast_downloadedstringlast_submittedstring
sites
site_urlstringpermission_levelstring
property_performance_accurate
countrystringdatestringdevicestringsite_urlstringtypestringclicksnumberctrnumberimpressionsnumber
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Google Search Console in Extract workflows.
Why Extract
Why Extract for Google Search Console
- Rust-native performanceUse Rust-native data movement to refresh Google Search Console reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Google Search Console API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Google Search Console data with customer and finance models, then send approved outputs through a separately configured Reverse ETL destination.
FAQ
Frequently asked questions
How does Extract handle incremental and full Google Search Console syncs?
An incremental sync processes only new or changed data since a stored checkpoint or new date partition, while a full sync processes the complete selected dataset or date range again. By avoiding repeated processing and writes for the full dataset, incremental syncs can reduce destination database updates and warehouse compute costs. Stream schemas define full refresh, partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Google Search Console data with Extract?
Historical coverage for Google Search Console: Backfill (Days) (backfill): The backfill setting revisits and updates data from the past X days, ensuring the most current and accurate information replaces any previously pulled data. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Google Search Console data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Google Search Console API activity, execution steps, and timing. This helps teams distinguish a source-data delay from a failed or incomplete run.
How often can Extract sync data from Google Search Console?
Extract supports schedules every 15 minutes, hourly, daily, or on a custom cadence. Teams can choose a frequency that matches routine reporting, time-sensitive monitoring, or operational activation needs.
What does the Google Search Console data model look like in the destination?
The Available streams table describes the datasets Extract can read from Google Search Console. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.