Marketing · Source connector
Google Analytics ELT Connector
Extract brings Google Analytics 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 Analytics channel, campaign, and engagement trends to identify opportunities for improvement.
Audience and content analysis
Use Google Analytics data to understand which audiences, content, and activities contribute to engagement.
Cross-channel reporting
Combine Google Analytics metrics with other marketing and business data for consistent performance reporting.
Flexible reporting cadence
Refresh Google Analytics reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Google Analytics 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 |
|---|---|---|
tech_device_model_report | Fields include conversions, date, device_model, engaged_sessions. | Incremental |
user_acquisition_first_user_google_ads_network_type_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
ecommerce_purchases_item_category_5_report | Fields include cart_to_view_rate, date, item_category5, item_revenue. | Incremental |
properties | Fields include name, account, create_time, currency_code. | Incremental |
custom_dimensions | Fields include name, description, disallow_ads_personalization, display_name. | Full refresh |
ecommerce_purchases_item_category_report_combined | Fields include cart_to_view_rate, date, item_category, item_category2. | Incremental |
tech_device_category_report | Fields include conversions, date, device_category, engaged_sessions. | Incremental |
google_ads_links | Fields include name, ads_personalization_enabled, can_manage_clients, create_time. | Incremental |
traffic_acquisition_session_source_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
custom_metrics | Fields include name, description, display_name, measurement_unit. | Full refresh |
traffic_acquisition_session_default_channel_grouping_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
accounts | Fields include name, create_time, display_name, region_code. | Incremental |
tech_os_with_version_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
demographic_interests_report | Fields include branding_interest, conversions, date, engaged_sessions. | Incremental |
traffic_acquisition_session_campaign_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
ecommerce_purchases_item_id_report | Fields include cart_to_view_rate, date, item_id, item_revenue. | Incremental |
demographic_city_report | Fields include city, conversions, date, engaged_sessions. | Incremental |
publisher_ads_ad_unit_report | Fields include ad_unit_exposure, ad_unit_name, date, publisher_ad_clicks. | Incremental |
events_report | Fields include date, event_count, event_count_per_user, event_name. | Incremental |
traffic_acquisition_session_source_medium_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
traffic_acquisition_session_medium_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
publisher_ads_ad_source_report | Fields include ad_source_name, ad_unit_exposure, date, publisher_ad_clicks. | Incremental |
demographic_region_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
pages_path_report | Fields include conversions, date, event_count, new_users. | Incremental |
tech_browser_report | Fields include browser, conversions, date, engaged_sessions. | Incremental |
tech_screen_resolution_report | Fields include app_version, conversions, date, engaged_sessions. | Incremental |
tech_platform_device_category_report | Fields include conversions, date, device_category, engaged_sessions. | Incremental |
user_acquisition_first_user_source_medium_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
demographic_gender_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
ecommerce_purchases_item_category_3_report | Fields include cart_to_view_rate, date, item_category3, item_revenue. | Incremental |
ecommerce_purchases_item_name_report | Fields include cart_to_view_rate, date, item_name, item_revenue. | Incremental |
conversion_events | Fields include name, counting_method, create_time, custom. | Full refresh |
publisher_ads_ad_format_report | Fields include ad_format, ad_unit_exposure, date, publisher_ad_clicks. | Incremental |
user_acquisition_first_user_source_platform_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
publisher_ads_page_path_report | Fields include ad_unit_exposure, date, page_path, publisher_ad_clicks. | Incremental |
tech_operating_system_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
ecommerce_purchases_item_category_report | Fields include cart_to_view_rate, date, item_category, item_revenue. | Incremental |
ecommerce_purchases_item_category_2_report | Fields include cart_to_view_rate, date, item_category2, item_revenue. | Incremental |
demographic_age_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
data_streams | Fields include name, android_app_stream_data.firebase_app_id, android_app_stream_data.package_name, create_time. | Incremental |
tech_platform_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
firebase_links | Fields include name, create_time, project. | Full refresh |
user_acquisition_first_user_source_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
pages_title_and_screen_name_report | Fields include conversions, date, event_count, new_users. | Incremental |
user_acquisition_first_user_campaign_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
ecommerce_purchases_item_brand_report | Fields include cart_to_view_rate, date, item_brand, item_revenue. | Incremental |
traffic_acquisition_session_source_platform_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
demographic_language_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
demographic_country_report | Fields include conversions, country, date, engaged_sessions. | Incremental |
tech_os_version_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
pages_title_and_screen_class_report | Fields include conversions, date, event_count, new_users. | Incremental |
conversions_report | Fields include conversions, date, event_name, total_revenue. | Incremental |
user_acquisition_first_user_google_ads_ad_group_name_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
ecommerce_purchases_item_category_4_report | Fields include cart_to_view_rate, date, item_category4, item_revenue. | Incremental |
content_group_report | Fields include content_group, conversions, date, event_count. | Incremental |
user_acquisition_first_user_medium_report | Fields include conversions, date, engaged_sessions, engagement_rate. | Incremental |
audiences_report | Fields include active_users, audience_name, average_session_duration, date. | Incremental |
Schema
Data model at a glance
tech_device_model_report
conversionsnumberdatestringdevice_modelstringengaged_sessionsnumberengagement_ratenumberevent_countnumbernew_usersnumbertotal_revenuenumber
user_acquisition_first_user_google_ads_network_type_report
conversionsnumberdatestringengaged_sessionsnumberengagement_ratenumberevent_countnumberfirst_user_google_ads_ad_network_typestringnew_usersnumbertotal_revenuenumber
ecommerce_purchases_item_category_5_report
cart_to_view_ratenumberdatestringitem_category5stringitem_revenuenumberitems_added_to_cartnumberitems_purchasednumberitems_viewednumberpurchase_to_view_ratenumber
properties
namestringaccountstringcreate_timestringcurrency_codestringdelete_timestringdisplay_namestringexpire_timestringindustry_categorystring
custom_dimensions
namestringdescriptionstringdisallow_ads_personalizationbooleandisplay_namestringparameter_namestringscopestring
ecommerce_purchases_item_category_report_combined
cart_to_view_ratenumberdatestringitem_categorystringitem_category2stringitem_category3stringitem_category4stringitem_category5stringitem_revenuenumber
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Google Analytics in Extract workflows.
Why Extract
Why Extract for Google Analytics
- Rust-native performanceUse Rust-native data movement to refresh Google Analytics reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Google Analytics API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Google Analytics 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 Analytics 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, incremental changes, partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Google Analytics data with Extract?
Historical coverage for Google Analytics: 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 Analytics data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Google Analytics 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 Analytics?
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 Analytics data model look like in the destination?
The Available streams table describes the datasets Extract can read from Google Analytics. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.