Marketing · Source connector
AdMob ELT Connector
Extract brings AdMob marketing data into data warehouses and databases for analysis with the rest of your business data. Teams use it to analyze campaign, creative, placement, spend, and revenue performance at a granular level. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Granular campaign optimization
Analyze AdMob campaign, creative, placement, geo, device, spend, and revenue detail to find opportunities to improve performance.
Direct-network reporting
Compare granular AdMob data with standard MMP and cost-aggregation reporting to work with dimensions those tools do not make available.
Spend and revenue reconciliation
Reconcile AdMob spend and revenue with finance, attribution, and internal performance data to investigate discrepancies.
Flexible performance monitoring
Refresh AdMob pacing, anomaly, and performance views every 15 minutes, hourly, daily, or on a custom schedule.
Warehouse and database analysis
Use Extract to make AdMob marketing data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Audience and campaign activation
Combine AdMob performance data with approved customer models, then use Extract Reverse ETL to activate audience or campaign updates downstream.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
ad_sources | Fields include _singular_extract_timestamp, ad_source_id, name, title. | Full refresh |
ad_units | Fields include ad_unit_id, app_id, _singular_extract_timestamp, ad_format. | Full refresh |
apps | Fields include app_id, _singular_extract_timestamp, app_approval_state, linked_app_info.app_store_id. | Full refresh |
mediation_report | Fields include ad_unit, app, ad_source, ad_source_instance. | Incremental |
Schema
Data model at a glance
ad_sources
_singular_extract_timestampstringad_source_idstringnamestringtitlestring
ad_units
ad_unit_idstringapp_idstring_singular_extract_timestampstringad_formatstringad_typesarraydisplay_namestringnamestring
apps
app_idstring_singular_extract_timestampstringapp_approval_statestringlinked_app_info.app_store_idstringlinked_app_info.display_namestringmanual_app_info.display_namestringnamestringplatformstring
mediation_report
ad_unitstringappstringad_sourcestringad_source_instancestringcountrystringdatestringformatstringmediation_groupstring
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with AdMob in Extract workflows.
Why Extract
Why Extract for AdMob
- Rust-native performanceUse Rust-native data movement to refresh AdMob reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect AdMob API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine AdMob 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 AdMob 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 AdMob data with Extract?
Historical coverage for AdMob: 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 AdMob data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect AdMob 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 AdMob?
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 AdMob data model look like in the destination?
The Available streams table describes the datasets Extract can read from AdMob. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.