Marketing · Source connector
Liftoff Ads ELT Connector
Extract brings Liftoff Ads 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 Liftoff Ads campaign, creative, placement, geo, device, spend, and revenue detail to find opportunities to improve performance.
Direct-network reporting
Compare granular Liftoff Ads data with standard MMP and cost-aggregation reporting to work with dimensions those tools do not make available.
Spend and revenue reconciliation
Reconcile Liftoff Ads spend and revenue with finance, attribution, and internal performance data to investigate discrepancies.
Flexible performance monitoring
Refresh Liftoff Ads pacing, anomaly, and performance views every 15 minutes, hourly, daily, or on a custom schedule.
Warehouse and database analysis
Use Extract to make Liftoff Ads marketing data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Audience and campaign activation
Combine Liftoff Ads 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 |
|---|---|---|
daily_creative_by_site | Fields include creative_id, date, site_id, creative_name. | Incremental |
daily_creative_by_placement | Fields include creative_id, date, placement_id, creative_name. | Incremental |
campaigns_tracking_events | Fields include campaign_id, _singular_extract_timestamp, name, url. | Full refresh |
daily_creative_by_country | Fields include creative_id, country, date, creative_name. | Incremental |
campaigns_budget_publisher_rates | Fields include campaign_id, geo, pub_app_id, _singular_extract_timestamp. | Full refresh |
campaigns_budget_daily_spend_limit_geos | Fields include campaign_id, geo, _singular_extract_timestamp, rate. | Full refresh |
daily_creative_by_platform | Fields include creative_id, date, platform, creative_name. | Incremental |
daily_campaign_by_platform | Fields include campaign_id, date, platform, campaign_name. | Incremental |
daily_campaign_by_placement | Fields include campaign_id, date, placement_id, campaign_name. | Incremental |
daily_creative_by_ad_type | Fields include creative_id, ad_type, date, creative_name. | Incremental |
daily_campaign_by_site | Fields include campaign_id, date, site_id, campaign_name. | Incremental |
campaigns | Fields include id, application.id, application.name, application.platform. | Full refresh |
applications | Fields include id, _singular_extract_timestamp, name, platform. | Full refresh |
daily_campaign_by_country | Fields include campaign_id, country, date, campaign_name. | Incremental |
creatives | Fields include campaign_id, id, application_id, _singular_extract_timestamp. | Full refresh |
Schema
Data model at a glance
daily_creative_by_site
creative_idstringdatestringsite_idstringcreative_namestring_singular_extract_timestampstringclicksintegercompletesintegerctrnumber
daily_creative_by_placement
creative_idstringdatestringplacement_idstringcreative_namestring_singular_extract_timestampstringclicksintegercompletesintegerctrnumber
campaigns_tracking_events
campaign_idstring_singular_extract_timestampstringnamestringurlstring
daily_creative_by_country
creative_idstringcountrystringdatestringcreative_namestring_singular_extract_timestampstringclicksintegercompletesintegerctrnumber
campaigns_budget_publisher_rates
campaign_idstringgeostringpub_app_idstring_singular_extract_timestampstringnamestringratenumber
campaigns_budget_daily_spend_limit_geos
campaign_idstringgeostring_singular_extract_timestampstringratenumber
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Liftoff Ads in Extract workflows.
Why Extract
Why Extract for Liftoff Ads
- Rust-native performanceUse Rust-native data movement to refresh Liftoff Ads reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Liftoff Ads API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Liftoff Ads 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 Liftoff Ads 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 Liftoff Ads data with Extract?
Historical coverage for Liftoff Ads: 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 Liftoff Ads data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Liftoff Ads 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 Liftoff Ads?
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 Liftoff Ads data model look like in the destination?
The Available streams table describes the datasets Extract can read from Liftoff Ads. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.