Connectors / Integration
Connect Google Ad Manager to Google BigQuery for Smarter Ad Analytics
Automate ad performance data into BigQuery and get scalable reporting without manual exports.
Google Ad Manager + Google BigQuery integration
Google Ad Manager and Google BigQuery are a natural pairing for any publisher or advertiser who's hit the ceiling on built-in reporting. Ad Manager generates a lot of impression, click, revenue, and yield data, but its native reporting tools get limiting fast when you need cross-channel analysis, long-term trend tracking, or custom attribution models. Integrating Ad Manager with BigQuery lets teams automatically stream ad performance data into a scalable data warehouse, where it's ready for SQL-based analysis, BI dashboards, and data science workflows.
The business case is straightforward: ad revenue decisions are only as good as the data behind them. Manually downloading Ad Manager reports and uploading them to BigQuery is slow, error-prone, and creates data latency that delays optimization decisions. An automated integration keeps impression counts, fill rates, eCPM figures, advertiser spend, and line item performance flowing continuously into BigQuery, where they can be joined with first-party audience data, CRM records, or web analytics to build a complete picture of monetization health. Revenue operations, data engineering, and finance teams get reliable, repeatable reporting pipelines that scale with the ad business.
Automate & integrate Google Ad Manager + Google BigQuery
Automating Google Ad Manager and Google BigQuery business processes or integrating data is made easy with Tray.ai.
Use case
Automated Daily Ad Performance Reporting
Schedule a recurring workflow that pulls yesterday's Ad Manager delivery data — including impressions, clicks, revenue, and viewability — and loads it into a dedicated BigQuery dataset. This eliminates manual report downloads and keeps your data warehouse current.
- Zero manual intervention in daily data ingestion
- Consistent, timestamped records for reliable trend analysis
- Finance and ops teams access accurate revenue figures every morning
Use case
Cross-Channel Revenue Attribution
Combine Ad Manager line item and advertiser revenue data in BigQuery alongside data from other ad platforms for unified cross-channel attribution modeling. Analysts can write SQL queries that span programmatic, direct-sold, and third-party demand sources in a single table.
- A single view of revenue across all demand channels
- Supports custom attribution models beyond Ad Manager's native reports
- Reduces analyst time spent manually stitching together CSVs
Use case
Yield Optimization and eCPM Trend Analysis
Stream Ad Manager network performance metrics into BigQuery on a rolling basis and use them to identify eCPM trends by ad unit, placement, device, or geography. Data science teams can build predictive models that inform pricing floors and inventory packaging decisions.
- Catch underperforming ad units before revenue is lost
- Power ML models with clean, structured historical data
- Enables automated floor price recommendations
Use case
Advertiser and Order-Level Pacing Monitoring
Pull Ad Manager delivery data at the order and line item level into BigQuery at regular intervals to track pacing against contracted goals. Trigger alerts or downstream workflows when campaigns are over-delivering or at risk of under-delivery.
- Proactively manage delivery risk for high-value direct campaigns
- Historical pacing data informs future order planning
- Reduces manual monitoring burden on ad operations teams
Use case
Audience Segment Performance Analysis
Load Ad Manager audience segment and key-value targeting data into BigQuery and join it with first-party audience profiles or CDP data. Publishers can then quantify the revenue premium of targeted versus non-targeted inventory at scale.
- Quantify the yield lift from audience targeting
- Supports data-driven audience packaging for direct sales
- Enables granular segment-level reporting not available natively
Use case
Billing Reconciliation and Finance Reporting
Automate the extraction of Ad Manager recognized revenue and invoicing data into BigQuery, where it can be reconciled against CRM deal values, order management systems, or ERP records. Finance teams get a single source of truth for monthly close processes.
- Eliminate manual reconciliation spreadsheets
- Accelerate month-end close with automated data pipelines
- Auditable revenue records with full lineage in BigQuery
Challenges Tray.ai solves
Common obstacles when integrating Google Ad Manager and Google BigQuery — and how Tray.ai handles them.
Challenge
Ad Manager API Report Generation Latency
Ad Manager reports aren't returned synchronously. The API requires you to submit a report job, poll for completion, and then download the result. This async pattern is hard to manage reliably in custom scripts and can fail silently if the polling logic is sloppy.
How Tray.ai helps
Tray.ai's workflow engine natively handles asynchronous API patterns with built-in polling loops and conditional branching. You configure the workflow to submit the report job, wait and poll at intervals until the report is ready, then download and load the data — no custom retry or state management code required.
Challenge
BigQuery Schema Management and Data Type Mismatches
Ad Manager reports return data in CSV or XML format with string-typed fields that need to be cast to the right BigQuery types — integers, floats, timestamps, dates — before loading. When those types don't line up with your BigQuery schema, you get load failures that are annoying to debug.
How Tray.ai helps
Tray.ai's data transformation operators let you map, cast, and reshape Ad Manager report fields before they reach BigQuery. You define type conversions and field mappings in a visual interface, and the BigQuery connector can enforce schema-on-write, so bad data gets caught before it causes a failed ingestion job.
Challenge
Handling API Rate Limits During High-Volume Backfills
When backfilling or syncing large volumes of Ad Manager data, workflows can burn through the Ad Manager API's rate limits quickly. That means throttled requests, incomplete data loads, and no clean way to resume without building custom checkpointing logic yourself.
How Tray.ai helps
Tray.ai has built-in rate limit handling with configurable retry logic, exponential backoff, and delay operators. For large backfill workflows, you can add explicit throttle steps between API calls inside loops. And because tray.ai's workflow execution is durable, a throttled or failed step retries from exactly where it left off — it won't reprocess data that already loaded.
Templates
Pre-built workflows for Google Ad Manager and Google BigQuery you can deploy in minutes.
Daily Ad Manager Report to BigQuery Pipeline
Google Ad Manager 
Google BigQuery Runs on a daily schedule to query Ad Manager for the previous day's network performance report — covering impressions, clicks, CTR, revenue, and fill rate — and appends the results as a new partition in a BigQuery table.
Ad Manager Line Item Delivery Sync to BigQuery
Google Ad Manager Google BigQuery Pulls line item and order delivery data from Ad Manager at a configurable interval and upserts records into BigQuery, enabling pacing dashboards and delivery reconciliation against contracted goals.
Ad Manager Audience Segment Data to BigQuery
Google Ad Manager Google BigQuery Extracts audience segment targeting data and associated performance metrics from Ad Manager and loads them into BigQuery for join analysis with first-party audience data stored in the same warehouse.
Ad Manager PMP Deal Metrics to BigQuery
Google Ad Manager Google BigQuery Syncs Private Marketplace deal-level metrics from Ad Manager into BigQuery on a recurring basis, powering deal health dashboards and buyer performance analysis for programmatic sales teams.
Ad Manager Historical Backfill to BigQuery
Google Ad Manager Google BigQuery A one-time or on-demand workflow that backfills up to 90 days of Ad Manager historical performance data into BigQuery, giving you a baseline dataset for trend analysis and machine learning model training.
Ad Manager Revenue to BigQuery for Finance Reconciliation
Google Ad Manager Google BigQuery Extracts recognized revenue and CPM data from Ad Manager monthly reports and loads structured records into BigQuery where finance teams can reconcile against CRM and ERP data for billing and close processes.
How Tray.ai makes this work
Google Ad Manager + Google BigQuery runs on the full Tray.ai platform
Intelligent iPaaS
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Learn more →Agent Builder
Build AI agents that read, write, and take action in Google Ad Manager and Google BigQuery — with guardrails, audit, and human-in-the-loop.
Learn more →Agent Gateway for MCP
Expose Google Ad Manager + Google BigQuery actions as governed MCP tools — observable, rate-limited, authenticated.
Learn more →Ship your Google Ad Manager + Google BigQuery integration.
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