Redbird AI syncs streaming viewership data, ad performance metrics, and audience analytics between BigQuery and Xumo automatically. Stop exporting CSV files, manually building attribution reports, or writing custom ETL pipelines to connect your CTV data warehouse with streaming platform metrics.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically pull watch time, completion rates, and concurrent viewer metrics from Xumo into BigQuery tables. Join CTV performance data with attribution models, ad spend, and content costs for complete ROI analysis across your streaming portfolio.
Send modeled audience cohorts, propensity scores, and viewing behavior segments built in BigQuery to Xumo's ad platform. Enable data-driven targeting without manual segment exports or platform switching.
Combine Xumo's real-time streaming metrics with BigQuery's historical content performance, ad revenue, and engagement data. Create executive dashboards showing content ROI, viewer retention, and monetization trends without manual data merges.
Match Xumo ad exposure events with downstream conversion data stored in BigQuery. Build closed-loop CTV attribution models showing how streaming ad impressions drive outcomes across channels and devices.
Run ML models in BigQuery analyzing Xumo viewership patterns and trigger notifications when content underperforms forecasts or when new releases exceed benchmarks. Enable rapid response to emerging viewing trends without constant dashboard monitoring.
Automatically capture and warehouse daily Xumo viewership metrics, channel performance, and ad delivery data in BigQuery. Build year-over-year comparisons and seasonal trend models without retention policy limitations or manual data preservation workflows.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and Xumo with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands BigQuery's nested data structures and columnar analytics patterns alongside Xumo's streaming event schemas and CTV measurement frameworks.
Redbird's AI maps Xumo's viewership events, ad impression logs, and content metadata to BigQuery's table structures automatically. It recognizes user identifiers across systems, normalizes timestamp formats between streaming events and warehouse partitions, handles nested JSON from Xumo's API responses, and understands dimensional modeling patterns for CTV analytics. No custom schema translation or field mapping configurations required.
faster CTV data integration than custom API connectors and manual BigQuery loads
Redbird can pull from BigQuery and Xumo simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either BigQuery or Xumo.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from BigQuery into Xumo, or from Xumo back into BigQuery. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automations from any BigQuery query result or Xumo streaming event — Redbird handles the rest.
Trigger workflows when scheduled BigQuery queries detect new audience segments, performance thresholds, or content recommendations.
React to real-time data arriving in BigQuery tables from attribution systems, CDPs, or other streaming sources.
Start workflows when BigQuery ML models finish scoring audiences, forecasting viewership, or detecting content anomalies.
Execute BigQuery SQL with dynamic filters and parameters based on Xumo events or streaming platform data.
Write Xumo viewership metrics, ad performance data, or content metadata directly into BigQuery tables with proper schema mapping.
Refresh BigQuery materialized views containing aggregated Xumo metrics when new streaming data becomes available.
Trigger automations when new episodes, channels, or content libraries go live on Xumo's streaming platform.
Start workflows when content hits watch time thresholds, concurrent viewer peaks, or completion rate benchmarks.
React to shifts in CTV ad delivery, impression volume, or campaign pacing across Xumo's advertising inventory.
Modify titles, descriptions, tags, or promotional flags on Xumo content based on BigQuery performance analysis.
Configure ad targeting parameters or content recommendations using audience segments and propensity models from BigQuery.
Update content availability, scheduling, or categorization on Xumo based on inventory decisions modeled in BigQuery.
Join streaming analytics teams using Redbird AI to connect BigQuery and Xumo. Automate your CTV data pipeline and spend more time optimizing content performance, less time moving data between systems.