Redbird AI syncs customer event data and warehouse insights between BigQuery and Segment automatically. Stop exporting CSV files, writing custom ETL scripts, or manually copying audience segments between your data warehouse and customer data platform.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically send computed audience segments from BigQuery—built from ML models or SQL queries—into Segment as traits and computed traits. Push high-value cohorts, churn risk scores, or LTV segments to every connected marketing and analytics tool without engineering work.
Append predictive scores, lifetime metrics, and historical aggregations from BigQuery directly onto user profiles in Segment. Surface propensity models, product affinity scores, and cross-channel behavior patterns for real-time personalization across your stack.
Capture incoming Segment events—track calls, identify calls, page views—and write them to BigQuery tables with proper schema mapping. Eliminate Segment warehouse connector delays and get fresh customer data into your analytical layer instantly.
Run data quality rules on Segment event tables in BigQuery and trigger alerts when thresholds break. Catch tracking gaps, schema drift, or event volume anomalies before they cascade into downstream reporting and activation issues.
Automatically move aged Segment raw event data from BigQuery active tables to Cloud Storage after retention periods. Reduce warehouse costs while maintaining compliance and audit trails for historical customer interactions.
Replicate Segment's cleaned and conformed data models from the Segment warehouse connector into BigQuery tables. Build unified customer analytics on top of both raw and normalized event streams without maintaining dual pipelines.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and Segment 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 table schemas and Segment's event spec, so your customer data warehouse and CDP stay in sync without brittle mappings.
Redbird's AI reads your BigQuery table structures—user dimensions, event fact tables, ML model outputs—and maps them to Segment's track, identify, and group calls with the correct event properties and traits. It handles schema evolution on both sides, transforms nested BigQuery structs into flat Segment properties, and validates events against your tracking plan automatically. No manual field mapping, no custom transformation scripts.
faster than building custom BigQuery-to-Segment pipelines with Cloud Functions or Airflow
Redbird can pull from BigQuery and Segment 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 Segment.
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 Segment, or from Segment 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 BigQuery query results, table updates, or Segment event streams, then take action in either system.
Trigger when a BigQuery scheduled query finishes running, with access to result row counts and execution metadata.
Detect when new records appear in a BigQuery table or materialized view, ideal for audience or metric updates.
Run a SQL query on a schedule and trigger when results meet conditions—row counts, aggregates, or specific values.
Execute a SQL query in BigQuery with dynamic parameters from upstream workflow data.
Write structured data into a BigQuery table with automatic schema matching and type conversion.
Run a SQL transformation and merge results into an existing BigQuery table using UPDATE or MERGE logic.
Trigger when Segment receives a specific track event name from any source, with full event properties.
Detect when an identify call creates or updates a user profile with new traits or attribute changes.
Fire when users enter or exit a Segment Audience, enabling immediate downstream activation or analysis.
Post a track call to Segment with custom event names and properties, routed to all enabled destinations.
Send an identify call to add or modify user profile traits in Segment, syncing to all connected tools.
Programmatically update Segment Audience membership by sending trait or event data that matches audience criteria.
Sync BigQuery and Segment in minutes, not sprints. Redbird AI handles the schema mapping, transformation logic, and ongoing maintenance so your data and growth teams can focus on insights and activation.