Sync customer support data into your warehouse and enrich Intercom with insights from BigQuery. Stop manually exporting conversation data, copying user attributes between systems, or running support analytics in spreadsheets.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically capture all customer conversations, tags, ratings, and resolution data from Intercom into BigQuery. Build comprehensive support analytics dashboards that join conversation data with product usage, revenue, and customer health metrics stored in your warehouse.
Push customer lifetime value, product engagement scores, churn risk predictions, and usage patterns from BigQuery into Intercom user attributes. Enable support teams to see critical context without switching to analytics tools, personalizing responses based on customer value and behavior.
Trigger notifications in Slack or Intercom when customers matching BigQuery segments—like enterprise accounts, at-risk users, or recent high spenders—initiate support conversations. Route priority tickets automatically based on data warehouse insights about customer importance.
Automatically run SQL queries on synced Intercom data to calculate team performance, CSAT trends, first response times, and resolution rates. Publish results to dashboards or send summaries to leadership without manual data pulls or BI tool configuration.
Sync user cohorts defined in BigQuery—like recent converters, trial users nearing expiration, or power users—into Intercom tags or segments. Trigger targeted in-app messages and support workflows based on data warehouse logic that combines product, revenue, and behavioral data.
Capture full conversation history, including message content, timestamps, and agent actions, into BigQuery for long-term storage and analysis. Enable compliance reporting, support quality audits, and AI training dataset creation from historical support interactions.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and Intercom 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 AI understands BigQuery table schemas and Intercom's customer data model, automatically mapping conversations, user attributes, tags, and events between your warehouse and support platform.
Redbird automatically recognizes Intercom objects like conversations, users, companies, tags, and events, mapping them to BigQuery tables with appropriate schemas and partitioning. The AI handles nested JSON from Intercom's API responses, flattens conversation metadata into queryable columns, and generates SQL that joins support data with your existing warehouse tables. When pushing data to Intercom, Redbird validates attribute types, handles batch updates efficiently, and ensures user identifiers match across systems.
faster than building custom ETL scripts and Intercom API integrations
Redbird can pull from BigQuery and Intercom 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 Intercom.
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 Intercom, or from Intercom 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 workflows from BigQuery query results or Intercom support events, then take action across both platforms automatically.
Trigger workflows when a BigQuery scheduled query identifies new records, changes in customer segments, or threshold breaches in support metrics.
Detect when new customer data, events, or calculated attributes are inserted into specific BigQuery tables or partitions.
Monitor when BigQuery table schemas are modified, new columns are added, or data types change in warehouse tables.
Write conversation data, support metrics, or enriched customer attributes from Intercom into BigQuery tables with proper schema mapping.
Execute custom SQL queries to analyze support data, calculate customer metrics, or generate segments for Intercom sync.
Upsert Intercom data into BigQuery tables, updating existing records and inserting new ones based on user or conversation identifiers.
Trigger workflows when customers initiate new support conversations via chat, email, or in-app messaging.
Detect when support tickets are marked as closed, capturing resolution data, final ratings, and conversation metadata.
Monitor changes to Intercom user profiles, including custom attributes, company associations, or tag assignments.
Push customer scores, segments, or behavioral data from BigQuery into Intercom user or company profiles for support team context.
Automatically tag Intercom users or conversations based on BigQuery analysis, such as high-value status or churn risk indicators.
Sync new customers or updated profile information from BigQuery into Intercom, ensuring support platform reflects warehouse truth.
Sync BigQuery with Intercom in minutes and stop manually managing customer data between your warehouse and support platform. Build workflows that keep your teams working from a single source of truth.