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Tools & Platforms

Reverse ETL

Syncing data from your data warehouse back to operational tools like email platforms.

Definition

Reverse ETL moves data from your central data warehouse (Snowflake, BigQuery, Redshift) to operational tools like email platforms, CRMs, and ad networks. Traditional ETL pulls data into the warehouse. Reverse ETL pushes it back out to the tools that need it for targeting, personalization, and activation.

Why It Matters

Your data warehouse often contains the most complete and accurate customer data. It combines information from multiple sources that never reaches individual tools directly. Reverse ETL makes this rich warehouse data available for email personalization and segmentation without building custom integrations for each data source.

How It Works

Define which warehouse tables and columns should sync to which tools. A reverse ETL platform (Census, Hightouch, or similar) queries your warehouse on a schedule and pushes updates to destinations. Your email platform receives enriched customer data that would be difficult to assemble through direct integrations alone.

Best Practices

  • 1Start with the data that has highest impact on email personalization
  • 2Sync incrementally rather than full refreshes when possible
  • 3Set appropriate sync frequencies based on data freshness needs
  • 4Monitor for sync failures and data quality issues
  • 5Document what data flows where for team visibility
  • 6Avoid syncing unnecessary data that clutters destination tools
  • 7Test synced data accuracy in your email platform

API and Webhooks

Sync data to Sequenzy via API from any source including your data warehouse or reverse ETL tool.

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Frequently Asked Questions

A CDP collects, unifies, and activates data as a complete platform. Reverse ETL just moves data from warehouse to tools. If you already have a data warehouse with unified customer data, reverse ETL may be simpler than adding a CDP. If you need data collection and identity resolution, a CDP does more.

Customer lifetime value, product usage scores, subscription details, calculated health scores, and any metrics you compute in your warehouse that would improve email targeting. Focus on data that is hard to get through direct integrations.

It depends on use case. Daily syncs work for most email segmentation. Hourly or real-time syncs matter for time-sensitive triggers. Balance freshness needs against cost and complexity.