What is a Reverse ETL?

Traditional ETL (extract, transform, load) moves data from operational systems into a warehouse for analysis. Reverse ETL runs that flow in the opposite direction: once a data team has computed something valuable in the warehouse — a customer health score, a churn-risk flag, a lifetime-value estimate — reverse ETL syncs that computed field back into the CRM or support tool where a salesperson or support agent will actually see it, rather than leaving it stranded in a BI dashboard nobody in an operational role opens day to day. This closes a long-standing gap between analytics and action: a churn-risk model is only useful if the customer success rep sees the risk score attached to the account record they're already looking at, not if it lives in a separate reporting tool they'd have to remember to check. Reverse ETL tools handle the mapping, scheduling, and incremental syncing needed to keep that operational field fresh without a data engineer manually exporting and re-importing CSVs. It's a foundational piece of modern RevOps and personalization stacks, and it pairs naturally with automation: once a computed insight lands in an operational system, a workflow can trigger directly off it.