What is Reverse ETL?
The process of syncing data from a data warehouse back into operational business tools like CRMs and marketing platforms.
Definition
Reverse ETL flips the traditional data pipeline. Instead of pulling data from business tools into a warehouse for analysis, it pushes modeled data back out to the tools where teams actually work. Think of it as the last mile of the modern data stack. Your analytics team builds models in dbt or Looker, and reverse ETL makes those models actionable in Salesforce, HubSpot, Marketo, or wherever your go-to-market team operates.
Why It Matters
Most companies have better data in their warehouse than in their CRM. Lead scores, health scores, product usage metrics, and segmentation models sit in BigQuery or Snowflake where sales reps can't see them. Reverse ETL closes that gap. It means the data team's work actually reaches the people making decisions, without building custom integrations for every tool.
Example
Your data team builds a product-qualified lead score in Snowflake using signup data, feature usage, and billing info. Census syncs that score to a custom field in Salesforce every hour. Reps can now sort their pipeline by PQL score and prioritize accounts showing real buying signals instead of guessing.