CustomerLake Campaign Agents: Reverse ETL activation and measurement
CustomerLake Campaign Agents is under active development and in private preview. This page describes the direction of the Databricks partner integration model so activation, advertising, marketing, CRM, and analytics platforms can understand where they fit. The integration framework is still being defined, and nothing here is a finalized specification or a commitment to a particular interface, connector, mechanism, or timeline.
What CustomerLake Campaign Agents is
CustomerLake is Databricks' agentic customer data platform (CDP), embedded directly in the lakehouse. It spans two products: Profile Agents for Customer 360 and identity resolution, and Campaign Agents for segmentation, reverse ETL, and agentic personalization.
This page covers activation-focused integrations with Campaign Agents. Campaign Agents lets Databricks customers turn the governed Customer 360 gold layer into live audiences and sync them to tools such as ad platforms, marketing and messaging tools, CRM, and analytics. Partners can then share engagement data back into Databricks for closed-loop measurement.
Identity resolution, enrichment, and data hygiene happen upstream in Profile Agents, which produces the resolved golden records that Campaign Agents activates.
Where partners fit
Activation partners plug into Campaign Agents as:
- Reverse ETL destinations
- Sharing measurement and engagement data back to Databricks
Example destination categories:
| Destination category | Integrations |
|---|---|
| Advertising and demand-side platforms | Sync audiences and conversion events via conversion APIs to improve match rates, attribution, and campaign optimization. |
| Marketing, email, and messaging | Sync segments and attributes into ESPs and engagement tools to trigger lifecycle email, SMS, and push campaigns. |
| CRM and sales | Write audiences, scores, and account/contact attributes back into CRM for lead prioritization, territory routing, and account-based plays. |
| Analytics and product intelligence | Deliver cohorts and attributes into analytics and experimentation tools to close the loop on measurement, funnels, and feature exposure. |
| Support and customer success | Surface health scores, churn signals, and segment membership inside support and CS tooling so they can act on the same profile. |
Closed-loop measurement
In addition to activation, Databricks wants to capture what happened downstream and return it to the lakehouse, so Campaign Agents can measure performance, attribute outcomes, and let the next audience or decision react to real results. Reverse ETL partners should write outcome data back into Databricks.
Partners contribute to closed-loop measurement by returning one or more of the following signals, keyed off the audience and member identifiers Campaign Agents emitted:
| Signal type | What the partner shares | Example uses |
|---|---|---|
| Delivery and reach | Whether members were received, matched, and made addressable, plus match and onboarding rates. | Audience QA, match-rate monitoring, reconciling sync failures |
| Engagement | Impressions, opens, clicks, views, and other interaction events per member or campaign. | Frequency capping, engagement scoring, creative optimization |
| Conversion and outcomes | Purchases, sign-ups, and other outcome events tied back to activated audiences. | Attribution and LTV analysis |
| Cost and spend | Media spend, CPM/CPC, and pacing at campaign or audience granularity. | Efficiency reporting, budget pacing, blended CAC |
How integration works
Databricks is currently building managed reverse ETL connectors to destinations. In 2027, SDKs and partner-specific frameworks are planned so partners can build their own connectors.
Until then, implement Delta Sharing to share relevant engagement and measurement data back into Databricks.
What's next
- CustomerLake overview - both products and intake
- Profile Agents - identity, hygiene, and enrichment upstream of activation
- Delta Sharing - share measurement data back into Databricks