Databricks has introduced CustomerLake, an Agentic CDP built directly in the Databricks lakehouse to help marketing and data teams unify customer data, activate audiences, and personalize experiences without moving or duplicating sensitive data.
Whatโs new
- A CDP embedded in Databricks โ CustomerLake brings core CDP capabilities like Customer 360, identity resolution, audience building, activation, and personalization directly to the governed data foundation teams already use.
- Profile Agents for customer data readiness โ Profile Agents help teams prepare raw customer data, identify quality issues, and unify fragmented records into trusted customer profiles directly in Databricks.
- Campaign Agents for always-on engagement โ Campaign Agents help marketers build audiences, recommend next-best actions, activate across channels, and optimize around business goals using governed customer context.
- Built to reduce martech sprawl โ Databricks positions CustomerLake as a way to avoid extra data copies, separate activation layers, and disconnected CDP systems by keeping customer data, AI, and governance in one place.
- Open across the existing ecosystem โ CustomerLake is designed to work with existing martech and adtech tools, with federated access to trusted customer data across systems like Databricks, Snowflake, BigQuery, cloud object storage, and operational databases.
At the center of the launch is the idea of moving from static campaigns to more continuous, agent-driven engagement. Databricks describes this as Infinity Campaigns: always-on loops that analyze signals, decide the next best action, and adapt across audiences, offers, and channels.
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