What will replace the traditional CDP in an agentic marketing stack?

Summary

• Databricks' answer is the agentic CDP. It defines one as a CDP that powers always-on 1:1 personalization with infinity campaigns, is embedded in the data foundation where governed customer context lives, and is built for agents as first-class operators alongside humans.
• CustomerLake is Databricks' version. It brings Customer 360, identity resolution, audience building, campaign automation, activation and personalization to data governed by Unity Catalog, with Profile Agents and Campaign Agents at its center.
• It is designed to work with existing martech. Databricks says CustomerLake does not necessarily replace existing martech tools, and it syncs audiences and signals to them.
• It is in Private Preview. Databricks announced it on June 16, 2026. Confirm availability with your Databricks account team.
• The framing is Databricks' own. The comparisons below come from Databricks launch materials and are attributed as such.

What will replace the traditional CDP in an agentic marketing stack?

We believe the successor is the agentic CDP: a customer data platform that lives inside the data platform and uses agents, with humans setting goals and guardrails, to build audiences and choose the next-best action. Databricks' founders argue that CDPs built for human-operated, batch-based campaigns were not designed for agents that research and buy on behalf of consumers. CustomerLake is the Databricks implementation. It was announced on June 16, 2026 and is in Private Preview.

What is an agentic CDP?

Databricks' CDP guide, citing Gartner, describes a customer data platform as software that supports marketing and customer experience use cases by unifying a company's customer data from marketing and other channels. It groups the work into data collection, data management and modeling, and data activation. Databricks also separates bundled CDPs from composable ones. Its product FAQ says bundled CDPs require copying customer data into a separate proprietary system, and composable CDPs reduce data movement but add another platform to manage.
In Databricks' definition, an agentic CDP has three traits. It powers agentic personalization through infinity campaigns, it is embedded in the data foundation, and it is built so that every function can be run by an agent or a human. Humans still set goals, review outcomes and stay in control.
Databricks' reasoning for embedding is that customer, business and decision context all live in the enterprise data platform, and agents need secure access to all three at once. It also argues that integrating with Unity Catalog means every agent action runs under the same data entitlements and security boundaries as other operations in the enterprise.

What are infinity campaigns and golden context?

Infinity campaigns are Databricks' term for continuous, agent-driven engagement loops that analyze customer signals, decide the next-best action and act across channels, based on real-time customer context and business goals. Databricks says agents need more than a Golden Record, which is a unified customer profile. They need Golden Context, which adds what the business is trying to accomplish right now and what has already been tried with this customer and how they responded.

How does the agentic CDP compare with the traditional pattern?

Dimension	Traditional CDP, as Databricks describes it	CustomerLake (Private Preview)
Where customer data lives	Sits outside the company's core data and AI platform.	Embedded in Databricks, so CDP capabilities run where governed customer data already lives.
Customer profiles	Many commercial CDPs include identity resolution and tools for custom traits on profiles.	Profile Agents build Customer 360 profiles, and Agentic Identity Resolution combines deterministic, probabilistic and agentic matching.
Campaigns	A series of manual steps: define an objective, request data, build a segment, validate the audience, create a journey, launch and measure.	Marketers set a goal, and Campaign Agents help identify the audience, recommend the next-best offer or channel, activate, and optimize or suppress on performance signals.
Activation	Pre-built integrations push audiences to and from marketing channels.	Managed reverse ETL connectors sync audiences and signals to martech, adtech and customer experience tools.
Governance	Another system to integrate, govern and reconcile.	Governed through Unity Catalog, with access, lineage and auditability across customer data, audiences and AI assets.

What does CustomerLake include?

• Profile Agents and Agentic Identity Resolution for Customer 360 profiles, with LLM and human review for edge cases.
• Campaign Agents for audiences, next-best actions and activation across channels.
• A real-time profile API, a serving layer for customer attributes.
• Third-party identity and data enrichment, built into the platform.
• Genie, so marketers can ask questions and build segments in natural language.
• Unity Catalog and Lakeflow for governance and for ingesting customer, campaign and engagement data.

FAQs

Does CustomerLake replace my existing martech tools?

Not necessarily, according to Databricks. It describes CustomerLake as open and composable, designed to work with the marketing, advertising, analytics and customer experience tools teams already use.

Does CustomerLake copy my customer data?

Databricks says no. CustomerLake is embedded in Databricks, so CDP capabilities run where your customer data already lives, and Lakehouse Federation reaches data held in other systems.

How is CustomerLake priced?

At launch, Databricks said pricing would follow a consumption model rather than a traditional software license. Ask your Databricks account team for current terms.

Will agents decide everything on their own?

No. The launch blog says humans define the strategy, goals and guardrails, and agents help scale execution.

Is CustomerLake generally available?

Databricks announced it in Private Preview on June 16, 2026. Ask your account team for its current status.