CustomerLake enters Beta: Leading enterprises going live with the Agentic CDP

CustomerLake enters Beta: Leading enterprises going live with the Agentic CDP | Databricks Blog

Skip to main content

Marketing

October 19, 2026

CustomerLake enters Beta: Leading enterprises going live with the Agentic CDP

A 10 point lift in conversion rates, 90% faster audience builds, and 40% reduction in CDP costs: Early CustomerLake results show what’s possible when Databricks is your Agentic CDP.

by Tasso Argyros , Katy Yuan , Cindy Jiang and Phil Catterall

Summary

• CustomerLake expands access with Campaign Agents Beta and Profile Agents Private Preview: The Agentic CDP embeds audience building, activation, personalization, and Customer 360 capabilities in the governed Databricks Data + AI platform.

• Customers are demonstrating faster execution and cost savings: Reducing audience turnaround time by 90%, becoming audience-ready in 2 hours versus 2–3 months, a potential 40% reduction in CDP total cost of ownership, and a 10-point lift in conversion rates

• A new operating model for agentic marketing: CustomerLake unites marketing activation, trusted context, and AI agents in Databricks to personalize engagement safely and effectively at scale.

Today, we’re excited to share a major CustomerLake milestone: Campaign Agents is advancing to Beta and Profile Agents is entering Private Preview. This marks the next stage of product maturity for the Agentic CDP embedded in Databricks, and expands participation to more customers.

When we introduced CustomerLake at Data + AI Summit , we outlined a new operating model for marketing: embed your CDP into the governed data and AI platform where your most complete customer context already lives.

Since then, brands like Getnet by Santander, HP, and AB InBev have been using CustomerLake to understand their audiences more deeply and give marketers greater freedom to deliver more tailored campaigns and better customer experiences.

Within 2 hours of starting with CustomerLake, we had models and attributes ready for audience building, versus 2 to 3 months with a traditional CDP. Using our Marketing Lakehouse offers the potential to reduce CDP total cost of ownership by 40%. —Kumar Ram, Global Head of Marketing Technology and AI Enablement, HP

AI is raising the stakes for marketing speed and relevance. 74% of consumers use AI to discover, compare, or purchase products. As agents take on more of the buying journey at machine speed, marketers need agents of their own to recognize changing intent and respond in real time. Databricks is where enterprise data, AI models, and governance already come together, giving CustomerLake agents the trusted context to act.

Expand

Powered by Genie, CustomerLake empowers marketers to build audiences in natural language using trusted customer data already in Databricks.

The customer stories below show CustomerLake’s three core principles in action: Embedded, Democratized, and Autonomous .

Embedded: Built on the Marketing Lakehouse you already trust

Hyper-personalized campaigns are only possible with a complete and consistent view of the customer. Enterprises already invest in Databricks to define their data, maintain quality, and govern how it’s used. CustomerLake makes that work available to marketers, reducing the need to recreate customer context in another platform.

For HP , using their Marketing Lakehouse foundation has accelerated audience turnaround while reducing martech cost of ownership.

Within 2 hours of starting with CustomerLake, we had data and attributes ready for audience building — versus 2 to 3 months with a traditional CDP. CustomerLake works directly with the schemas, governance, and data models we already have in Databricks, offering the potential to reduce our CDP total cost of ownership by 40%. That’s why we're making CustomerLake central to our AI-ready marketing data strategy. —Kumar Ram, Global Head of Marketing Technology and AI Enablement, HP

Read more about how HP is building an AI-ready CDP with Databricks CustomerLake .

Getnet by Santander is connecting transactional, behavioral, and predictive intelligence so commercial, CRM, and marketing teams can work from a complete view of the customer.

CustomerLake gives Getnet our first unified Customer 360, combining transactions, interactions, behavior, and predictive models like churn propensity score. Our commercial, CRM, and marketing teams can explore insights and create audiences in natural language, replacing weeks of manual data extraction. Following our Mexico rollout, we plan to expand across Latin America and Europe. —Ainhoa Alonso, Chief Data and AI Officer, Getnet by Santander

Democratized: Giving marketers direct access to customer intelligence

Customer intelligence is most valuable in the hands of the people closest to the customer. CustomerLake gives those teams the freedom to explore customer context and immediately act on what they learn.

Zé Delivery, part of AB InBev , is enabling greater ownership of live campaigns for its CRM team without dependence on data engineering.

Our CRM team now builds audiences in CustomerLake and syncs them directly to Braze without engineering support, shifting from data dependence to true marketing self-service. We’re expanding access to CustomerLake and Genie across our CRM and growth teams, giving more marketers the independence to turn customer insights into personalized experiences for millions of consumers across Brazil. —Bruno Smarsaro Bazelato, Director of Data and Analytics, Zé Delivery (AB InBev)

CustomerLake makes enterprise data that was previously difficult to bring into marketing tools directly available for audience building and activation, through the engagement platforms marketing teams already use.

Autonomous: Scaling personalized engagement with agents

A growing customer base shouldn’t mean more generic marketing. CustomerLake’s agentic approach helps marketers use richer customer context to make personalization more targeted as audiences grow, without multiplying the manual work behind each campaign.

For Wine.com , that means turning a vast catalog and diverse customer tastes into opportunities for more relevant, precisely targeted campaigns.

We launched production email campaigns with CustomerLake just 23 days after kickoff, and have since scaled to 100 active audiences syncing daily to Braze. Across 6.5 million profiles and thousands of wines, the ability to target customers on purchase behavior, varietal preferences, and engagement patterns has fundamentally changed our personalization. What used to be a multi-team, multi-day manual process is now something our marketing team can do on their own, every day. —Billy Galanko, Director Marketing Content & Strategy, and Eric Wallace, Lead Data Engineer, Wine.com

Philadelphia Union’s ambition is to turn a surge of interest from the FIFA World Cup into a lasting relationship with each individual fan.

Replacing our previous CDP with CustomerLake cut our audience turnaround time by 90%, and its Genie-powered tools have eliminated much of the manual work our previous platform required. We're now building audiences directly on our Databricks data and running hundreds of audience syncs each month to Salesforce Marketing Cloud. With the World Cup driving heightened interest in Major League Soccer, that speed helps us deliver more relevant communications and build lasting fan loyalty. —Kyle Mathiot, SVP Technology & Analytics, Philadelphia Union

Databricks on Databricks: Personalizing Summit recommendations for 30,000 attendees with Infinity Campaigns

We’re putting CustomerLake to work in our own marketing, too. For Data + AI Summit, we used CustomerLake to personalize session recommendations for 30,000 in-person attendees. Campaign Agents evaluated each person’s engagement history to craft an email reflecting the recipient’s interests and behavior, helping attendees discover the sessions most relevant to them.

The campaign delivered a 10 point conversion lift against a control group, a 10% click-through rate and a 60% open rate , outperforming every previous Summit email campaign. It shows how trusted customer context can inform both who to engage and what to recommend.

Campaign Agents Beta: Expanding agentic campaigns to more customers

Campaign Agents is now in Beta, opening participation to more customers who meet the technical requirements.

As participation expands, delivery partner Stitch has seen how CustomerLake can accelerate the path to marketing self-service across its client base.

CustomerLake enabled an enterprise media brand to deliver marketer self-service segmentation in days versus months with a traditional CDP. The team built on its existing Databricks data foundation, without recreating data integrity and governance work in another platform. —Bobby Tichy, Chief Solution Officer, Stitch

The results above show meaningful progress: faster audience turnaround, greater marketer independence, and personalized recommendations at scale. These are the building blocks for CustomerLake’s broader vision of Infinity Campaigns : continuous, agent-driven engagement loops that analyze customer signals, determine relevant actions, and adapt as customer context changes.

Each step gives marketers more room to shape the customer experience and less time coordinating the mechanics behind it. People set the strategy, goals, and guardrails; agents help scale execution.

Profile Agents Private Preview: Build and use Customer360 profiles directly in Databricks

Profile Agents, entering Private Preview today, helps data teams unify scattered customer information from dozens of sources into trusted Customer 360 profiles directly in Databricks, giving marketers a consistent customer view for better segmentation and personalization.

Its capabilities address three connected tasks:

• Source normalization: Field mapping and semantic normalization bring source data from different sources into a consistent structure and meaning for downstream use.

• Agentic Identity Resolution: Deterministic, probabilistic, and LLM-based matching help connect fragmented records. Golden record survivorship determines which attributes to retain in the unified profile.

• Stateful, incremental processing: Micro-batch updates keep profiles current as data changes, while manual data steward overrides allow teams to apply human judgment where needed.

Profile Agents and Campaign Agents can be adopted independently. Teams can start with campaign workflows using their existing customer data or use Profile Agents to improve how they prepare and unify customer records.

Your best CDP is Databricks

AI in marketing can only work safely and effectively at scale when agents have governed access to trusted customer data, models, and business context. CustomerLake brings these together in Databricks, giving agents the intelligence and guardrails to make relevant decisions that achieve business goals.

Customers are already demonstrating what this new operating model for agentic marketing can deliver. Now, more organizations can put their Databricks investments to work for customer engagement.

To get access to CustomerLake, contact your Databricks account team.

Get the latest posts in your inbox

Subscribe to our blog and get the latest posts delivered to your inbox.

Sign up

View all blogs

slice-start id="_gatsby-scripts-1"

slice-end id="_gatsby-scripts-1"