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.
—Kumar Ram, Global Head of Marketing Technology and AI Enablement, HP
AI is raising the stakes for marketing speed and relevance. 74% of consumersuse 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.
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.
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.
—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.
—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.
—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.
—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.
—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.
