At Zooplus, Europe’s leading online pet platform, Pallavi is responsible for customer acquisition, retention, and AI-driven product platforms. Speaking at our DACH User Group Event in Cologne, she shared a powerful story about turning customer obsession into operational strategy, and why technology alone is never enough.

A Clear Mission: From Tools to Transformation

In mid-2023, Zooplus set out on a mission to become a truly customer-centric organization. This involved rebranding, redesigning their digital presence, and most importantly, using technology to better serve customers. A cornerstone of this transformation was the implementation of a Customer Data Platform (CDP), with a clearly defined 2024 goal: enable marketing automation across 30 markets to reduce time to market, improve cost efficiency, and create a unified customer profile.

But as Pallavi points out, buying software isn’t the same as using it well. Only 17% of businesses say their CDP drives measurable business impact. The key, she argues, is building the culture and processes around the tech to unlock its real value.

Building from the Ground Up: Cross-Team Orchestration

The Zooplus team didn’t just roll out a CDP and hope for the best. They created a new team, defined top 10 use cases to focus on, and launched high-impact initiatives like automated newsletter redesigns and trigger-based campaigns. As they scaled, they encountered common challenges:

• Local vs. central control: Automation required rethinking local workflows.
• North Star alignment: Was the goal revenue impact, cost savings, or speed?
• Data silos: How do CDP and data lakes co-exist?

The solution was to reframe the entire initiative not as isolated use case implementation, but as customer journey orchestration. This subtle shift had big implications: focus on journeys, not just campaigns. Look at customer lifetime value, not just click-throughs. And ensure teams are aligned not around tools, but outcomes.

From Use Cases to Unified Experiences

Pallavi emphasized the danger of thinking in disconnected touch points. A classic example: abandoned cart emails. If a customer left because their payment failed or shipping wasn’t available, a 15% discount email won’t help. What they need is relevance, context, and empathy.

This understanding led to practical changes at Zooplus:

• Implementing tools like Qualtrics to bring customer feedback into strategy decisions.
• Auditing end-to-end workflows across marketing, UX, and CRM.
• Facilitating cross-functional workshops to foster alignment.

As she put it, “Buying SaaS is not equal to using SaaS. The human part is the extreme sport.”

Creating a Cultural Shift

The real transformation at Zooplus was cultural. Teams began speaking the language of the customer. Personas, intent, and behavior became the pillars of journey design. Instead of chasing campaign metrics, the company began optimizing around customer value and experience quality.

They mapped entire journeys, from discovery to retention, and used these to prioritize capabilities. Not every use case had to be fully personalized (Level 4, as Pallavi called it, à la TikTok), but each had to fit Zooplus’ goals and maturity level.

Their guiding principle? Don’t build technology for technology’s sake. Build it to deliver customer experience.

Final Takeaway

In Pallavi’s words: “The customer is looking for very simple things: trust, relevance, understanding, and value. If we solve these, the sales and revenue will follow.”

It’s a reminder that the most sophisticated data strategies are grounded in simplicity and empathy. And that real innovation lies not in the tools we buy, but in how we use them to serve the people who matter most: our customers. 

You can find and watch the full session here.

Hopefully this session helps you to start thinking of Customer Experience based on leveraging technology rather than building technology to build Customer Experience.                             – Pallavi Modi

The post Building Customer-Centric Data Strategies: Lessons from Zooplus’ Pallavi Modi appeared first on Tealium.

In this podcast, you’ll discover how PostNL evolved from siloed data to delivering personalized B2B experiences at scale.

Key takeaways to listen out for:

• Unique dual-profile CDP architecture – How PostNL manages both company-level and individual visitor data simultaneously for complex B2B relationships
• Four practical use case categories – Real examples spanning marketing, sales, operations, and customer support that you can apply to your own business
• Overcoming data silos – The specific challenges PostNL faced with their legacy data warehouse and how they solved scalability issues
• B2B personalization at scale – Technical insights into their architecture, data flows, and integration with Salesforce Marketing Cloud
• Future roadmap reveals – Their plans for leveraging Tealium’s Moments API, conversational AI, omni-channel expansion, and machine learning integration
• Data volume management strategies – How they handle 100,000+ daily events without performance issues

Listen now ↓

This case study offers actionable insights for any organization looking to break down data silos and implement CDP technology for customer experience transformation.

We used AI to generate this podcast. It summarizes a presentation delivered at Tealium’s Benelux User Group in Amsterdam, June 2025, by Arjen Aggenbach (Omnichannel Manager, PostNL) and Anna Rijntjes (Snr. Customer Success Manager, Tealium).

The post PostNL and Tealium CDP: From Data Silos to Personalized B2B Experiences appeared first on Tealium.

Challenge

As Tealium prepared for its global 2025 Digital Velocity events, the goal was to deliver more than just a conference app—it needed to be a living demonstration of what’s possible with the Tealium ecosystem. The team set out to showcase real-time personalization, AI-driven recommendations, post-event engagement, and seamless integrations with partner technologies, all in a mobile-first experience. Beyond a single event, this would act as a blueprint for how brands could activate Tealium’s capabilities across the full customer journey.

The post Case Study: Powering Real-Time Engagement at Scale appeared first on Tealium.

The OMR Festival 2025, one of Europe’s biggest digital marketing events, brought together over 67,000 marketing pros for two days packed with inspiration, innovation, and just the right amount of nerdiness.

And speaking of nerds, our Big Data Theory masterclass brought Sheldon-level precision to the OMR stage. Tealium’s Ulisse Sarmiento teamed up with Vodafone’s Jeroen Jaspar and Nico Glibber to reveal how Vodafone is using smart data, real-time orchestration, and AI to cut through complexity, overcome privacy challenges, and drive real business impact, like breaking down data silos and boosting conversion rates.

#1 What Is The Formula To Achieve Amazing Results (AR) With Your Customer Data?

A question not only Sheldon should ask but any digital marketer who wants to stay ahead of the curve. 

The session introduced a powerful framework:
RT*(1PD + 0PD)AI = AR, which means Real-Time Data *(First-Party Data + Zero-Party Data)AI = Amazing Results.

Now, if you really want to crack the code behind amazing results (AR), first you need to get a grip on the four key types of customer data and how to actually activate them in real-time. These four data types are zero-party data, first-party data, second-party data and third-party data.

The equation also underpins Vodafone’s strategy to build rich, privacy-first customer profiles, and enable AI models that deliver timely, relevant customer experiences.

#2 The Vodafone Formula: Capabilities, Structure, And The Right Team For CDP Success

Success didn’t happen overnight. Before implementing a Customer Data Platform (CDP), Vodafone identified four core capabilities where a CDP would serve as a central enabler: paid media personalisation, owned media personalisation, prospect targeting, and machine learning.

To keep existing customers engaged and satisfied, they prioritised tailored experiences across both paid and owned channels. At the same time, building smarter prospect journeys and developing in-house machine learning models allowed Vodafone to maintain full control and retain valuable expertise.

These four essential components were then defined for the operation of Vodafone’s CDP.

• A cross-functional team: Assembling a cross-functional, embedded CDP team to capture ideas for new use and business cases. 
• An operating model: Integrating the CDP into existing systems (no parallel tech stacks) 
• Implemented SteerCos: So that senior management roles ensure funding, guidance and decision making
• Evangelism: Using evangelism internally with tracked results and clear wins, an easy to understand communication about the complex topic of a CDP

#3 How To Break Down Data Silos And Implement Personalisation At Scale

One of Vodafone’s amazing results is that with a CDP they were finally able to break down data silos. Anyone who’s been working in marketing for a long time knows that marketing tools often still operate in silos, making it difficult to get the data to the rest of the company. 

Vodafone explains how with a CDP as the heart of their martech brings together their clickstream data from their web and app for example, and distributes it to all their other channels. Vodafone’s data scientists work directly within platforms like Google Cloud and AWS. Instead of pulling the data into digital tools, they bring digital data to where the richest data already lives, inside their enterprise systems. For a company like Vodafone, this approach has been key to unlocking some truly impressive results. Based on that, they developed a number of use cases. Let’s dive into them.

• Use Case 1: Personalisation at Scale
  One of Vodafone’s first CDP campaigns centred around a personalised availability check on their website. Using the CDP, they captured real-time visitor data, built audiences based on 360 customer profiles, and fed those insights back into their targeting engine to display tailored banners. The result? A 10–30% uplift in conversions compared to a control group that didn’t receive personalisation, proving the value of smart, timely re-engagement. Want to see how it works in real time? Watch the full masterclass to catch their demo and experience the use case in action, powered by real-time customer behaviour.
• Use Case 2: CDP Returnfeed
  Another impactful use case Vodafone implemented is the CDP return feed for existing customers. By sending cart abandonment data, including a deep link to the product page, back into their decision engine, Vodafone triggers a personalised follow-up email 24 hours later. This seamless handoff between the website, CDP, and campaign engine allows customers to return directly to their shopping cart and complete the purchase. The result? A clear win for smart, timely re-engagement—proving just how powerful the right message at the right moment can be.
• Use Case 3: Propensity-to-Buy Models
  Vodafone’s third and most advanced use case leverages machine learning to predict which users are most likely to convert, enabling smarter, more focused engagement across channels. To support this, Vodafone’s in-house data scientists built a propensity-to-buy model using a random forest algorithm within their own infrastructure. The goal: predict with confidence when a user is likely to make a purchase within the next hour. After training the model on a wide range of behavioural data (such as product page visits, cart activity, and service-related browsing patterns), they defined a score—67% likelihood of conversion—as the internal benchmark for high purchase intent. While this number is specific to Vodafone’s business model and data structure, the results have been remarkable. One standout application of this model is in Vodafone’s omnichannel sales experience. When high-intent users browse the website, they’re shown a personalised hotline number, allowing them to connect directly with a telesales advisor if they prefer not to complete the purchase online. Now, Vodafone uses the propensity score to prioritise calls in the telesales queue, essentially creating a “fast lane” for customers most likely to buy, similar to VIP boarding at an airport.
  
  This approach led to a more than 50% increase in conversions among high-propensity users calling the hotline. It also helped sales teams focus their time on actual purchase opportunities, rather than handling low-intent service queries. The key takeaway? With the right data signals, AI models, and orchestration, Vodafone turned predictive intelligence into measurable sales impact, and this is only the beginning. The same model can now be adapted for countless other use cases across their customer journey.

#4 Use Data To Fuel AI – Not The Other Way Around

Before you unleash AI magic, you’ll need more than just good intentions – you need clean, connected, AI-ready data. The real blocker to AI success? It’s not the algorithm… it’s your messy data. Our nerds-in-chief from Vodafone and Tealium broke it down – smart data foundations, real-time orchestration, and how to stop your AI dreams from crashing on bad data.One key takeaway from Vodafone: keep AI and machine learning efforts in-house to retain control and build lasting expertise. Want to see how they’re doing it?

Watch the full episode of The Big Data Theory masterclass and get inspired to level up your own data strategy:
Watch now

#5 A Tool Is Only As Powerful As The Team Using It

“A fool with a tool is still a fool,” joked Jeroen Jaspar, highlighting that the real power of a CDP lies in the people behind it. At Vodafone, building the right cross-functional team was essential, starting with IT and development roles to get the infrastructure right, and later expanding to operational roles like CDP Operators.

Just like Leonard bridges Sheldon’s logic with Penny’s spontaneity, Vodafone’s team acts as the bridge between technical complexity and real-world marketing outcomes, bringing structure, communication, and collaboration to the heart of data orchestration.

As marketers and organisations, we’re facing no shortage of challenges, rising ad costs, economic uncertainty, fragmented customer journeys, and messy data aren’t going anywhere. The key isn’t to fear the complexity, but to prepare for it, and keep learning from those who are already turning theory into impact.

That’s exactly what Vodafone shared in the Big Data Theory masterclass at OMR. From structuring teams to building AI-ready data foundations, their learnings offer a real-world playbook for tackling today’s challenges head-on.

Want to see how your team can put these principles into practice?
Watch the full masterclass, plus a Q&A packed with practical insights, and start unlocking the full value of your customer data.

The post How Vodafone Uses Smart Data and AI to Boost Conversions – 5 Key Lessons from OMR 2025 appeared first on Tealium.

Let’s dive straight in.

In this 6-minute podcast, you’ll discover how TUI is embracing AI to transform travel – from dynamic pricing and personalized couponing, to empowering employees and enhancing customer service with generative AI tools.

Hear how AI is being harnessed across the TUI ecosystem to:

• Assist agents
• Improve search
• Create tailored journeys
• Drive efficiency
• Empower innovation
• Nurture loyalty

We used AI to generate this podcast. It summarizes a presentation delivered at AWS Summit Stockholm in June 2025 by André Exner (Group IT Director – AI, Analytics & Innovation at TUI Group) and Richard Marsh (RVP Sales – Europe International, Tealium).

Listen now ↓

Want to hear more about TUI’s data strategy for AI, innovation, and growth?

Check out the on-demand recording of TUI’s keynote at our conference in London.

Session: Unveiling the Future: Data Differentiation & Innovation in the Era of AI

Speakers: André Exner (Group IT Director, TUI), Jeff Lunsford (CEO, Tealium) and Mike Anderson (CTO, Tealium).

Watch TUI’s session here →

The post TUI Group Leverages AI to Transform Travel appeared first on Tealium.

Here are a few takeaways from the event:

#1 AI is Moving at Lightning Speed (With Mixed Results)

Remember when we were all trying to figure out what ChatGPT was? That feels like ancient history now. Generative AI tools have become part of our daily routine, both at work and at home. The adoption rate has been faster than any tech wave we’ve seen before.

Is this rapid adoption a good thing? The answer is complicated.

On the positive side, AI is incredible at streamlining those tedious, time-consuming tasks we all dread. It’s revolutionizing how we conduct research, analyze data, and create content. Take our friends at Jasper, for example, they offer a suite of AI apps that help marketers build go-to-market assets like campaign briefs, messaging guides, ad copy, and blog posts. Tools like Jasper and others featured at the symposium are designed to eliminate the grunt work, freeing up marketers to focus on what really matters: strategic thinking and creative problem-solving.

But here’s where things get unsettling. AI has a darker, borderline-dystopian side. We’re seeing deepfakes, widespread disinformation, sophisticated cyber attacks, and a concerning trend toward over-reliance that’s eroding our critical thinking skills. During Rahaf Harfoush’s keynote, she showed a clip of Miquela, an AI-generated social media influencer promoting a rehydration powder “for the glow, yeah?” It was both fascinating and deeply unsettling.

For better or worse, AI is here to stay. 88% of business leaders now see AI, data science, or digital commerce as critical for achieving growth.

#2 Agentic AI is Going to be Everywhere

Agentic AI refers to autonomous AI systems that can make decisions and pursue complex goals with minimal supervision. Unlike generative AI, which is reactive to user prompts, agentic AI proactively adapts to changing situations and makes contextual decisions. Using technologies like natural language processing, machine learning, and reinforcement learning, it operates independently in applications such as robotics or virtual assistants.

Agentic AI is now being deployed in several ways to transform customer experiences and improve marketing productivity. Think of some of the things marketers are asked to do:

• Build awareness and generate pipeline: Agents can assist with campaign planning and creation
• Grow customer lifetime value: Agents can autonomously recommend next best action, offer, or product.
• Bring a new product to market: Agents can help by autonomously generating messaging and positioning briefs, collateral, and sales enablement content.

Many of the exhibitors were demonstrating some very cool agentic AI tools for marketers. This next wave of AI will undoubtedly create even more productivity gains for marketers.

#3 It’s Still All About the Data

Nicole Greene, one of Gartner’s AI experts, presented a session entitled “How to Develop an AI Strategy for Marketing.” In the session, she outlined the progression of AI value over the next 5 years

• AI as a Tool – Using AI to reduce the burden of manual tasks. (today)
• AI as an Agent – Using AI to support the delivery of better customer experiences. (18-36 months)
• AI as an Influencer – Enabling AI to make decisions more autonomously, requiring less human oversight. (3-5 years)

In each phase, she stressed the importance of having your data house in order. Feeding high-quality data into your AI models has the following benefits.

• Performance: Dirty data creates unreliable, inaccurate AI systems that make poor decisions.
• Legal Compliance: Data protection laws like GDPR require explicit consent for using personal data in AI training, with severe penalties for violations.
• Trust: Proper consent builds public confidence in AI systems by respecting privacy and individual autonomy.

This is why solutions like Tealium’s AIStream are critical for feeding clean, consented data into AI models to optimize their performance and value.

The Bottom Line: Embrace the Change, But Do It Right

The Gartner Marketing Symposium made one thing crystal clear: AI isn’t just transforming marketing—it’s fundamentally reshaping how we work, think, and connect with customers. From streamlining mundane tasks today to autonomous decision-making tomorrow, we’re witnessing the most significant shift in our industry’s history.

But here’s what separates the winners from the rest: it’s not about jumping on every AI trend or tool that emerges. Success comes down to building a solid foundation—clean data, clear strategy, and a commitment to doing AI right from the start. The marketers who invest in proper data infrastructure and thoughtful AI implementation today will be the ones reaping the biggest rewards as we move through Nicole Greene’s progression from AI as a tool to AI as an influencer.

The future of marketing is being written right now. The question isn’t whether you’ll use AI in your marketing—it’s whether you’ll be ready to harness its full potential when the next wave hits.

The post Gartner Marketing Symposium Recap appeared first on Tealium.

The Shift: From Storage-Centric to Cloud-Centric CDPs

The classic CDP model revolves around a central repository where customer data is ingested, unified, and stored. This approach makes sense if you believe real-time activation isn’t a competitive differentiator. Tealium never subscribed to this approach but more about that later. Today, consumers expect experiences that are not only personalized—but instantaneously relevant. Every delay, every missed signal is a missed opportunity.

At the same time, Data Clouds like Snowflake, AWS, and Databricks have become the new standard for enterprise-scale data management and AI. These platforms are infinitely scalable, accessible, and most importantly already house vast amounts of data and insights. Why duplicate all that into another storage solution?

The Rise of Data Hunger: Fueling the Data Cloud in Realtime

Shifting away from traditional storage based CDPs, the future is in real-time streaming customer data that has been consented, standardized and enriched with identity from every customer touchpoint.  Organizations are hungry not only for event level data but also the highly contextualized and labeled intelligence created through real-time enrichment. This gives the Data Cloud access to 3 essential data scopes in event, visit and visitor. Data wrangling slows down Data Cloud innovation, and with Tealium data is delivered at the highest possible fidelity at the point of engagement in a ready to use format.

The value of this newly realized asset is a massive improvement in overall Data Cloud cost and time to value.  Most importantly real-time means Agentic and ML initiatives get access to in the moment context needed for the absolute best outcome at the highest confidence level.

A Flexible Composable Architecture: Power Without the Bloat

Tealium’s data strategy is delivering in a very unique manner. Instead of requiring organizations to duplicate data into a new isolated warehouse or re-ingesting what enterprises already maintain in their data cloud, Tealium integrates natively with these environments. That means organizations can activate insights directly from their data cloud infrastructure, with no performance tax and no new data silos to manage. By eliminating the need to copy data, Tealium reduces operational complexity, lowers data governance risks, and dramatically shortens the time to value. Zero Copy alone however leaves a large gap in orchestrating real-time experiences as Zero Copy and other Reverse ETL options only access the historical data.

The Real-Time Profile Cache: Precision at Speed

What sets Tealium apart is its high-speed, event-driven profile cache, which updates in milliseconds with every single customer interaction. This lightweight asset unlocks all of the real-time use cases.

Every click, tap, swipe, purchase, or interaction a user has with your brand immediately updates their profile in Tealium’s cache. This live profile view acts as a hyper-relevant, continuously evolving source of engagement for personalization engines, AI models, and customer service systems. Best of all it’s not just the events that are captured but also calculated enrichments that are adding deep intelligence to the customer profile. Now we have a realtime streaming intelligent pipeline and the sky is the limit in how powerful this is for AI and CX. Rather than housing all of this in isolated storage, Tealium streams data back to the Data Cloud for AI and Segmentation.

Think of it as a real-time edge profile—lightweight, ephemeral, but immensely powerful. It ensures that every moment with a customer is powered by the most up-to-date understanding of who they are, what they want, and how they’re engaging right now.

In-the-Moment Activation: The New Gold Standard

With this dynamic infrastructure in place, Tealium enables true in-the-moment customer experiences with no lag between insight and action. Whether it’s triggering an AI enabled email based on a product engagement, surfacing personalized content in an app, fueling a GenAI agent, or routing a customer to a VIP support line, Tealium delivers the real-time intelligence to make these experiences possible.

And because this real-time engine is supported by integrations with thousands of turnkey AI, martech and adtech platforms, activation isn’t just fast—it’s everywhere.

A New Era for Customer Data Platforms

The rise of the Data Cloud has fundamentally changed the rules of the CDP game. In this new era, storage-heavy CDPs are quickly becoming obsolete. Enterprises are demanding tools that are cloud-centric, real-time, and tightly integrated with existing data ecosystems. Tealium isn’t just evolving to meet this demand—it’s leading the charge.

With a native-warehouse friendly architecture, the ability to activate data without loading or copying, a real-time profile cache updated in milliseconds, and deep integration with the modern enterprise stack, Tealium is redefining what it means to be a CDP. The result? Smarter data, faster insights, and more meaningful customer experiences—when they matter most. Now your CDP can be the perfect complement to your Data Cloud investment. Why choose one method over the other when you can have the Best of All Worlds!

The post How Tealium is Redefining the CDP Market in the Age of the Data Cloud appeared first on Tealium.

Evolving With Our Customers

We saw teams scaling rapidly, deploying dozens or even hundreds of connectors across global regions and business units. And with that scale came new demands — for greater visibility, more efficiency, and deeper flexibility.

We didn’t just want to improve performance or update the visuals. We wanted to rethink the Connector experience to match how modern teams work with data today.

“We built the new Connector UI to empower customers with clearer insight, smarter workflows, and a more scalable foundation for activating data. It’s designed not just for where our users are today, but where they’re headed.”

-Corbin Spicer, Director of Partner Products at Tealium

What We Set Out to Improve

With the new Connector UI, we focused on four key areas:

• Visibility and Observability – A high-level view of each connector’s performance, with trends, sortable results, and error types — all helping teams quickly spot what’s working and where attention is needed.
• Workflow Efficiency – Copy mappings from existing configurations, apply bulk actions across connectors and actions, and use labeling to organize setups at scale.
• Developer-Friendly Templating – Full-screen code editing, clearer visibility of Trimou templating, and easier navigation for teams building advanced configurations.
• A Unified, Scalable Design System – The new UI is built on Tealium’s latest design system, improving accessibility, consistency, and long-term maintainability for our teams and users.

How This Helps You

Whether you’re a marketer, analyst, or developer, the updated experience is designed to make your day easier:

• Faster time-to-insight with in-UI metrics and simplified debugging.
• Easier reuse and scalability through features like Copy Mappings and bulk editing.
• Streamlined collaboration thanks to labels, favorites, and a cleaner layout.
• Room to grow with a more performant and extensible foundation for the future.

If you’re already part of our Early Access program, you’ve seen firsthand how the new experience transforms daily workflows. For everyone else, this marks the beginning of a faster, more powerful way to activate your data.

We’re excited to roll this out and continue improving based on your feedback.

The post Why We Built the New Connector User Interface — And What It Unlocks for You appeared first on Tealium.

Powering the Next Generation of AI Marketing

Marketers today face a growing challenge: the data they rely on for machine learning and personalization is often incomplete, stale, or stuck in pre-processing pipelines. That means delayed model training, inaccurate targeting, and missed moments.

Tealium AIStream solves this by delivering real-time, enriched, consented behavioral data directly into Databricks Delta Lake, eliminating the data preparation bottleneck. This streaming data is:

• AI-ready and optimized for Delta Lake ingestion

• Enriched at the point of capture

• Structured for immediate use across the Lakehouse environment

This enables accelerated time-to-insight and faster model deployment, whether you’re working with real-time, historical, or hybrid data sets. Per Matthew Gray, SVP of Global Partnerships and Alliances at Tealium: “We’re proud to join the Built on Databricks community and deepen our collaboration to support the world’s leading enterprises. Our partnership ensures customers continue to benefit from cutting-edge innovation, real-time insights, and the highest standards of compliance and performance.”

Real-Time Interoperability Across the Lakehouse

With Tealium now tightly integrated into Databricks’ ecosystem, data and AI teams can seamlessly stream behavioral data into and orchestrate from:

• Delta Live Tables for scalable, real-time analytics

• MLflow for model experimentation, deployment, and activation

• Unity Catalog for secure data governance, sharing, and enforcement

• Feature Store for building AI-ready customer features

Whether you’re using Tealium’s EventStream for data collection or AudienceStream for audience orchestration, this partnership gives brands the flexibility to build modern, composable marketing architectures tailored to their needs.

Built-In Privacy and Governance

As regulations evolve, AI must be built on a foundation of trust. Tealium AIStream captures consented, first-party behavioral data and tags every record with consent metadata. That consent-aware data is ingested directly into Unity Catalog, ensuring:

• End-to-end data lineage

• Compliance with privacy regulations

• Ethical AI development practices

Key Benefits for Marketing and Data Teams

With Tealium and Databricks, brands can now:

• Activate real-time data for personalized customer journeys

• Improve segmentation with machine learning

• Build unified profiles across channels and touchpoints

• Accelerate marketing analytics and campaign optimization

• Scale data processing across high-volume customer interactions

• Maintain compliance with global privacy regulations

A Future-Proof Foundation for AI Marketing

This partnership enables modern enterprises to build marketing stacks that are responsive, intelligent, and ready for whatever comes next. By integrating Tealium’s real-time data capabilities into Databricks’ unified data and AI platform, organizations can finally bridge the gap between raw data and real-time action, without sacrificing trust, scale, or agility.

Learn more about why Databricks and Tealium are Better Together:
tealium.com/technology-partner/databricks-tealium-better-together

Visit us at Databricks Data and AI Summit, June 9 – 12, 2025  – Booth #522

The post Tealium + Databricks: Powering the Next Generation of AI Marketing appeared first on Tealium.

What This Integration Delivers

• Seamless Data Flow: Import data from Snowflake tables or views with near real-time efficiency, keeping your customer insights current and actionable. Our flexible query modes (timestamp, incrementing, or both) intelligently identify new or modified rows, ensuring you’re always working with the latest information.
• Complete Data Compatibility: Work confidently with all Snowflake data types while mapping columns precisely to Tealium attributes. The integration maintains data integrity through intelligent visitor ID mapping that connects Snowflake data with your existing customer profiles, creating a truly unified view of each customer.
• Efficient Processing: Handle large datasets effortlessly with real-time batch processing, balancing performance with system efficiency.

How Your Team Benefits

• Richer Customer Insights: Combine historical data from Snowflake with real-time behavioral data in Tealium to build more accurate audience segments and deliver in-the-moment personalized experiences.
• Superior Data Quality: Our integration automatically cleanses and transforms data during import, significantly reducing manual preparation work and delivering higher quality information for your analytics and marketing efforts.
• Real-Time Activation: Move from data collection to meaningful action faster with immediate access to newly imported customer insights.
• Operational efficiency & cost savings: Automate previously complex data transfer processes to reduce redundant tasks and free your team to focus on strategic initiatives rather than data management.
• Flexible Implementation: Choose the data ingestion method that works best for your needs: In addition to the Snowflake inbound data source integration, you can also ingest data via API import, file import, or Tealium’s visual Data Connect query tools.
• Enterprise-grade Compliance & Governance: Maintain compliance with data governance requirements and privacy regulations, ensuring customer consent is respected throughout the data integration process. The integration supports GDPR, CCPA and other data regulations with consent.

Transform Your Customer Data Strategy

This integration represents a significant advancement in how businesses can connect their data warehouse insights with real-time customer engagement. By bringing Snowflake’s robust data storage capabilities together with Tealium’s customer data orchestration, your team can unlock deeper insights and create more effective customer experiences.

We encourage you to think about how this integration could enhance your specific customer data initiatives. Ready to learn more about transforming your approach to customer data? Contact our team today to discuss how the Tealium-Snowflake integration can support your business goals.

Come visit us at Snowflake Summit in San Francisco, June 2-5. Booth #1414. 

The post Bridging Your Data Worlds: Tealium’s New Snowflake Integration appeared first on Tealium.