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Clean room and CDP: What's the difference and why might you need both?
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Marketing runs on data, but the data needed to drive performance is more fragmented, restricted and difficult to access than ever. The data clean room is emerging as a solution, enabling brands to securely collaborate, unlock insights and activate campaigns—and proving that privacy and performance can go hand in hand.
A data clean room is a secure, pseudonymized environment where brands can combine first-, second- and third-party data to better understand their customers and expand prospective audiences without compromising data privacy.
In a data clean room, multiple parties can access the data for insights, activation and measurement, but those parties can never take or deanonymize data they don’t own. For example, a retailer and a CPG brand may use this technology to share customer data with each other, both augmenting what they know about shared customers, expanding unknown audiences and enabling more effective campaigns.
Learn how data clean rooms can help you reach new customers in this video with Epsilon’s Michelle Dieschbourg, Senior Manager of Product Marketing.
Third-party cookies are (still) on their way out. Identity signals are increasingly fragmented across multiple emails, devices and channels. And customer data is locked inside internal silos, platforms and partners. Meanwhile, consumers still expect marketers to provide highly relevant experiences with every interaction.
Put simply, it’s hard to effectively connect with consumers.
First-party data is often touted as the silver bullet. Clean, resolved first-party data is foundational to omnichannel marketing, but it only provides information about what known customers do within the brand’s owned universe (not outside it). Plus, some brands just don’t have a lot of first-party data to begin with.
Partners offer complementary signals from their data ecosystems, and third-party platforms and publishers provide their own insights for purchase. Combining insights from these data sources provides brands with a rich, complete customer view needed to power marketing performance.
But doing this has become more difficult. Data privacy regulations remain paramount, and brands can’t just share data anymore—they need a controlled way to work on it together.
Clean rooms offer a privacy-safe space for brands to use multiple sources of data to derive insights and build a complete customer view.
Customer data platforms (CDPs) and clean rooms both help brands to unlock deeper insights about consumers—but in slightly different ways. Many marketers consider them find them to be complementary technologies.
The primary role of a CDP is to unify, cleanse and serve as a repository for a brand’s known customer data. It helps you know your own customers better so you can personalize and orchestrate campaigns across owned and paid channels.
A data clean room platform serves as a secure, pseudonymized environment to combine data sets from various sources—including first-party data, data from walled gardens, partner data, regulated data, etc. It helps you find and understand current and prospective new customers safely.
| Customer Data Platform (CDP) | Data Clean Room | |
|---|---|---|
| Primary purpose | Unify, cleanse, and enrich your own customer data | Enable data collaboration and discovery of new/prospective customers |
| Data type | First-party, personally identifiable information (PII-based), like name, email, transaction data, behaviors | Pseudonymized data from multiple sources (first-, second- and third-party) |
| Activation | Across owned + paid channels (email, site, media) | Paid media activation, programmatic and social |
| Example use cases | Personalization for existing customers, cross-channel orchestration, customer life cycle marketing | Audience expansion, partner data collaboration, lookalike modeling and prospecting |
Regardless of whether you choose to use a CDP, a clean room or both, the full value of these platforms will come from unifying these tools with the rest of your adtech and martech. Properly integrating the technology allows you to funnel the insights to activation platforms like demand-side platforms (DSPs) to deploy more personalized campaigns—and measure performance in real time.
Data clean rooms and AI have a symbiotic relationship. A clean room can provide the required data foundation for effective AI, and AI scales the clean room’s capabilities.
For AI to work effectively, it requires large amounts of high-quality data, which a clean room can provide.
Clean room technology allows your brand to work with various data sets to augment and enrich data, filling gaps on known and prospective customers. The best data clean rooms are also equipped with identity resolution. Identity unifies fragmented data into a single, accurate view of each person—giving AI the clean, consistent inputs it needs to generate reliable predictions in a privacy-safe environment.
On the flip side, AI can also scale the functionality of the clean room. When a clean room is equipped with identity and properly integrated with the broader tech stack, the technology can:
Now add AI to the mix.
AI data clean rooms use AI-driven audience insights to develop, activate, measure and learn from campaigns—in real-time and at scale.
Understand who you want to reach now, who to reach next and who to avoid. When powered by AI, a data clean room can do this at scale—learn how.
Data clean rooms turn data collaboration into action. From insights to activation to measurement, here are five ways marketers are putting them to work.
Clean rooms combine first-, second-, and third-party data to create a richer, more complete understanding of both known and prospective customers. This unified view helps identify high-value audiences, uncover new prospects and build more precise targeting strategies.
Data clean rooms turn audience insights into action by allowing you to activate campaigns across channels with unified, person-level data. With identity resolution and integrated activation capabilities, you can deliver the right message to the right individual at the right time—and continuously optimize based on real performance signals.
Data clean rooms enable person-level measurement by connecting exposures and outcomes across channels. With identity resolution, you can move beyond siloed metrics to understand real customer behavior and optimize spend.
Clean rooms provide a privacy-safe environment for brands and partners to collaborate on data, unlocking shared insights without exposing sensitive information. This collaboration helps both parties better understand overlapping customers and create more effective joint marketing strategies.
Retailers and brands can use clean rooms to combine transaction data with media exposure data for more precise targeting and measurement. This allows brands to reach in-market shoppers more effectively while helping retailers monetize their data through more valuable retail media offerings.
Learn more about the essential capabilities and value drivers you should look for in a clean room solution—and what questions to ask during the evaluation process.
Many independent clean rooms come as an empty box a brand is expected to fill. But these solutions are missing two key components present in any high-performing data clean room platform:
For brands without a lot of first-party data, it can be hard to find value in the average clean room—they only have so much data to analyze and glean insights from. They would need to rely heavily on partners and purchased third-party data to make the clean room investment valuable, thus tacking on costs to an already-expensive technology investment (not to mention the additional procurement involved).
And then there's the issue of data quality—quality data is foundational for quality results. Brands often have disparate data that live in various systems and platforms, and a lot of that data is often inaccurate, duplicative or incomplete. Data clean rooms can deploy identity resolution solutions designed to unify, clean and organize data, but that often comes at an additional cost.
A data clean room equipped with preloaded data and identity enables brands to start activating their data on day one. Epsilon Clean Room comes preloaded with data and identity that delivers better prospect identification, high-performance media activation and closed-loop measurement.
A multi-brand jewelry retailer was dealing with disjointed data, fragmented propensity and attribution models and limited performance metrics. See how the retailer used Epsilon Clean Room to attract new customers across channels.
The future of privacy-safe data collaboration will be defined by stricter regulations, the continued decline of third-party cookies and the growing need for brands to work together without exposing sensitive data. Data clean rooms are emerging as the foundation for this shift—enabling secure, compliant collaboration across companies while still unlocking valuable customer insights.
As identity resolution and AI become more tightly integrated, brands can unify fragmented data, enrich it with partner inputs and power more accurate modeling, activation and measurement at scale. The result is a new marketing paradigm: one where privacy and performance are no longer in conflict but mutually reinforcing.
Epsilon Clean Room’s preloaded data enhances your first-party data using identity resolution, giving you the best view of customers and prospects on a platform made for marketers and data scientists—all built on a privacy-first network.
