As privacy regulations tighten and the industry shifts away from third-party cookies, brands and media owners seek more sophisticated, privacy-safe ways to collaborate on data. This has paved the way for data clean rooms—secure, decentralized environments that enable multi-party data collaboration without exposing the underlying data to each partner. 

Like architects drawing up blueprints for a new building, media agencies now survey the entire landscape—brands, media owners, data partners, and technology providers—and design a cohesive plan that keeps every “room” (or data source) structurally separate yet interconnected.

Rather than merely executing a buy, agencies orchestrate complex data strategies—managing insights, planning, activation, and measurement. This blog explores how data clean rooms are empowering agencies to become active leaders of data collaboration and why these decentralized solutions are poised to transform the way agencies operate at scale.

Data Clean Rooms 101

A “data clean room” is a privacy-enhancing technology that allows multiple parties to compare or analyze data sets without sharing raw information. Think of it as a secure “meeting room” in the cloud: two or more partners—like a brand and a media owner—can match or analyze their respective customer data, but no one ever sees or handles personally identifiable information (PII) from the other party.

Historically, these collaborations required a third-party data processor to centralize data, creating both compliance risks and logistical hurdles. Clean rooms remove those burdens. Data remains under each party’s control, so it’s never pooled or commingled. This decentralized approach has proven highly attractive to agencies worried about liability or the accidental leakage of client data. By adopting a data clean room model, agencies can help their clients run advanced use cases—such as audience insights, predictive modeling, media planning, campaign activation, and measurement—without ever taking custody of sensitive information.

Timeline: How We Got Here

To appreciate why agencies are stepping into a new leadership role, it helps to look at how data collaboration has evolved over the last few years:

Direct Brand–Media Owner Deals

In the early days of data collaboration, deals were often bilateral—a brand and a media owner would link up, match audience segments, and run a campaign. Agencies would come in to finalize negotiations and ensure execution ran smoothly. During this stage, agencies were primarily “passive.” They didn’t own the data strategy or the technological relationship; they simply enabled existing brand–media owner connections.

Growth of Complexity

Soon, media owners and brands began layering in more data sources—like commerce data, retail data, or second-party partnerships. These multi-party setups demanded more advanced infrastructure. At the same time, privacy regulations stiffened globally, increasing the risks associated with centralizing consumer data. Everyone needed a way to collaborate safely.

Rise of Agency First-Party Data Divisions

Recognizing the complexity, many large agencies spun up specialized data teams or divisions. They started championing data strategies that pulled together multiple partners—brands, media owner, and data providers. Agencies began to see themselves as orchestrators, guiding clients from “no data strategy” to “first-party data strategy,” and eventually to “multi-party data collaboration.”

Decentralization & Privacy-Enhancing Tech

The final piece of the puzzle arrived with privacy-preserving tools, particularly data clean rooms. These made it possible for agencies to drive more complex collaborations without becoming data processors themselves. As brands looked for end-to-end solutions—insights, planning, activation, and measurement—agencies discovered they could deliver all of this by leveraging decentralized clean room technology at scale.

Like master architects, agencies no longer just “paint the walls” after the structure is built; they now draft the entire design from the foundation up, ensuring each data partner’s privacy requirements are baked in from day one.

Why Agencies Are Embracing the Data Clean Room Model

Reduced Liability, Increased Trust

Handling raw customer data carries hefty compliance and reputational risks. With a decentralized solution, agencies don’t have to ingest or store personal data from the brand. That keeps them out of the legal crosshairs. One data executive summed it up succinctly in an internal discussion: “There’s an absolute reticence for an agency to ever be exposed to that personal data.” By staying one step removed, agencies can operate more securely and focus on delivering strategic value, rather than worrying about compliance headaches.

Full-Funnel Capabilities

Data clean rooms let agencies go well beyond basic audience matching. By intersecting multiple data sets within these secure environments, agencies gain deeper behavioral insights that inform everything from strategic campaign planning to granular audience segmentation. The result is a more precise approach to media planning, free from the limitations of cookie-based targeting. 

Once campaigns launch, agencies can activate media across media owners, retail partners, or streaming platforms without ever commingling data. This level of privacy-focused collaboration also streamlines measurement, enabling advanced analytics such as multi-party attribution and incrementality testing at scale. 

This “all-in-one” approach dovetails perfectly with an agency’s full-funnel mission: help clients from the earliest planning stages to final campaign analysis.

Scalable “Productization”

The beauty of decentralized data collaboration lies in its repeatability across an entire client roster. After setting up a clean room solution for one brand, agencies can replicate the same proven framework for other clients with minimal operational overhead. By developing a standardized “playbook” that outlines data onboarding, partner integrations, and day-to-day management, agencies can swiftly bring multiple media owners and brands into secure data collaborations. This approach saves time and resources and positions the agency as the central connector for all parties. 

What begins as a one-off pilot soon evolves into a scalable engine for growth—enabling agencies to continually expand and refine their data-driven services for each new campaign, partnership, and client. In architectural terms, once you’ve nailed the blueprint for a single structure, you can adapt and replicate it across an entire skyline—each new building (client) benefiting from the same sturdy, privacy-first foundation.

Building Private Data Networks with InfoSum

In the past, “private data networks” were predominantly owned or hosted by major media owners—each media owner would invite select brands to collaborate, with the media owner acting as the data gatekeeper. While that model still exists, the new frontier sees agencies owning their own private ecosystems of brand, data, and media partners. Here’s how it works:

Agency as the Orchestrator

The agency sets up a clean room environment (or partners with a privacy-preserving technology provider) that integrates seamlessly with the agency’s existing platforms. Brands “Bunker” their data in their own secure environment, controlling access at all times.

Multi-Party “Nodes”

Any relevant partner—media owner, retailer, or data provider—can host its own data in a separate, secure Bunker. Because each Bunker is owned by the data owner, they retain full control over the rules and permissions governing how, where, and for what purpose their data is used. At the same time, agencies act as the curators of collaboration, orchestrating multi-party engagements without ever handling the raw data themselves. The agency coordinates access, sets up workflows, and aligns strategic objectives, all while ensuring each party’s permissions are respected. This means no one ever sees another’s raw data; only aggregated or anonymized results are shared for planning, activation, or measurement.

Strategic Value

Brands tap into new media partners or specialized data sets with minimal overhead. Media owners access incremental brand budgets because the agency drives demand for first-party-based campaigns. The agency becomes the central “connector” for all these data relationships, going from passive broker to active orchestrator.

Over time, these private data networks can grow significantly, offering advertisers everything from retail audience segments to premium TV inventory, all executed via the agency’s secure infrastructure.

Real-World Examples

Here are some real-world use cases that illustrate the power of agencies leading data collaboration:

Suppression in Streaming Video

• An agency works with a consumer brand aiming to avoid over-targeting existing customers on a streaming platform.
• The brand’s first-party data is matched—within a clean room—to the platform’s subscriber base.
• Existing customers are suppressed, reducing ad waste and improving ROI.

Retail + CPG Collaboration

• A large consumer packaged goods (CPG) company wants to run a campaign on a retailer’s website to promote a new product launch.
• Via a clean room, the retailer provides purchase-based audiences, while the CPG brand analyzes overlap with its own high-value segments.
• The agency orchestrates the entire process, ensures privacy compliance, and measures the lift in sales.

Multi-Brand Insights & Planning

• A global media agency has multiple brands within the same industry, looking to glean cross-customer insights.
• Each brand hosts its first-party data in its own secure environment. The agency queries the combined data sets for aggregated audience insight—such as common customer attributes—without exposing any single brand’s raw data.
• This intelligence informs future campaign strategies across the agency’s entire client portfolio.

In each scenario, the agency isn’t just finalizing deals. It’s actively shaping strategy, ensuring data privacy, and ultimately delivering stronger business outcomes for clients.

From passive to active data collaboration leaders

Media agencies have reached a pivotal moment in the world of data-driven marketing. Where they once acted primarily as passive facilitators of brand–media owner deals, they now have the opportunity to become active orchestrators of multi-party data collaboration. By harnessing decentralized clean rooms, agencies can ensure data privacy, reduce liability, and maintain full oversight of how insights, activation, and measurement come together. This transition from broker to driver is radically different from the past—but it’s also what positions agencies to thrive as third-party cookies vanish and privacy expectations intensify.

For agencies committed to scaling this approach, begin by assessing your current data strategy, training internal teams, and selecting tech providers that prioritize privacy and interoperability. Early pilots—such as suppressing existing customers in a connected TV campaign or running an incrementality test with a retail partner—can quickly demonstrate ROI and spark broader adoption. By “productizing” data collaboration, agencies unlock a truly full-funnel, privacy-centric model that resonates with brands and consumers alike.

Ultimately, the role of the modern media agency resembles that of a skilled architect. Agencies design the blueprint for privacy-safe data collaboration, coordinate each “room” where data owners can safely operate, and ensure the entire structure stands on a compliant, future-proof foundation. By embracing this architectural mindset, agencies elevate their position from behind-the-scenes coordinators to the true architects of data-driven campaigns, delivering both brand success and consumer trust. The potential is enormous, and the technology is ready—agencies just need to seize the opportunity.