Data clean rooms have shifted from emerging technology to essential infrastructure for retail media. With 66% of organizations now using clean rooms in some capacity, according to the 2025 State of Retail Media report, these secure environments enable brands and retailers to collaborate on first-party data without exposing raw information.

As US retail media ad spending approaches $70 billion in 2026, clean rooms have become the connective tissue between purchase data, campaign measurement, and privacy compliance. However, fewer than half (48%) of US retail media networks currently offer clean room capabilities, according to Q2 2025 data from Mars United Commerce, signaling meaningful white space for networks to differentiate amid intensifying competition.

What is a data clean room?

A data clean room is a secure digital environment where multiple parties can combine their first-party data to generate audience and campaign insights without exposing raw data to each other. The IAB Tech Lab defines it as a "secure collaboration environment which allows two or more participants to leverage data assets for specific, mutually agreed upon uses, while guaranteeing enforcement of strict data access limitations."

In practice, clean rooms allow retailers, brands, and media partners to match customer records, analyze overlapping audiences, and measure campaign performance while maintaining privacy controls. The technology uses cryptographic techniques and privacy-enhancing technologies (PETs) to ensure neither party sees the other's underlying data.

Why are data clean rooms becoming essential for retail media?

Retail media's growth depends on data collaboration that clean rooms uniquely enable. Four factors are accelerating adoption:

• First-party data activation. As legacy signals like third-party cookies fade, retailers' purchase data becomes the most valuable targeting signal. Clean rooms allow brands to activate this data without retailers surrendering it.
• Closed-loop measurement. Retail media networks can connect ad impressions to actual transactions. Clean rooms provide the secure infrastructure to share this attribution data with advertisers.
• Privacy compliance. State privacy laws limit how brands collect and use consumer data. Clean rooms keep data anonymized and aggregated, helping companies stay compliant across jurisdictions. Some 66% of US data and ad professionals have adopted data clean rooms due to privacy legislation and signal loss, according to February 2024 data from the IAB and BWG Strategy.
• Non-endemic advertiser expansion. Retail media networks are attracting advertisers beyond CPG, including financial services, gaming, and travel. Clean rooms enable these partnerships without exposing competitive shopper intelligence.

How do retail media networks use data clean rooms?

Retail media networks deploy clean rooms for three primary functions:

• Matching purchase data with behavioral data. Retailers, brands, and media partners can combine data to create a more complete customer view. "You can get beyond simple purchase data and start to target based on a series of actions," Riyaad Edoo, executive director of commerce at EssenceMediacom, noted in an IAB roundtable. "That gets to the psychology of the consumer, their behavioral patterns or passion points."
• Connecting online ads to in-store sales. CVS Media Exchange partnered with Pinterest on a clean room that cross-references CVS ExtraCare member purchasing habits with Pinterest data, enabling closed-loop reporting for suppliers.
• Informing channel investment. "One of our biggest wins with data clean rooms is when we use it as a baseline to inform channel investment," said Kavita Cariapa, senior vice president at Dentsu, per EMARKETER. Clean rooms help agencies identify incrementality opportunities across retail media networks.

What types of data clean room providers exist?

Two categories of providers dominate the market:

Walled garden clean rooms are operated by major platforms and media companies. Examples include Amazon Marketing Cloud (AMC), Google Ads Data Hub, Instacart’s Data Hub, Disney's clean room, and NBCUniversal's clean room. These environments typically limit analysis to the platform's own inventory and audiences.

Amazon expanded access to AMC significantly in September 2025, making it free for all Sponsored Ads advertisers. This move removed cost barriers that previously limited clean room access to larger advertisers with dedicated data teams.

Independent clean room platforms are provided by third-party vendors. Snowflake, LiveRamp, InfoSum, and AppsFlyer operate platform-agnostic solutions that support collaboration across multiple partners and cloud environments.

How do data clean rooms differ from DMPs and CDPs?

All three technologies analyze data to generate customer insights, but they serve different purposes:

• Data management platforms (DMPs) collect and house first-, second-, and third-party data inputs, generating insights for real-time decision-making. They integrate with demand-side and supply-side platforms and can be used by both advertisers and publishers.
• Customer data platforms (CDPs) focus exclusively on an organization's first-party data about its own customers. CDPs create a unified view of each customer for personalized marketing and other use cases.
• Data clean rooms exist solely to enable secure data sharing between multiple companies. The key distinction is collaboration: clean rooms allow two or more parties to combine their data assets without either party accessing the other's raw data.

More than 80% of data clean room users also use CDPs and DMPs, per the IAB. The technologies are complementary, not substitutes.

What are the main challenges with data clean room adoption?

Despite rapid growth, clean rooms present specific obstacles:

• Actionability. 39% of organizations struggle to drive actionable insights from clean room data, according to the 2025 State of Retail Media report. Integration with planning, activation, and reporting workflows remains inconsistent.
• Cost. 48% of marketers and agencies cite a lack of budget as the reason they aren’t planning to use clean rooms, found July 2024 data from Cint and Lotame. While Amazon's free AMC access addresses this for its ecosystem, independent solutions carry significant implementation and licensing fees.
• Technical expertise. Clean rooms require SQL proficiency and data science capabilities. Many brands lack dedicated analysts to extract insights effectively.
• Interoperability. Each retailer operates its own clean room with different technical requirements. Managing collaborations across Amazon, Walmart, Kroger, and Target creates operational overhead.

Industry standardization is progressing. IAB Tech Lab finalized ADMaP 1.0 in February 2025 for attribution data matching and PAIR 1.1 in July 2025 for audience activation, establishing common protocols for privacy-safe data sharing.

What role do data clean rooms play in retail media measurement?

Measurement is the most established clean room use case in retail media. Clean rooms address the channel's core attribution challenge: connecting digital ad exposure to in-store and online purchases.

Retail media networks use clean rooms to provide advertisers with:

• Closed-loop attribution. Deterministic measurement linking impressions to transactions, which traditional digital advertising cannot offer.
• Incrementality analysis. Testing frameworks that isolate the true lift from retail media campaigns versus baseline sales.
• Cross-channel reporting. Unified measurement across on-site search, display, off-site programmatic, and connected TV inventory.

What should brands consider when selecting a data clean room for retail media in 2026?

Due diligence should address four areas:

1. Cloud compatibility. Evaluate whether the platform is cloud-agnostic or requires specific infrastructure. Brands working across multiple retail media networks need flexibility to collaborate with partners using different cloud providers.
2. Privacy controls. Examine the privacy-enhancing technologies employed. Look for platforms supporting protocols like PAIR and ADMaP, which ensure industry-standard security for data matching and attribution.
3. Measurement capabilities. Assess built-in reporting and analytics features. Platforms with reach and frequency reporting, AI-powered segmentation, and customizable attribution windows reduce the need for external tools.
4. Retailer coverage. Determine which retail media networks the platform integrates with natively. Some clean rooms offer direct connectors to Amazon, Walmart, and Kroger, while others require custom implementation.

Start with retailers where you have existing distribution and sales data to benchmark performance before expanding clean room partnerships.

We prepared this article with the assistance of generative AI tools and stand behind its accuracy, quality, and originality.

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