Data Clean Rooms: The Definitive Guide

Kevel Team

Written by the people building the future of retail media

Table of Contents

• What Are Data Clean Rooms?
• Key Features of Data Clean Rooms
• Types of Data Clean Rooms
• How Are Data Clean Rooms Used?
• Pros & Cons of Data Clean Rooms
• Best Practices: How To Use A Clean Room Solution
• The Future of Data Clean Rooms

What data clean rooms are and how they work.

Data clean rooms have become an essential tool for advertisers and publishers looking to optimize their first-party data while upholding user privacy. With the unstable status of third-party cookies and privacy regulations growing increasingly stringent, these secure environments have taken center stage in the ad tech landscape. This comprehensive guide explains how data clean rooms work, their key benefits and challenges, and best practices for implementation.

What Are Data Clean Rooms?

Data clean rooms are secure environments where multiple parties can analyze aggregated datasets without exposing personally identifiable information (PII). They allow advertisers, publishers, and platforms to match and enrich audience data for targeting and measurement -- while preserving privacy.

According to the IAB State of Data Report 2023, 64% of companies using privacy-preserving technologies are leveraging data clean rooms. This growing interest and increased adoption is likely driven by the tightening of privacy regulations and the increasingly unstable state of third-party cookies.

Key Features of Data Clean Rooms

The core features that make data clean rooms an attractive solution for optimizing first-party data include:

• Secure data isolation. Each party’s raw data remains separate and inaccessible to others.
• Encryption and anonymization. Sophisticated encryption methods, data anonymization processes, and privacy-preserving computations protect individual user information from unauthorized access or identification.
• Access controls. Strict permissions determine who can view or interact with specific data.
• Audit trails. All activity within the clean room is logged for accountability and transparency.

Types of Data Clean Rooms

Data clean rooms come in various forms, each tailored to meet specific needs and use cases in the digital advertising world. By understanding the main types of clean rooms available, companies can select the option that best aligns with their data collaboration needs and privacy standards. Let’s discuss the three primary categories of data clean rooms on the market today:

1. Walled Garden Solutions

Major platforms such as Google, Facebook, and Amazon offer proprietary clean room solutions. These platform-managed environments allow advertisers to match their own data with platform user data for audience analysis and campaign measurement. While they offer powerful capabilities, their functionality is confined to each platform’s ecosystem.

Examples:

• Google’s Ads Data Hub, which enables advertisers to analyze campaign performance within Google Cloud
• Facebook’s Advanced Analytics, which offers insights into cross-platform engagement
• Amazon Marketing Cloud, which allows brands to enrich their data with Amazon’s extensive e-commerce insights

2. Independent Providers

Independent providers like Snowflake, InfoSum, and Habu offer standalone clean room technologies that operate across multiple platforms and data sources. These orchestrator-managed clean rooms serve as neutral third-party environments, enabling secure data collaboration across different platforms and regions. They can be especially valuable for organizations that need greater flexibility -- whether to analyze data across walled gardens, incorporate offline data sources, or support cross-partner collaboration.

Examples:

• Snowflake’s Data Clean Room, which offers a neutral environment for cross-platform data analysis and secure collaboration
• InfoSum’s decentralized platform, which keeps data within each party’s infrastructure while enabling shared insights
• Habu’s clean room solution, which features pre-built use cases and user-friendly interfaces to simplify clean room adoption for organizations of all sizes

3. Industry-Specific Offerings

Specialized clean room solutions have emerged to meet the unique data collaboration needs of specific industries. These tailored environments support secure data sharing and analysis while ensuring compliance with sector-specific regulations and privacy standards. Industry-specific clean rooms often include pre-built use cases, data models, and compliance frameworks designed to address the particular challenges and opportunities within each vertical.

Examples:

• Retail Media Networks like Walmart’s Luminate and Kroger Precision Marketing, which offer clean rooms that help CPG brands analyze customer behavior and optimize marketing strategies using retailer data
• Healthcare-focused clean rooms like Datavant, which provide HIPAA-compliant environments for researchers and healthcare organizations to securely analyze patient data for clinical trials and drug development
• Financial services solutions from companies like Experian and TransUnion, which offer clean room technologies that enable banks and insurers to collaborate on fraud detection and risk assessment while maintaining strict data privacy controls

How Are Data Clean Rooms Used?

According to the IAB Tech Lab, the primary use cases of data clean rooms include:

1. Addressability and Audience Activation. Data clean rooms allow advertisers and publishers to build more precise audience segments by transforming first-party data into “addressable IDs” for targeting and measurement. For instance, a luxury watch brand could combine its customer data with engagement data from a lifestyle magazine to identify high-income prospects.
2. Customer Insights and Data Enrichment. Organizations can match their conversion data with publishers' ad exposure data to evaluate campaign performance across multiple channels. This facilitates more accurate multi-touch attribution models and richer customer profiles -- without the need to share personal information directly.
3. Optimization and Measurement. Clean rooms offer a secure space for both real-time and offline attribution, helping identify which touchpoints across various channels and campaigns contributed to a conversion without exposing user level conversion or engagement data. By enriching customer profiles with partner-sourced attributes, businesses gain deeper insights and can deliver more personalized, effective marketing strategies.

Pros & Cons of Data Clean Rooms

Benefits

• Privacy Compliance. Data clean rooms enable organizations to meet the constantly evolving privacy regulations like GDPR and CCPA. By encrypting and anonymizing data, they minimize exposure of personal information. The IAB Tech Lab’s data clean room standards emphasize that clean rooms “provide a ground for secure collaboration between governmental entities, research institutions, NGOs and businesses to share environmental data sets.”
• Enhanced Data Collaboration. Clean rooms encourage partnerships between advertisers, publishers, and platforms by providing a secure environment for data sharing.
• Improved Targeting and Measurement. Access to richer datasets allows for more sophisticated audience segmentation and campaign analysis, meaning more effective campaigns and better ROI analysis.

Challenges

• Technical Complexity. Implementing and managing data clean rooms often requires specialized knowledge. Apoorv Durga of Real Story Group points out that clean room providers will “need to integrate more comprehensive activation features to stay relevant and competitive.”
• Interoperability Issues. Ensuring seamless data exchange between different clean room solutions remains a hurdle. The IAB Tech Lab is still working on standards like the Open Private Join and Activation (OPJA) to address this challenge.
• Cost Considerations. The average company spends as much as $879,000 on data clean rooms according to a Funnel.io survey, making it a significant investment, especially for smaller organizations.
• Real-Time Limitations. Some clean room setups struggle with low-latency data processing, potentially hampering real-time ad optimization. Clean rooms don’t solve all privacy and data sharing issues and you will almost always need to employ it in conjunction with other tools and technologies.

Best Practices: How To Use A Clean Room Solution

Implementing a data clean room requires planning and execution to maximize its value. Here are some best practices to consider throughout implementation:

1. Define Clear Objectives. Before investing in a clean room solution, identify specific use cases and desired outcomes. This might include improving audience targeting, enhancing measurement capabilities, or enabling secure data partnerships. Having well-defined goals will guide your implementation strategy and help measure success.
2. Establish Data Governance. Develop comprehensive policies for data usage, access, and retention within the clean room environment. This includes defining roles and permissions, establishing data handling protocols, and ensuring compliance with relevant privacy regulations. A strong governance framework protects both your organization and your partners.
3. Choose the Right Partners. Carefully evaluate potential clean room providers based on your technical requirements, industry expertise, and scalability needs. The right partner should align with your long-term data strategy and business goals.
4. Start Small and Scale. Begin with pilot projects to prove value before expanding clean room usage across your organization. This approach allows you to identify and address any implementation challenges early on, refine your processes, and build internal expertise. As you demonstrate success, gradually expand to more complex use cases and larger datasets.
5. Prioritize Data Quality. Ensure your first-party data is well-organized, accurate, and properly formatted before ingestion into a clean room. Clean, standardized data is crucial for effective matching and analysis. Regular data quality checks and cleaning processes will help maintain the integrity of your information throughout the clean room lifecycle.
6. Invest in Training. Educate your teams on clean room best practices, privacy-preserving technologies, and relevant regulations. This includes not just technical staff but also marketers, analysts, and decision-makers who will be working with clean room insights. Ongoing training ensures your organization can fully leverage the capabilities of your clean room while maintaining compliance and data security.

By following these best practices, organizations can set themselves up for success in implementing and utilizing data clean rooms effectively, unlocking new opportunities for data-driven marketing while upholding user privacy.

The Future of Data Clean Rooms

As privacy regulations evolve and third-party identifiers fade, data clean rooms are becoming an essential player in digital advertising. The IAB Tech Lab’s recent interoperability standards promise to accelerate industry-wide adoption, while advancements in AI and machine-learning will revolutionize clean room analytics -- enabling unprecedented audience modeling and predictive insights. Moreover, the use of clean rooms is expanding beyond advertising into sectors like healthcare and finance, where secure data collaboration is equally critical.

In this shifting landscape, organizations that understand the capabilities, limitations, and best practices of clean rooms will be best positioned to lead with privacy-first, data-driven marketing strategies that deliver meaningful impact in an increasingly privacy-conscious world.