The Top 7 Data Clean Room Solutions
Explore the Top Data Clean Room Solutions known for their secure data collaboration, privacy compliance, and analytics capabilities, enabling organizations to share and analyze data without compromising privacy.
Written by Mirren McDade
Technical Review by Laura Iannini
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1.
AWS Clean Rooms
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2.
AppsFlyer Data Clean Room
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3.
Google Ads Data Hub
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4.
Habu
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5.
InfoSum
Data Clean Room Solutions provide a secure environment that allows brands to share data, while maintaining privacy. Essentially, they are protected spaces where advertisers can access aggregated, anonymized data and match it with their own information for better analysis and insights. Implementing a data clean room comes with a variety of advantages, including adherence to compliance regulations (like GPDR), as well as understanding customers to develop personalized advertising strategies.
The data clean room service industry is a competitive space with many providers offering unique solutions. Most of these solutions seamlessly integrate with modern marketing platforms, delivering features such as customizable data processing, automated data cleansing, identity mapping, and analysis tools.
This guide will explore into the best providers of data clean room services. We will evaluate their offerings, advantages, key features, and integration capabilities, to help you select the right platform for your use case.
Amazon Web Services delivers on-demand cloud computing platforms and APIs to various users ranging from individuals to governments. AWS Clean Rooms allows businesses and their collaborations to analyze shared datasets securely, without needing to copy or share any essential data.
This solution allows clean rooms to be established swiftly, enabling secure and unique insights in contexts such as advertising initiatives, investment choices, and R&D. AWS Clean Rooms offers easy setup and workflow. Users can start a clean room, invite participants, and initiate collaboration in a few simple steps. Security is ensured by a vast array of privacy-enhancing procedures designated specifically for these clean rooms. The system supports flexible SQL analysis rules and privacy-enhancing machine learning to address business needs and enables deeper customer insights by consolidating assorted data from various channels and partner datasets. It also aids in enhancing marketing and advertising experiences by enabling collaboration with promotional partners.
In addition, this solution supports improved reporting and measurement by analyzing sensitive datasets across firms and departments. It also facilitates accelerated research and development by enabling secure collaboration.
AppsFlyer is a mobile marketing analytics and attribution platform. The platform focuses on helping brands make informed business choices through its specialized measurement, data analytics, user engagement, fraud protection, and privacy-preserving technologies.
The platform offers a Data Clean Room solution which establishes a secure environment to enrich and analyze data from marketing campaigns. This solution remedies data blindness and offers a multi-channel view of networks, aligns with privacy restrictions, and augments business intelligence efficiency. Within the Data Clean Room, custom business logic empowers businesses to run distinct queries to obtain personalized information. Customizable reports facilitate tailored report configurations for a comprehensive insight into performance. The platform also grants users the ability to set a minimum limit for data, ensuring the protection of user identities and privacy.
A self-owned bucket feature grants users authority over their data including its upload, when and how it is joined, and who can access it. Simplified work processes are facilitated by a user-friendly tool for report creation. AppsFlyer’s platform delivers agile development, ensuring users receive the latest features as they are developed.
Ads Data Hub is a Google owned tool that integrates with BigQuery allowing users to merge their first-party data with Google’s event-level ad campaign data. This data can lead to valuable insights that can assist in enhancing advertising efficiency and optimizing campaigns. The results from Ads Data Hub are grouped over a selection of users, offering a comprehensive data overview while preserving end-user privacy.
Implementing robust privacy checks, the platform enables matching between first party and Google-hosted data, without compromising privacy. Users can grant Ads Data Hub access to their data, while maintaining strong privacy controls. Ads Data Hub is unique in its provision of access to events underscored by Google IDs and mobile device IDs, including publisher-specific user IDs, facilitating comprehensive campaign analysis. However, certain publisher user IDs are exclusively available for measurement, not for activation. Enhanced audience building and management capabilities are also offered via Ads Data Hub for use in additional Google Ad products. The tool also supports various first-party data links, such as mobile app data, offline transaction data, and data from a connected ID space.
Additionally, Ads Data Hub provides access to Campaign Manager 360 and Display & Video 360 Active View metrics, along with advanced YouTube viewability measurement for advertisers and agencies.
Habu
Habu is a collaborative data platform that enables businesses to unlock insights effectively and securely, without moving data. This decentralized data solution supports optimal privacy and encourages better business decisions as it allows businesses to generate answers to any question, using any tool, and any data source on a scalable platform.
Habu’s automated system and APIs are designed to maximize efficiencies and investments, while working seamlessly with business partners. With robust security protocols in place, it ensures the protection of consumer privacy, data, and intellectual property. It prevents risks associated with data movement, making data sharing and collaboration both safe and productive. Designed to be user-friendly for business users and flexible for technical teams, Habu offers a sleek, intuitive user interface, with low-code options, thereby simplifying access to insights. Their data clean room platform permits users to maintain full control over their data, while encouraging collaboration with partners.
One of the key features is its ability to provide insights drawn from a diverse assortment of data sources, ranging from private clean rooms to walled gardens, with no coding required. It works with leading platforms for activation, data and identity companies, agencies, consultancies, and major cloud platforms, effectively integrating with your existing tools and technology investments.
Habu
InfoSum
InfoSum is a data collaboration platform, specializing in secure data clean rooms. It is designed to enhance customer experiences, while safeguarding privacy. With InfoSum, companies can establish their own Data Clean Rooms, allowing for real-time matching and analysis of an unlimited number of datasets without data exposure, leakage, or misuse. This ensures optimal privacy and performance.
This platform facilitates the creation of data collaboration networks to amplify data-driven strategies such as audience planning, activation, and measurement, all under comprehensive data privacy, security, and governance protocols. Features such as decentralized data processing, multi-party collaboration, and robust privacy protection come as standard with InfoSum. InfoSum’s product suite includes Insights, Identity, Activation, and Measurement components. The Insights feature bridges internal and external data silos, providing expansive, actionable views of customers. The Identity segment improves match rates through seamless low-cost onboarding and ID crosswalks. Activation allows direct collaboration with partners and platforms, maximizing the potential of first-party data. Measurement quantifies campaign effectiveness using privacy-first metrics and advanced analytics.
With InfoSum, businesses can leverage secure, high-performing audience creation tools, transparent match rate testing, and verification of campaign reach. All these processes are conducted without sharing or copying sensitive data, offering companies a unique blend of control, transparency, and data protection.
InfoSum
LiveRamp
LiveRamp is a global data collaboration platform that delivers consumer privacy, data ethics, and foundational identity. The platform provides a clear and comprehensive view of the customer, facilitating extensive insights, while maintaining consumer and brand trust. LiveRamp’s primary offering divides into four product portfolios.
Live/Identity allows businesses to construct a robust enterprise identity infrastructure and offers a compliant identity framework with advanced identity resolution capabilities. Live/Access amplifies your data’s value, allow users to utilize custom segments and lookalike modeling for an in-depth understanding of customers. Users can buy and sell trusted third-party data in LiveRamp’s dynamic marketplace and explore new collaboration opportunities. Live/Connectivity, which is a solution for optimal customer reach, offers personalized experiences via multiple channels — browsers, mobile devices, and CTV. This is possible through RampID, an identifier designed to protect privacy while connecting the digital ecosystem. Live/Insights enables discovery of innovative insights through measurement and collaborative analytics.
LiveRamp’s clean room capabilities support various use cases and partnerships, enhanced with progressive permissioning and privacy-enhancing technologies. LiveRamp’s solutions can be embedded in any cloud, resolving identity on the client’s preferred platform, inclusive of major platforms such as AWS, Google, Snowflake, Azure, and Databricks.
LiveRamp
Snowflake is a data management company that operates the Data Cloud, where many businesses globally mobilize data with significant scale, concurrency, and performance. Within this Data Cloud, organizations are able to consolidate their data, discover and securely share governed data, as well as conduct various analytic operations.
The platform is complemented by Snowflake Marketplace, which facilitates the sharing, partnership, and monetization of extensive datasets and services, as well as complete data applications. Snowflake’s platform is designed to eliminate data silos and deliver architectural simplicity. This is achieved through the inclusion of automation features to create a unified solution for organizations to extract more value from their data. Snowflake’s platform is also optimized for various workloads, including those using SQL, Python, or other languages, ensuring scaled performance. The system’s global connectivity allows organizations to access relevant content across multiple platforms and regions, maintaining a seamless user experience. The Data Cloud model by Snowflake brings all workloads directly to the data, breaking silo structures and rapidly promoting insight generation.
The platform also accelerates AI and machine learning workflows, supports application development, provides cybersecurity measures, invites collaboration, and manages data warehouses and lakes. Snowflake’s platform is devised to be the foundation upon which data-intensive applications are built, tested, and launched, supporting overall business progress.
FAQs
Everything You Need To Know About Data Clean Room Solutions (FAQs)
A Data Clean Room solution is a controlled and secure environment within which data analysis and collaboration can be conducted, without risking exposing sensitive or Personally Identifiable Information (PII). These solutions provide organizations with a way to share and analyze data collaboratively, without negatively impacting privacy and while maintaining compliance with data protection regulations.
A data clean room is tool that is designed to facilitate the running of targeted advertising campaigns, apply frequency capping, measure and report on campaign performance, and run attribution – all done in a way that maintains strong security and privacy. This is achieved by uploading all first-party data and comparing it to the aggregate data residing in the data clean room, which has also been added by other companies.
This differs from other data partnership types where companies will exchange user-level data including device IDs, cookie IDs, ID created from hashed email addresses etc. Instead, data clean rooms will match first-party data provided by brands and advertisers but will prevent any user level data from being accessed outside of the data clean room or shared with anyone else.
When a company manages to leverage a data clean room effectively, they can create better targeted campaigns, improve understanding of audience behavior, and optimally allocate resources.
Data Clean Rooms work by asking companies to add their first party data to the clean rooms, where a variety of privacy-protection measures are then applied to the data, including restricting access, pseudonymization, differential privacy, and noise injection. Next, data is placed into cohorts, and can then be activated and used for various marketing processes included targeting, measurement, and audience analysis. Reports provided by the data clean room can be used by advertisers and publishers to improve current and future campaigns. Since privacy is a key focus of data clean room solutions, reports are based on aggregated data, meaning useful metrics like number of clicks on your ads are visible, but private user data (such as IDs) is not.
Data Clean Room solutions provide a good balance between supporting companies in reaching target audiences, measuring campaign performance, and attributing impression and click conversions, with the need to preserve user privacy. As a company, having a single, secured silo where you can analyze your customer data without breaching privacy regulations means you can make smarter, data-informed business decisions, improve campaign effectiveness, and significantly reduce ad spend wastage.
Data clean room solutions are particularly useful for organizations in need of a way to strengthen their collaboration on data analysis projects, conduct research, or share insights without risking compromising the privacy of sensitive information. These solutions work well to help organizations to strike a balance between data collaboration and privacy, allowing them to responsibly gain value from their data assets.
Some key capabilities offered by data clean room solutions include the following:
- Data Collaboration – Data Clean Room solutions offer users a framework for securely exchanging data between authorized parties. In order to ensure data is protected both in transit and at rest, these solutions provide robust encryption protocols, secure APIs, and secure file transfer mechanisms. This allows for more collaborative exploration and analysis of diverse data sets, without disrupting the integrity and security of the original raw data.
- Data Segregation and Isolation – Data Clean Rooms use an isolated environment to bring together data from various parties, while also blocking unauthorized access or inadvertent leaks. This feature works to prevent cross-contamination and unauthorized access by enforcing strict isolation measures. Access permissions and controls are enforced to ensure confidentiality and integrity of data is maintained, which contributes to a more secure and compliance environment.
- Audit Trails – Keeping an audit trail means having a comprehensive record of user activities within a secure environment, which is done via detailed logs that track actions, access, and modifications made to the data during collaborative analysis. Audit trails are employed in data clean room solutions to effectively track user activities. This then provides visibility and accountability for data interactions. These logs serve as a useful tool for maintaining the integrity of data, meeting regulatory requirements, and identifying potential anomalies or security incidents within the clean room averment.
- Anonymization and De-Identification – This involves the transformation of sensitive data to remove personally identifiable information, which ensures that identifies cannot be easily traced back to individuals. Many data clean room solutions come with built-in capabilities that work to anonymize and de-identify important and sensitive data. These capabilities support strong protection for data privacy by hiding personally identifiable information while still allowing for meaningful analysis to take place.
- Compliance Frameworks – Compliance is at the core of data clean room solutions. These solutions typically align with the relevant regulatory frameworks, including HIPAA, GDPR, and CCP. This ensures that all data handling and collaboration practices are in adherence with legal and industry specific requirements, to avoid the risks associated with non-compliance.
Written By
Mirren McDade is a senior writer and journalist at Expert Insights, spending each day researching, writing, editing and publishing content, covering a variety of topics and solutions, and interviewing industry experts. She is an experienced copywriter with a background in a range of industries, including cloud business technologies, cloud security, information security and cyber security, and has conducted interviews with several industry experts. Mirren holds a First Class Honors degree in English from Edinburgh Napier University.
Technical Review
Laura Iannini is an Information Security Engineer. She holds a Bachelor’s degree in Cybersecurity from the University of West Florida. Laura has experience with a variety of cybersecurity platforms and leads technical reviews of leading solutions. She conducts thorough product tests to ensure that Expert Insights’ reviews are definitive and insightful.