Data clean rooms 101

A data clean room is a privacy-focused technology service or software that protects data privacy while facilitating data collaboration among brands and advertisers. This secure and controlled environment ensures compliance with privacy regulations like GDPR and CCPA by anonymizing personally identifiable information (PII) and providing you with non-personally identifiable information for demographic targeting and audience measurement. 

By using the data from your clean room collaboration, you can execute more targeted advertising campaigns, implement frequency capping, measure campaign performance, and perform attribution by combining first-party data with aggregated data from other sources. 

Clean room technology helps to balance the demands of data-driven insights, audience targeting, and collaboration with the importance of user privacy protection. It offers a path forward that respects user preferences, navigates the changing data collection landscape, and ensures data-driven initiatives are effective and ethically sound.

With growing data privacy concerns, it's essential to keep users' personal information safe. Data clean rooms provide a means to process and share anonymized PII data, allowing you to use combined insights to do things like target specific demographics and measure audience engagement without compromising individuals' sensitive information. Users can engage with digital platforms and advertising providers with greater peace of mind, knowing their personal information is protected.

Third-party cookies are being phased out, which has presented a significant challenge for digital advertising and data analytics. Data clean rooms offer an alternative way to get deeper, more comprehensive insights without cookies. By creating a secure environment for data collaboration, clean rooms can help you continue to collect valuable data without relying on third-party cookies.

A clean room is a trusted platform for multiple parties to enrich their first-party data. This controlled environment protects sensitive data while enabling insight and information exchange among partners. In an era where consumers are increasingly vocal about their desire for stricter data privacy, data clean rooms allow you to align with these heightened preferences. By adhering to guidelines and regulations like GDPR and CCPA, clean rooms demonstrate a commitment to responsible data handling and collaboration.

The deprecation of third-party cookies has accelerated the need for data clean rooms, and with the decline of these cookies, businesses are increasingly relying on first-party data for personalization and targeting. Data clean rooms have become pivotal for companies seeking to navigate this new data landscape, as they offer a secure and privacy-compliant environment for first-party data sharing and collaboration. 

But despite their increasing importance, several challenges have prevented the broader adoption of data clean rooms. One challenge is the lack of interoperability across different partners using data clean rooms. Collaboration partners may rely on different digital identifiers, leading to lower match rates and inefficient use of clean rooms for collaboration. Experian offers identity resolution services to help partners efficiently collaborate by resolving identity in both datasets. This ensures that two partners are each prepared for data collaboration to achieve higher match rates and full data insights. Efforts like these to enhance interoperability are key to data clean rooms’ continued growth and effectiveness.

Data clean rooms are widely used and highly useful for secure data collaboration, but they have some limitations related to data privacy, matching, and analysis.

Clean rooms must adhere to stringent privacy regulations, such as GDPR and CCPA. Maintaining compliance can be complex, as personally identifiable information (PII) must be anonymized while still providing valuable insights. Experian is a leader in data privacy compliance, which is why we have partnered with three vetted clean room providers who are committed to privacy regulations just like us. We can help you get started with privacy-safe data collaboration through one of our clean room partners, including AWS, InfoSum, and Snowflake.

Another limitation of clean rooms stems from data quality and various digital identifiers. First, data quality can vary across sources and hinder the effectiveness of data matching. Consistent, accurate data is crucial for precisely identifying and aggregating information. 

Digital identifiers also cause challenges with efficient data collaboration. Companies often use different digital identifiers, making it difficult to collaborate because there is a lack of a common language to tie data sets together. Experian’s identity resolution services works with most digital identifiers and can help you prepare your data for collaboration and achieve higher match rates.

Data clean rooms have certain limitations regarding data analysis. One limitation is their reliance on data sampling, which narrows the scope of analysis to a specific subset of available data. This restriction can potentially compromise the comprehensiveness of insights and introduce bias into findings. Moreover, some data clean room solutions may not support real-time data analysis — an obstacle when time-sensitive insights are needed for informed decision-making.

The anonymization processes employed within clean rooms also present challenges by reducing the granularity of the data. As a result, it becomes more difficult to access the finely detailed information necessary for thorough and detailed analysis. It’s essential to approach data clean rooms carefully and strategically to overcome these limitations effectively.

Consumers engage with brands across various physical locations and digital platforms, meaning the fragmentation of customer data across these different channels can be challenging for marketers to track. Each platform generates its own data stored in different formats, which makes it difficult to create a unified view of the customer. Data fragmentation can lead to disjointed customer experiences, missed opportunities, and impersonal marketing efforts — like receiving promotional emails for products already purchased. 

Experian’s identity resolution capabilities, coupled with our clean room providers, can help you achieve secure and effective matching between disparate data sets. In partnership with clean room providers, our identity resolution solutions empower you to securely collaborate with partners, extract deeper insights, and enrich your data without exposing sensitive data sets. 

When you use Experian's Graphs in your data clean room, your partner and you benefit from increased match rates. You are able to perform self-service identity resolution in your clean room, using Experian's offline or digital Graphs.   

Here are some expert predictions for the future as technology develops and clean room adoption becomes more widespread.

Changing data privacy regulations — like GDPR and CCPA — and emerging data protection laws will likely impact data clean rooms and continue to shape the landscape, demanding stricter adherence to privacy standards and data anonymization practices. Clean rooms that can efficiently navigate these regulations will be in high demand.

Technological advancements like improved data analytics tools, artificial intelligence, and machine learning are likely to shape the future of data clean rooms. These technologies will enhance the efficiency and accuracy of data matching, analysis, and insights — ultimately making clean rooms even more valuable for businesses looking to derive actionable insights from their data.

Businesses can leverage data clean rooms for various applications, from digital advertising and marketing to market research and strategic decision-making, creating numerous opportunities for providers and users. Clean rooms have tremendous growth potential; as more organizations recognize the value of secure data collaboration, the demand for clean room services will likely increase.

Retail advertisers have recognized the shift in consumer behavior toward streaming TV services, such as connected TV (CTV), over traditional TV channels. To effectively target their audiences on CTV platforms, advertisers needed to leverage their customer tiering and past purchase history datasets. Here's what happened in a real-world case study:

• Advertiser data: The advertiser has first-party data on their shoppers and has bucketed their shoppers into tiers based on loyalty. 
• CTV platform: The CTV platform has first-party viewership data on their streamers. 
• Data clean room collaboration: They decide to collaborate in their preferred clean room provider, AWS. 
• Identity resolution: For their respective IDs, they ask Experian to share our Graph in their clean room environment.
• Execution: The retailer is able to resolve their data to the CTV platform's streamer data, using the IDs shared from Experian's Graph, to create tiered audience segments for activation on the CTV platform.

In this collaboration, the advertiser enriched their data with partner CTV data without revealing their raw data to the partner. This enriched data helped them target specific CTV segments. Working with identity resolution providers like Experian, the AWS Clean Room simplified secure data joining using Experian's identifiers. This demonstrates how clean rooms help businesses collaborate securely, enrich their data, and enhance audience targeting strategies. You can read the full case study here.

Here are some important takeaways to sum up what we’ve discussed:

• Strategic consideration: Creating a data clean room is a strategy that requires careful consideration and planning for the long term. It’s vital to choose the right partner instead of the first solution that comes your way to ensure that privacy standards are being met. 
• Safe data sharing: Data clean rooms offer a secure environment for sharing data between entities and enable a more comprehensive understanding of customer behavior to support informed decision-making.
• Privacy compliance: Data clean rooms anonymize all data to eliminate compliance and regulatory risks. Brands like yours must prioritize secure and compliant data handling practices as regulatory requirements become stricter. Experian can help you ensure that your data collaboration practices are compliant.
• Extract valuable insights: Data clean rooms offer access to valuable insights beyond your data ecosystem, making them a game-changer in a competitive business environment.

Experian offers a suite of data collaboration services and boasts decades of experience in managing data privacy. We’re ready to be your trusted partner for data clean room collaboration and provide the means to conduct effective, secure, and privacy-compliant data collaboration. 

Let us empower your data-driven insights and marketing strategies while safeguarding consumer privacy so you can stay ahead in the dynamic marketing landscape. Contact us today to learn more about how we can help.