Data clean rooms 101

Learn about data clean rooms, data collaboration, and how they can benefit your business

What is a data clean room?

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. 

Why is there a need for data clean rooms?

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.

Enhanced user privacy protection

 

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.

 

Minimized impact of cookie deprecation

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.

Secure collaboration with data partners

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.

Why haven’t data clean rooms been more widely adopted?

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.

Benefits of using data clean rooms

So far, we’ve discussed how clean rooms offer a highly secure environment for data sharing with strict privacy regulations while eliminating the need to share consumer data with partners. We’ll elaborate more on the reasons brands are using data clean rooms below.

Manage your own privacy controls during collaboration

Clean rooms empower businesses to manage their own privacy controls. This ensures their data remains protected while permitting data analysis collaboration. Having this level of security and privacy protection makes data clean rooms an attractive solution for brands seeking to gain insights, share information, and collaborate with partners while prioritizing data privacy and compliance with data protection regulations. No consumer data leaves the clean room, and brands do not have to share their first-party data directly with their data partners.

Achieve high match rates during collaboration

High match rates are essential for deriving actionable insights and for the success of clean room use. Brands are always looking for ways to improve their data collaboration outcomes in clean rooms. When you choose Experian as a collaboration partner, we can help you achieve higher match rates and maximize your results from clean room investment. Businesses can leverage our diverse range of digital identifiers and expertise in adjusting which identifiers to match on. This capability enhances data matching precision and ensures data from different sources align more accurately. 

Advanced analytics

Within clean rooms, businesses can conduct more in-depth analysis by combining diverse datasets to gain a deeper understanding of customer behavior and audience insights. This results in better, more comprehensive reporting to uncover the true reasons why a project was successful, or to identify areas that can be improved next time. The collaborative nature of data clean rooms helps brands gain full performance insights, refine their strategies, and make data-driven decisions with greater accuracy.

Improve audience targeting

Data clean rooms empower businesses to enhance their audience targeting capabilities through the comprehensive consumer and audience data that can be gained from collaborating with partners. This data allows brands to build better, more accurate audience profiles — and with improved audience targeting, they can create highly personalized marketing efforts. The outcome is increased engagement, conversions, and overall marketing effectiveness.

Collaborate on data insights

Brands are turning to data clean rooms to collaborate on first-party data insights and harness more robust data for their business goals. With data clean rooms, brands can access a wealth of data that empowers them to enhance their marketing strategies and decision-making processes.

This collaborative environment allows brands to merge and analyze data from various sources so they have a more comprehensive view of their target audience and market trends. The result is a higher level of precision in marketing efforts, enabling businesses to deliver more personalized, effective, and data-driven outcomes. Ultimately, clean rooms facilitate collaboration to help marketers access the full potential of data insights and give them a competitive edge.

benefits of data clean rooms

Use cases and applications of clean rooms

Clean room collaboration offers versatile applications that empower you to make data-driven decisions, including:

Insights

Data clean rooms enable you to inspect, mine, and model comprehensive data, fostering the discovery of valuable information and suggesting actionable conclusions. You can gain a better understanding of your target audience and market trends.

Segmentation

The insights that you gain through clean room collaboration allow you to identify cohorts with shared characteristics within your client data for in-depth analysis. This segmentation can help you refine audience strategies and tailor campaigns to specific customer preferences and behaviors.

TV targeting

Clean rooms enable users to leverage insights and segments for addressable TV marketing. You can precisely target your audience with this approach for optimized TV advertising efforts.

Attribution and measurement

Clean rooms are instrumental in attribution and measurement. They enable you to gain the full insights you need to carefully evaluate campaign performance and craft relevant reports to gain a holistic view of effectiveness from your marketing efforts. 

Digital advertising and marketing optimization 

Experian's clean room partners support various aspects of digital advertising and marketing optimization, including dynamic creative optimization (DCO), site side optimization (SSO), and bid optimization. These features enhance the effectiveness of your digital marketing campaigns and lead to improved audience engagement, conversions, and overall marketing efficiency.

Types of data clean rooms

Clean rooms come in various types, each tailored to different data collaboration requirements.

Third-party clean rooms

Third-party clean rooms are secure environments for data collaboration that are managed and operated by a third-party entity separate from the organizations providing the data. These clean rooms serve as neutral grounds for data analysis and collaboration, particularly when multiple organizations or stakeholders need to work together on data-related projects. Some good examples of third-party clean room partners we work with include Infosum, AWS, and Snowflake.

Traditional data clean rooms vs. distributed data clean rooms

Traditional data clean rooms confine all information within a single location, imposing restrictions on its sharing capabilities. Distributed data clean rooms, on the other hand, have emerged alongside cloud technology to eliminate the need for data transfers between locations. Drawing on the power of cloud storage, partners can now retain complete control over their respective datasets while seamlessly engaging in collaborative analysis with other stakeholders. 

What’s the difference between a CDP and a data clean room?

While customer data platforms (CDPs) and clean rooms both organize data that help you get to know your customers better, these tools also have some important differences to be aware of. Ultimately, they are used for different purposes.

A CDP is a customer-focused platform that consolidates known consumer data to enhance customer relationships and personalization. The purpose of a CDP is to collect and analyze known customer data so you can fill in the information gap on your current customers. Clean rooms, on the other hand, are secure environments that allow two companies to enrich their first-party data with the other’s. This data collaboration draws on anonymized data so that two partners can gain deeper insights while adhering to data privacy laws. Insights derived from clean room practices may be used to enhance targeting, measurement, research, and more while complying with strict regulations. Both tools play crucial roles in data-driven marketing and customer engagement.

Challenges and limitations of data clean rooms

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.

Data privacy and security concerns

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.

Technical challenges with matching

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.

Limitations in data analysis

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.

Why identity resolution is needed in data clean rooms

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.   

Real-world example and case study of clean room collaboration

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.

data clean room collaboration case study use case

Key takeaways about data clean rooms

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.

Partner with us to start collaborating in clean rooms today

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.

We can help you get started with data clean rooms

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