Data Clean Rooms, What are they, and how do they work?

Companies worldwide are increasingly attempting to capitalize on data's opportunities while also safeguarding it to protect consumers. The data clean room is a data management concept designed to assist customers in maximizing security and utility. Consider clean data rooms to be a warehouse where a company can store aggregated advertising data gathered from various sources and later pool it with first-party advertiser data to analyze trends without jeopardizing security controls.

Businesses use data clean rooms to understand the performance of their advertising better. Data clean rooms provide a secure and controlled environment to process and store personally identifiable information (PII) for various analytics purposes according to privacy regulations.

How does a data clean room function?

Creation

Data clean rooms are created by collecting user-level first-party data such as transactions, customers, or media and storing these in a secure environment.

Encryption

After data enters a clean room, clean rooms secure and encrypt all data, protecting it from any access beyond that warranted by the data owner.

Accessibility

Clean rooms are accessible to brands without restraint; their clients receive completely anonymized data that complies with all regulations.

Why is a data clean room used?

Data clean rooms ensure that parties entering into the clean room agreement agree on the right of access and usage. The clean room service provider is responsible for adhering to the terms of the agreement. Protecting personal data improves the privacy of a data clean room, and organizations can comply with laws such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

Many advertisers and marketers spend a significant portion of their advertising budget on platforms like Amazon Marketing Cloud (AMC) and Google's Ads Data Hub (ADH). Organizations are becoming more aware of clean rooms to understand their customers better, fill gaps by targeting previously untapped potential customers, and analyze consumer behavior, ad campaign efficacy, and user score analysis.

Data Clean Room Applications

Data clean rooms help businesses stay compliant and competitive by giving them complete control over the clean room environment and using secure data without restrictions. Typically, data clean rooms are used to:

Anonymization:

Data can be anonymized at the user level and used to measure a clean room. Encryption and hashing techniques ensure data security at all stages of data usage.

Compliance:

With built-in privacy compliance for regulations such as CPRA, GDRP, CCPA, data clean rooms are an efficient way to meet these requirements.

Analysis:

Data clean room usage includes customer analysis of their lifetime value. Users can do customer-level analysis to understand customers' overall value, both in terms of their consumption and the process of dealing with your organization.

Data Clean Room Challenges

Ideally, data clean rooms would be a perfect solution that every company would adopt at once. But there are some disadvantages too.

Budget:

A Data Clean Room is an expensive solution since it's a distinct environment managed by a third party. The cost of building one and the ongoing cost of hosting data is a pricey affair.

Privacy:

As much as platforms need to share data for data clean rooms to succeed, advertisers should also do their part. By migrating PII customer data to a third-party data clean room provider, data owners are exposing themselves to the risk of a data breach.

Fall-outs:

Data clean rooms will determine a minimal number of users before sharing the aggregated results with business units. This is limiting when a business advertises across multiple platforms since it is impossible to join the data to build a holistic picture of how customers interact.

Data Clean Room Best Practices

• Following are a few best practices that you can follow whether you're setting up a data clean room or improving the current one to ensure that you maximize its value.
• Data clean rooms should be designed to anticipate how consumer behavior will shift in the future, rather than just thinking about today.
• It is equally essential to analyze consumer behavior in real-time with an adequate data clean room. Analyzing consumer behavior in real-time will yield invaluable insights.

Remember that the goal of a data clean room is to see how the market is performing and how you can improve it. It is possible to construct, control, and set up a clean room solution with the right expertise to the best of one's ability.