“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Peter Vandre, chief analytics officer at Dentsu Aegis Network Media.
The idea of a safe place where marketers can analyze sensitive data has been around at least since the early 2000s. Banks used credit data for direct marketing purposes, for example, but had to comply with new payment card industry regulations. And the healthcare system’s Health Insurance Portability and Accountability Act created patient rights to protect the privacy of medical records.
Walled gardens have brought back data clean rooms to selectively share some of their own data with brands under very limited use cases, within environments they tightly control. As Google increasingly curtails access to user-level data outside its Ads Data Hub, brands will be forced to seriously consider putting more data into the clean room environment for campaign measurement and analysis.
The data clean room concept is becoming synonymous with walled gardens, but with emerging regulations, it may not be practical for brands to analyze marketing data within walled gardens alone. In a private data clean room, it’s possible to establish a secure and privacy-compliant data environment that facilitates individual-level insights, measurement and targeting at an enterprise level.
The private data clean room
Data clean rooms can simplify privacy compliance. No PII is contained in the environment, and the enterprise can’t reverse the data to PII. This can greatly reduce the amount of consumer data that is subjected to regulations such as GDPR and CCPA, and many enterprises are already turning to data clean rooms for this purpose.
These data clean rooms also allow companies to keep data safe without sacrificing attribution and one-to-one targeting. Walled garden clean rooms are incredibly limited today. Forget trying to do advanced attribution or any kind of one-to-one targeting. In a private clean room, there is more flexibility in tools used, how queries are constructed and even how audiences leave the clean room for activation. Secure audience transfer using hashed IDs can ensure that audiences are delivered to activation platforms without leaking identity.
Lastly, companies can benefit from securely sharing second-party data. With the cookie dying, marketers and publishers are turning to more persistent identifiers, such as hashed emails, as a way to exchange audiences. CPGs and manufacturers are looking for ways to get closer to customers through data-sharing partnerships with retailers. Data clean rooms can help with this data integration and governance.
The primary technical challenges of private data clean rooms are ensuring sensitive data is appropriately filtered and records are keyed to “safe IDs.” These safe IDs can exist at an individual level, but they cannot be directly joined to any outside identifiers. Brands must also ensure that no one on staff can directly match any of these safe IDs to data in any other environment. This separation is vital to the clean room concept.
Perhaps the greater challenges of setting up private data clean rooms are organizational. Beginning a clean room project requires broader organizational alignment around data governance. By design, restrictions will be put in place for the type of data that can be accessed in the clean room and by whom. Brands must establish rules for what data can enter the clean room, how that data is combined and under what circumstances data can leave. Understanding the analytics use cases for the environment is also critical to setup.
A way to overcome some of these challenges is to involve IT and legal teams at the onset of the process to decide on the best environment to host the rooms. Compliance laws and policies can be different for private and public companies, and it’s critical to assess these when developing a clean room environment. For example, appropriate governance rules for who can access data within the environment and other institutional processes can impact success.
The days of dumping data into a data lake and slapping some analytics tools on it are coming to an end. In this emerging world of heightened privacy and data security, the private data clean room is an important consideration for enterprises requiring more control of their analytics.