What brands need to know to jump into the 'clean room' conversation

Today, the digital industry is going through the much-needed process of redefining the meaning and legal implications of data privacy. Data clean rooms have emerged as a compelling means of sharing data between businesses and drawing valuable insights for running successful, scalable ad campaigns. In Australia alone, there are up to 500 clean room deployments either active or preparing to be active. Good timing: Australian privacy legislation is currently under review, aimed at bringing Australia up to speed with global standards for data privacy. Brands in the APAC region should consider this an alert to prepare their tech stacks to ensure data connectivity and portability in the present and the future. 

The market conditions that make data clean rooms so enticing are global. And yet, their rate and manner of adoption aren’t consistent around the world. Brands would benefit from the support of a “clean room concierge,” who can help find the right proposition for their needs, based on their observations of markets where clean room adoption is at a more mature level. While many brands are letting their agency partners take the lead on clean room strategy, they still need the right knowledge to take part in these conversations.

One size doesn’t fit all

Let’s remember what’s really at stake in the face of third-party cookie deprecation: The data connectivity that allows a brand’s core marketing initiatives to thrive. The choice of a clean room carries great impact for the business. A concierge who truly understands the landscape will note that clean rooms, at this stage, can be sorted into four distinct categories:

• Walled Gardens: This is the most common variety of clean rooms, with many APAC agencies encouraging brands to implement solutions like Google. These environments offer straightforward implementation, but can also be customised by a data scientist. The data that goes into a walled garden clean room will generally stay there. And yet, brands should take note that walled gardens may not offer sufficient solutions forever— their utility depends on how data policy evolves and how each walled garden responds. This variety of clean room is suitable for activation, suppression, measurement, and attribution.
   
• Data Warehouses/Clouds: Just as Snowflake is built on top of Amazon Web Services, these clean room functions sit on top of a data warehouse or cloud, where the business’s data lives. The data is moved to the clean room, along with the partner’s data. The tools here can be customised considerably by a business that has the internal engineering and data science resources to do so. 
   
• Data Collaborations: These are environments where the marketer’s data can be combined with a common identifier, utilising an identity spine to ensure privacy. The marketer uploads the brand’s first-party data, and the collaboration conducts the matching. Unlike walled gardens, they allow marketers to activate outside of the collaboration environment. Because they’re designed for activation and for supplying insights, they’re also fairly straightforward to implement. Beyond activation, they’re especially useful in data analysis and enrichment, and monetisation.
   
• Queries: A query clean room connects multiple clean rooms or data warehouses, providing a neutral environment. The business’s tech team oversees it, and handles data orchestration among any participating partners. While the brand will need to take on some of the technical work, a marketer with some tech skills and training would be able to assist. Query clean rooms can accept any common identifiers of choice, and they’re especially useful in analysing overlap. 

It starts with a strong first-party data strategy

An education shortage isn’t the only reason why so many APAC brands are hesitant to lead the charge toward data clean room adoption. There’s also the first-party data shortage. Many brands are still occupied with identifying and collecting the right data required to drive a strong first-party data strategy. Even those with a strategy spelled out may not have scalable volumes of first-party data. Brands and their agencies must do their privacy-related due diligence together, as regulations become more stringent in the region. And brands themselves need to start asking questions about which varieties of data clean rooms will suit their needs. A few key questions to ask:

• Where is your data currently housed?
• What does the data represent? For example, how much is authenticated, and how much comes from unknown browser-based and in-app actions?
• Which identity solutions will you and your partners use?
• What is your use case? Can the clean room environment in question support your varieties and locations of data, and the particular identity solutions in play?

Now is the right time to get proactive about clean room vetting

Brands need to take the discussion around data clean rooms and turn it into action. Priorities right now must include refining a sustainable first-party data strategy, understanding privacy regulations and being proactive rather than reactive, and testing clean room solutions. Marketers and brand leaders should watch for new data clean room standards coming from the IAB U.S. There’s a lot to be learned about gaining the most value from the right type of clean room, and to remain competitive, brands will need to get up to speed fast in order to truly get started on the right foot.

 

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