Beyond the Buzz: data clean rooms

With privacy front and center in the quest for the optimal customer experience, data clean rooms are having a moment right now. But what are they, exactly? And can they live up to the hype? Here’s what you need to know.

Nicolas Lierman
Nicolas Lierman

Utopia for marketeers?

Cleanliness is next to godliness. In the digital realm, respecting user privacy while also offering excellent customer experience seems to be a challenge of almost Biblical proportions, with ever-more stringent regulations and the imminent demise of third-party cookies. Which is why ‘data clean rooms’ are having a moment right now. But are they really the solution to everything, or just a hyped-up workaround? Here’s what you need to know.

In the time of Siegert and Philippe, (personal) information on the internet roamed freely, and almost every website used cookies to offer personalized experiences. Privacy was just a vague concept no one really cared about. That mindset has changed drastically over the last couple of years, however, and new policies like GDPR and CCPA were implemented to protect user privacy. In addition, companies like Apple, Amazon, Google and Facebook are closing off their data troves or walled gardens and commit to getting rid of tracking technologies.

Match and measure

  • Now, you might wonder how on earth brands can still respond to customer expectations in a privacy-safe manner? The answer – according to the believers, at least – are data clean rooms. In this secure, privacy-first environment, brands can match their first-party data with a partner’s data for analysis, targeting and measurement.
  • Important to note is that these ‘partners’ can be big tech heavyweights like Facebook and Google, but also local brands, companies, and organizations. In the first case, Big Tech shares its aggregated data and still exerts strict control. Brands can see how their first-party data relates to external data, spot inconsistencies, and make useful predictions.

The case for cooperation

The second scenario is an altogether different story, in which two or more companies set up a cooperative clean room to share useful data in a privacy-compliant way. This could open up entirely new opportunities for market segmentation. Imagine, for example, a supermarket knowing what kind of foods are most popular during a big soccer game.

Sounds like a great idea, right? The truth is that data clean rooms are utopic at best (in the case of brands cooperating) and a distraction from the ‘real’ problem of digital advertising at worst. The ‘cooperative’ clean rooms, for example, lack the standardization required for efficient data matching. How, for example, can you be sure that the way one company identifies a customer is completely compatible with the way someone else does it?

The dirty side of data clean rooms

But there’s a more perverse effect at play here as well. Brands are paying Big Tech big money to get access to their ‘walled gardens’. This means that marketeers aren’t just paying to reach their own customers within the Facebook or Google environment, but also to reach customers outside of those environments.

Which is exactly why companies should focus their efforts on obtaining as much first-party data as possible. Doing so, of course, requires a drastic mental shift and an absolute commitment to data quality. However, it is also the only way in which we can build an internet where customer privacy is truly respected, and users get the agency they deserve over their own data.

The truth is data clean rooms are utopic at best and distract from the real issues with digital advertising at worst.


You’ve guessed it: MultiMinds is a party-first company – or a first-party data company, whichever you like most.

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About the author

Nicolas Lierman

I translate abstract and often complex ideas into elegant solutions. Combining a strong technical skill-set with a visual mind, I strive to deliver products that really speak to the customer.