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How clean are Clean Rooms anyway?
A Privacy-enhancing Technology: Friend or foe?
I often wonder who first came up with certain words or terminology to describe something – anything.
Every term we know was first coined by an individual or a group, correct? Someone must have first uttered the word "data" to describe a particular something (and I wonder whether they went "day-taa" or "daa-taa" or maybe something else altogether).
That brings us to the topic of today's track: Data Clean Room (DCR), a privacy-enhancing technology (PET).
Data Clean Rooms
The physical Clean Room was invented by a certain Willis Whitfield in 1962 to prevent dust particles from contaminating nuclear weapon components (source). It's unclear who but someone surely first thought of building the digital version of this physical device and aptly labeling it a data clean room.
Anyhow, before we get into why this new piece of data tech is gaining momentum and who was the first to commercialize a DCR, I'd like to offer a simple definition:
A data clean room enables two or more organizations to combine and enrich their respective first-party data sets without sharing unnecessary data points (such as PII or proprietary data), thereby staying compliant with privacy laws.
But is it really that simple? Let's find out.
You might already know that at databeats, we always strive to present both sides of a story while maintaining a neutral point of view. In fact, our entire premise is to bring people with diverse perspectives together – to find common ground and beat the gap for good.
I've personally learned a lot from folks building new tools and tech, and that includes the CTO of Habu (a Data Clean Room vendor) who answered some fundamental questions about DCRs in a sub-ten-minute episode.
You can watch or listen to the conversation, or if you prefer to read (like me), you can go through the key takeaways.
Jon Keegan, an investigative journalist at The Markup, interviewed Daniel Goldberg, a privacy lawyer and member of the IAB (Interactive Advertising Bureau) to dissect the DCR tech and highlight some of its privacy concerns. I'm glad that Daniel highlights the fact that every clean room vendor operates somewhat differently and that the devil is in the details.
P.S. The Markup is a publication I recommend if you'd like to understand how institutions are using tech to change the way society operates.
"Privacy is the core responsibility of data collaboration and data clean room solutions." – Jeffrey Bustos
Jeffrey, who's a VP at the IAB, makes a compelling argument that supports Daniel's POV that DCRs are no silver bullet and the tech is subject to what the vendor is actually doing:
In Jeffrey's words, "Data clean rooms must provide full transparency and remove the need for any data to move, enabling permission controls that allow each party to dictate how their data is matched, analyzed, and activated."
I think the best way to understand emerging technologies is to dig into use cases.
Therefore, I was glad to find Jeffrey's guide where he describes how retail media networks (owned or third-party advertising channels made available to brands by retailers) leverage data clean rooms to work with brands, and what that process looks like.
If you'd prefer a quick summary of the key benefits of data clean rooms for both retailers and brands, here you go:
CPG (consumer packaged goods) brands are able to identify unique and overlapping audiences across a retailer's properties, enabling retailers to expand revenue
The advanced audience-building and measurement capabilities offered by DCRs are attractive to CPG brands for audience extension purposes
Retailers are able to add new revenue streams by leveraging the data they already collect and own
It's not surprising but it's definitely ironic that the first company to offer a commercial Data Clean Room, a privacy-enhancing technology, was Google – with its launch of the Ads Data Hub in 2017 (source).