Clearing Up Data Clean Rooms

Keeping up with adtech jargon can sometimes feel more impossible than collecting all the infinity stones (although, thankfully, far less dangerous). Everyday a new acronym seems to pop up and annually some sort of new tech emerges. The DMP talk that ruled our world a decade ago, gave way to CDPs, which are currently being supplanted by chatter around Data Clean Rooms. Now you may be thinking “I already clean my datasets as part of my ETL process”, but this new technology has nothing to do with cleaning data! This term is derived from engineering clean rooms, or rooms that are isolated and well-controlled from contamination, and commonly needed for scientific research. Confused? Let’s dig in and help demystify the tech!
So what is a Data Clean Room in the advertising sense? A Data Clean Room is privacy enhancing technology that allows for secure data collaboration between partners. The main purpose of a Data Clean Room is to mitigate consumer privacy and data security risk, while maintaining critical marketing and media use cases. Please note this is not the same thing as a Data Safe Haven! A Data Clean Room allows for sharing data with trusted 3rd parties, whereas a Data Safe Haven refers to a secure and controlled environment in which data can be stored, processed, and analyzed without leaving the protected warehouse.
Still confused? Consider this metaphor: let’s say you have a bunch of secrets and I have a bunch of secrets. We want to talk about any secrets we have in common, but we want to stay mum on any secrets that only you or I uniquely know. How can we both determine the secrets that we have in common, as well as find a way to share with each other further details regarding those secrets, but only those secrets? Well, we go to our most trusted friend, share our lists of secrets with them, and our good friend will notify us of which secrets we’re safe to discuss in more detail, while never revealing any of the non-overlapping information.
data clean room diagram 
Now that we better know what a Data Clean Room is, why would we want to leverage one? The technology really provides three core services: 
  1. They protect data custody, crucial for allowing data matching without the need to move data or unduly share with 3rd parties
  2. Identity/PII is not leaked, as linkages of individuals cannot occur 
  3. Attributes cannot be appended at the user level, which guarantees differential privacy
While data sharing is becoming table stakes in our ever more data connected world, both ethical and legal concerns demand that maintaining control over your data, as well as respecting PII, always has to be at the forefront of any/all data conversations. Data Clean Rooms provide the ability to share data between partners, with the benefit of also providing that crucial ownership and control of the data, which is the only way to ensure you are truly respecting privacy.  
At this point you may be wondering about how your organization might leverage a Data Clean Room. In general, there are four main use cases for Data Clean Room adoption: 
  1. Customer Profile Enrichment ie “how can I better understand my customers with third party data?”
  2. Audience Overlap Analysis ie “how many customers overlap between two brands?” 
  3. Campaign Measurement & Attribution ie “how did my campaign perform based on my data and my partner’s data?”
  4. User Scoring Analysis ie “how likely are my customers to engage with another company’s product?” 
All of which provide extremely valuable consumer insights to your brand. 
If you’re thinking “these are all valuable insights, but they seem like nice-to-haves instead of need-to-haves”, in the short term I actually agree. Data Clean Rooms are a somewhat nascent technology in the advertising space and, considering many smaller brands haven’t yet developed a solid first-party data strategy, much less integrated with a DMP or CDP, investing in a Data Clean Room would absolutely be the equivalent of a freshman enrolling in a 400 level class. However, long term every brand needs a first-party strategy, that 1PD needs to be managed somewhere, and, faster than you know, strategically disclosing parts of that 1PD to trusted partners will be just a matter of regular business. 
How do you know if your company’s data maturity journey is ready to climb to the next vista? Firstly, your company has collected an “analyzable amount” of first party data related to your campaigns and/or customers (this amount is hard to define without digging into your specific business needs). Secondly, that data is stored in a cloud environment. Thirdly, your company has defined sharing use cases that either provide direct financial value in and of themselves, or use cases that will further business in a way that will provide direct support to the financial bottom line. Data (and the technology that supports it) is only as useful as its use case, so while you will be technically unable to move forward with a data clean room without establishing the first two points, investing (not insignificant) resources into a data clean room is pointless without having a very good idea of your objectives going in. 
Still confused? It’s very understandable as bringing your company into a state of complete data maturity is quite the mountain to climb! That being said, there will never be a better time to get started and I’m here to help. Please reach out for a data strategy consultation today!