Increasing privacy restrictions and deprecation of cookies warrant marketers to innovate and thoughtfully use customer data for audience activation and media measurement. Brands have
been collecting and building data lakes to house 1st party data are now using innovative
technologies like data clean rooms for data collaboration.
What is a Data Clean Room?
A data clean room, in simple terms is a privacy-safe box that facilitates data collaboration between multiple entities. The beauty of data clean room implementations is that it provides the data owner’s full right on what data they are willing to share and the granularity of data that they want to share.
They could pull off the clean room instance at any given time.
The ability to write custom queries and advance modelling for data segmentation and insight generation is made possible in a data clean room.
Data clean rooms make seamless data enrichment capabilities possible as multiple parties can share 1st party data in a privacy-safe collaboration space.
The current landscape of data clean room infrastructure providers is split into two:
Walled Garden Clean Room (Safe Rooms)
These are owned by dominant industry players who provide solutions like Google Ads Data Hub (ADH) and Amazon Marketing Cloud (AMC). Also, Facebook is building something that is in beta, so more to come there!
Neutral Clean Rooms
These clean room providers are partner-agnostic and can easily integrate and work with any publisher, brand, or data partner. HABU, Infosum and Snowflake are data clean room providers.
Top Three Benefits of Using Clean Rooms for Data Collaboration
It is still early days, and data clean room adoption is in nascent stages, but there is opportunity!
Brands will adopt more of this either through publisher owned clean rooms or neutral cleans rooms.
1. Privacy Control
All large organizations aren’t comfortable sharing their 1st party data, data clean rooms provide an innovative approach where there is no actual movement of data, but data is accessed at run time for a particular use case.
2. Audience Targeting and Personalization
Data clean rooms provide the ability for brands to target the right audience and enable personalization with audience matching and activation.
3. Measurement and Advanced Analytics
Data clean rooms provide the ability to do granular data analysis like audience overlap, optimal frequency and data segmentation.
*There might be more data clean rooms introduced recently but I haven’t explored these, so they are excluded in my article.
