Data Clean Rooms (or DCRs for short) are becoming a foundational technology in the modern, first party data-driven landscape. As third party identifiers continue to crumble, collaboration between different parties with value-adding first party data will be a key lever for scaling data-driven marketing use cases.
While Data Clean Rooms are well covered in western markets, they’ve yet to gain much traction here in APAC. As such, the goals of this deck are to provide a high level overview of how Data Clean Rooms work as well as an exploration of key concepts to further build and reinforce understanding. This includes the following:
- How Data Clean Rooms work
- The data matching process
- Conceptualising how Data Clean Rooms facilitate use cases
- Identity Graphs in Data Clean Rooms
- User data models in Data Clean Rooms
- Privacy Enhancing Technologies (PETs)
- Data Clean Room categories and types
- Data Clean Rooms as a platform or product
For additional context and commentary, we highly recommend viewing the accompanying video for this guide.