A data clean room is a secure, encrypted location where first-party data can be anonymized and matched with aggregated second-and-third-party data from trusted partners and publishers to perform analysis. Only the aggregated data is analyzed, with no way to revert the data to its original data set. This ensures the confidentiality of the first-party data.
What Does a Data Clean Room Do?
Data clean rooms are not new, but they have been given a new life due to the diminishing third-party cookie.
As third-party cookies come to an end and data privacy regulations continue to evolve, companies are challenged with developing a deeper understanding of their customers and how their marketing and advertising strategies are performing. A data clean room is a safe way to gather the data they need to resolve these challenges.
With a data clean room, you can:
- Identify ad performance and where you are wasting ad spend
- See where you are duplicating efforts across channels
- Understand how customers are interacting with your brand
- Identify lookalike audiences, or define new segments for targeting
- Find new opportunities to reach and engage with customers
- Determine customer lifetime value
- Find ways to work with partners to build joint marketing programs
Types of Data Clean Rooms
There are several types of data clean rooms. It’s essential to understand the differences between each one.
Walled Gardens
The most well-known data clean rooms are from the large tech companies that provide advertising services, like Google Ads Data Hub and Amazon Marketing Cloud.
These walled gardens - closed ecosystems with complete control over their network and data - give an advertiser limited access to aggregated customer data so they can analyze how their advertising is performing. Companies only have access to their data, not their competitors’ data.
They cannot bring in data from other locations to get a complete view of advertising performance (hence the term, “walled garden”). Depending on the publisher, there may also be restrictions on how big the datasets are to analyze.
AdTech Vendor Data Clean Room
Some adtech vendors offer data clean rooms similar to Google and Amazon. These are also walled gardens, meaning a company can only get access to their data from the vendor and the vendor has complete control over what aggregate data is provided and how it can be queried. One of the challenges with these rooms is that it can be difficult to determine the validity of the attribution model, so the company can’t be sure they are measuring against the correct data.
Agency Data Clean Room
Several agencies provide data clean rooms that enable a company to connect their first-party data with multiple third-party data sources, including ad networks and demand-side platforms. These data clean rooms would not include data from the walled gardens mentioned above.
Private Data Clean Room
Companies can create their own data clean rooms with complete control over where the space is located, how it’s secured, and how the data is imported and matched up. Also called a partner data clean room, the company can work with multiple partners to bring in their data, anonymize it and match it up, giving all parties the ability to query the dataset. Each partner retains control over how their data is used in the data clean room.
In most cases, data never leaves the data clean room, regardless of what type of data clean room is employed. However, there are examples where segments or target lists can be exported out to use in an ad network, a customer data platform or demand-side platform for marketing and advertising purposes.
As more companies look for new ways to improve ad performance and overall customer experience, they will likely use more than one type of data clean room to ensure they are measuring the performance of all their marketing programs.
FAQ
What is the difference between a data clean room and a CDP?
A data clean room is a secure environment for analyzing aggregated, anonymized data from multiple sources (often including partners or ad platforms) without exposing raw data, while a CDP stores and activates identified customer data for personalization and targeting. Data clean rooms are primarily used for measurement, attribution, and insights across partners, whereas CDPs focus on creating unified customer profiles for direct engagement and activation.
Why are data clean rooms important in a privacy-first world?
Data clean rooms enable companies to gain insights and measure marketing performance while maintaining strict privacy controls and compliance with regulations like GDPR. They allow analysis of combined datasets without exposing individual-level data or sharing raw customer information between parties. This makes them essential for collaboration with partners, walled garden platforms, and publishers as third-party cookies disappear.
Can data from a data clean room be exported for marketing use?
In most cases, data never leaves the data clean room in its raw form to protect privacy and confidentiality. However, some data clean rooms allow aggregated insights or specific segments and target lists to be exported for use in advertising platforms, CDPs, or demand-side platforms for marketing and advertising purposes, provided the data remains anonymized and meets privacy requirements.
Related Terms
- Cookieless Tracking — Privacy-preserving tracking methods that complement data clean room strategies
- Data Onboarding — Process of matching offline data to online identifiers, often used alongside clean rooms
- Data Governance — Policies and controls that govern how data is managed within clean room environments
- PII (Personally Identifiable Information) — The sensitive data that clean rooms are designed to protect and anonymize