Data Clean Room

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 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.

Amy Onorato
Amy Onorato
Amy Onorato is the Managing Editor of and Senior Content Marketing Manager at Treasure Data. Prior editorial and creative roles include journalism, content marketing and content strategy for CBSNewYork, Newsday, DMN, and Publicis Sapient.

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