Why Data Clean Room is a Hot Topic and Why It’s More Crucial Than Ever?

For years, marketers have used consumer data from cookies, their websites, or data obtained from other data businesses or exchanges to make sure their advertising are seen by the correct audiences and to determine the efficacy of those ads.

Because cookies can be read anywhere on the internet, third-party cookies served as the primary mechanism for audience targeting, creative personalization, frequency limiting, campaign performance measurement, and attribution modelling.

The virtual cookie has now broken. Although Google is the last of the main browsers to phase out third-party cookies (until 2023), the advertising business would be significantly impacted due to its size (65% of the market share for all browsers).

Key Regulatory & Browser Changes That Aim to Eliminate the Third-Party Cookie:

Source: Publicis Groupe Deck – A Cookie-less Future: Advertiser Preparation

Marketers will still have an access to and be able to use their own first-party data, but it will be much harder to match data across networks. Instead of utilizing the cross-platform view made possible by third-party cookie monitoring, it will rely on a more thorough study on each platform.

This issue has a number of remedies, “Data Clean Room” being one of the more popular ones.

The phrase “Data Clean Room” is taken from the manufacturing sector, where a clean room is a sterile, controlled environment

What is a data clean room, and how does it work?

A data clean room is a safe, secure setting that enables marketers to combine first-party data for measurement, enrichment, and activation in a way that respects consumer privacy.

The majority of contemporary data clean rooms operate using cloud-based software as a service (SaaS) models, allowing marketers and content creators to work together.

Because there is no personally identifiable information (PII) present in these environments and neither a user nor an enterprise can convert IDs to PII, marketers are able to abide by privacy laws like the California Consumer Privacy Act (CCPA) in the US and the General Data Protection Regulation (GDPR) in Europe. Also, protecting towards the upcoming data protection bill in India.

How do data clean rooms work?

The architecture of a clean room begins with the data sources, which is relatively straightforward. Before being uploaded into the data clean room, the data is encrypted. Then, it is kept encrypted while being computed and analyzed.

The graphic below illustrates the numerous data sources entering the clean room, including ad servers, CRMs, and other data sources. But, information might also come through a variety of identification links. Demand-side platforms (DSPs) and walled-garden platforms, like Facebook and Google, are potential sources of these relationships.

Source: Spiceworks blog
  • Data is anonymized: Anonymizing the data is the first step in setting up a data clean room.
  • Data is transmitted securely: After anonymization, data can be sent to a data clean room.
  • Access controls are implemented: Access restrictions are implemented to guarantee that only authorized users can access the data.
  • Data analysis is carried out: While in the clean room, analysts can carry out many forms of data analysis, including statistical modelling, machine learning, or data visualization. The data, however, cannot be used to identify specific people because it has been anonymized.
  • Findings are securely shared: After the analysis is finished, the findings can be safely shared with other parties.

Different players in data clean room

  • Walled Garden – Google’s Ads Data Hub (ADH), the Amazon Marketing Cloud (AMC) and Meta Advanced Analytics
  • Independent Data Clean Rooms – LiveRamp Safe Haven, Snowflake, AppsFlyer Privacy Cloud, Habu CleanML, Decentriq, Aqilliz

We might assert that walled gardens, such as Google, were either the first to develop Data Clean Rooms or have had a higher rate of market adoption thus far. It, however, had restrictions because it could only activate and consume data from the Google environment.

Benefits of using data clean room

  • Ad targeting: By using a data clean room, marketers can access pertinent customer data in a safe atmosphere without invading their privacy. This data can be used by businesses to more effectively target advertising campaigns and increase client interaction.
  • Compliance: Organizations can make use of data clean rooms to make sure they abide by data protection laws. Businesses can lower the risk of data breaches and other security issues by restricting access to sensitive data.
  • Machine learning: Without disclosing private information, machine learning models can be trained in data clean rooms.
  • Marketing Analytics: The data clean room is a helpful tool for marketers to examine current data sets in order to get insightful knowledge about consumer behavior.
  • Third-Party Data Sharing: When businesses desire to share data with third-party providers, data clean rooms are frequently used. Companies can lessen the chance of data leaks and protect confidentiality by segregating sensitive data in a safe setting.
  • Data Collaboration: It is possible to combine various data sets from various sources into a single database using data clean rooms. This is especially helpful for businesses that need to combine vast amounts of data from numerous sources into a single format.

There is an increased interest in using second-party data as the new third-party data. Second-party data is first-party data that two or more parties decide to share for mutual benefit.

Companies and publishers must form alliances for standardized, secure methods of sharing data with other parties. For data sharing, expansion, and activation, brands will need to view media owners more as partners than vendors. The combined data can then be utilised to develop insights, create look-alike models, and assist advanced measurement by understanding what users are interacting with, purchasing, etc.

Consider the overlap between Holiday planning service provider and a well-known Travel website as an illustration of how the clean room is effectively utilized. By adhering to privacy laws, the data that these two businesses may share would be advantageous to both parties in order to learn more about their ideal shared clients.

PAIR (Publisher Advertiser Identity Reconciliation) was just introduced by Google’s DSP Display & Video 360. It’s a brand-new approach that enables publishers and advertisers to reconcile their first-party data for audiences that have visited both their sites and those of the advertisers and publishers in a secure and confidential manner. With aggregation, advertisers and publishers will be able to activate first-party data that is encrypted and specific to their websites, enhancing their Consolidated Programmatic Media Buying strategy. By using this procedure, parties are guaranteed that user-level data will never be shared, and that aggregated data will only be understandable and useful in the specific context of their direct interaction.

Clean room structure on DV360
Source: Google Blog

IAB Tech Lab, the global digital advertising technical standards-setting body has announced the launch of its Data Clean Room Guidance & Recommended Practices. To review you can visit IAB Tech Lab website.

If you’re interested in learning more about how you can prepare for a privacy-first marketing era, feel free to get in touch with us growth@performics.com


Mangesh Kaurase, Asst Vice President – Programmatic

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