Data Clean Rooms: A Key Element of the New Cookieless Paradigm?

Emmanuel Chomier, Senior Manager at Converteo, is an expert in Data & Media topics. He assists our clients in leveraging data to enhance their media performance through the optimization of their marketing data ecosystem and advanced analyses (Test & Learn, Attribution, Omnichannel, MMM, etc.).

Key Takeaways:

• In light of the imminent removal of third-party cookies, digital players are exploring alternative solutions, some of which have yet to prove their effectiveness.
• In an uncertain context, first-party data, collected in compliance with regulations, is proving to be a reliable and valuable resource.
• The data clean room represents an innovative tool that allows the sharing and enrichment of first-party data within a secure framework. It guarantees data anonymity while providing valuable insights, thus addressing current concerns regarding privacy and regulation.
• While Google and Amazon have their own data clean rooms integrated into their ecosystems, companies can also create their own neutral and secure spaces for data collaboration.
• Despite the challenges associated with data clean rooms, these post-cookie innovations symbolize an evolving industry where trust and secure sharing are essential for defining the future of digital marketing.

For several years, and with a recent intensification, each week brings its share of questions, proposals, and innovations related to the end of third-party cookies.

Despite many areas of uncertainty, one thing is clear: digital players must prepare for their definitive removal, as the countdown officially began on January 4th!

To address this removal, there is no shortage of alternative proposals. Universal IDs, data clean rooms, logged-in environments, contextual targeting, and solutions offered by browsers (notably Privacy Sandbox – Google Chrome) are among them.

However, their effectiveness is still to be demonstrated, despite their clear potential. This is also true for universal IDs, as discussed in this article by Minted.

One priority seems to generate consensus: to rely more on first-party data. Historically, this data is the least voluminous but by far the most qualitative, and regulation should allow for long-term use.

The Data Clean Room promises to facilitate the exploitation of this first-party data, for use cases such as media targeting, customer knowledge, or even monetization. It is currently one of the most advanced cookieless solutions available. 

The data clean room, a private environment:

To begin with, the IAB defines a data clean room as a secure collaboration environment that allows two or more participants to use data assets for specific, mutually agreed-upon purposes, while ensuring strict access restrictions to the data, for example, by not revealing or exposing their customers’ personal data to other parties.

In summary, a data clean room is a neutral environment where multiple partners share their first-party data in an anonymized manner to derive aggregated insights or share them securely with a third party (e.g., for targeting).

Clearly, it is essential that each party has the proper consent from their users for each of the intended use cases.

Using a data clean room will enable the following use cases:

• Enrichment of data with third-party data

• Audience overlap analysis between multiple databases

• Reach and frequency analysis of media campaigns

• Measurement of incremental lift from activations

• Attribution analysis

• Audience targeting

• Creation of lookalike audiences

• Data monetization by making it accessible to a third party

Example 1: A company (e.g., an insurance firm) can improve its understanding of its customer base by collaborating with a third party (e.g., Leboncoin) within a data clean room, allowing for cross-analysis. This process involves jointly analyzing data to identify relevant trends.

Example 2: A company can retarget its customers with third parties through the secure sharing of its CRM database.

Example 3: A company can generate additional revenue by securely sharing data with partners or third parties while maintaining the confidentiality of sensitive data.

While there are several types of data clean rooms, each with its own specific interoperability features and advantages, they can generally be grouped into two categories:

1. Agnostic data clean rooms: These are technological solutions focused on interoperability, providing dedicated storage and collaboration spaces without supplying data (e.g., Liveramp, Google BigQuery, Snowflake, Weborama).
2. Media partner data clean rooms: These utilize data from their own platforms and leverage it to enhance their media suite with a new secure data-sharing tool (e.g., Meta, Amazon, Google Ads Data Hub, TF1, Carrefour Links).

The data clean room as an exchange hub

These data clean rooms are independent, providing a neutral and secure space where multiple partners can share data safely. They do not supply any data and are solely a technological solution available for making one’s own data accessible.

These data clean rooms allow an advertiser to make their data accessible to partners and, depending on the terms of collaboration, gain access to their data in return, outside of a closed environment. They can be a key tool in a large-scale data monetization strategy (for example, one advertiser wishes to make their data accessible to 20 advertisers, such as a retailer and its partner brands).

The main providers of “independent” data clean rooms are Snowflake, Decentriq, Liveramp, Weborama, and others.

This type of data clean room offers the following advantages:

• Neutrality: Independence from major market players.
• Impartiality: Fair treatment of data without external influence.
• Flexibility: Possibility for customization and integration with various sources.

However, the following disadvantages must also be considered:

• Cost: Potentially high setup costs, requiring economies of scale to break even (both technical and human resources).
• Complexity: Technical expertise needed for installation and maintenance (setup, security standards, regulatory changes, etc.).
• Reach: Necessity of having large volumes of data to share.

Data Clean Rooms as Extensions of Media Buying Platforms

Depending on their needs, a company can also turn to turnkey Data Clean Rooms (DCR) offered by major advertising players such as Google, Amazon, Meta, or TF1 & M6. These platforms rely on “independent” Data Clean Rooms (see part 1).

These ready-to-use solutions for third-party advertisers provide a practical alternative for companies looking to leverage data in a secure environment without having to establish specific partnerships.

Media Partner DCRs are secure environments where data can be analyzed while maintaining confidentiality.

• The standard data accessible through these DCRs is media data. Google Ads Data Hub, Meta (Advanced Analytics), and TF1 or M6 (with Liveramp) provide only detailed information on user engagement with media content, viewing trends, and advertising campaign effectiveness.
• Others go further by providing access to media and consumption data, such as Carrefour Links (with Liveramp), Le Bon Coin (with Liveramp), and Amazon, offering valuable insights into shopping habits and consumer preferences.

Snapchat, TikTok, and other publishers could also enter this space, but no official announcements have been made so far.

Thanks to the resources that these players can offer, these solutions present several advantages:

• The first is availability. No additional contracts or in-depth discussions are necessary to gain access if you meet the eligibility criteria (which depend on your area of activity and your budget spent on the platform, among other factors).
• The second is the absence of licensing fees. These data clean rooms are often provided by these players as an additional component of their advertising offerings.

However, they also present prerequisites to keep in mind before getting started:

• Accessibility: They often require technical expertise to fully leverage their potential (at least a basic understanding of SQL).
• Interoperability: They are inherently limited to a single environment (for example, you cannot use Meta’s Advanced Analytics for your YouTube campaigns).
• Data Sharing: Some contracts may not always be updated and may not comply with European DPO guidelines.

In conclusion, in a post-cookie universe, data clean rooms position themselves as a major innovation, combining privacy protection with targeted consumer insights. They are complex tools due to their highly secure nature and technical usage, with significant gains in measurement and activation. They reflect an evolving industry where data, secure sharing, and transparency take precedence.

Before embarking on a project involving the integration or use of a data clean room, it is crucial to ask the right questions to define their relevance and potential benefits. This strategic reflection is essential to identify the type of data clean room to use, ensure the long-term adoption of these technologies, validate their role in the company’s strategy, and anticipate the human resources needed to successfully execute this project.

If you wish to embark on this adventure, Converteo is equipped to assist you in validating the need for a data clean room, selecting the right solution, implementing it, and utilizing it on a day-to-day basis.

Discover our data marketing consulting services.

Contributor: Fabien Rubin, Media x CRM Consultant.