Whether they’ve collected it through website and app interactions, loyalty programs, or previous marketing campaigns, brands possess — and protect — a wealth of information about their customers. In a first-party data future, they can use this information for targeting, measurement, and more — if they have the right tools and methods to use that data in collaboration with publishers and other data partners in a secure and compliant way.
Data clean rooms (DCRs) are a secure way for brands to collaborate with publishers, retailers, or other data partners. What’s more, they also open the door for brands to use more of their first-party data for more purposes. This article covers how it works, and which challenges are non-issues with the right DCR.
Challenges of collaborating with partners on first-party data
First-party data may be the way forward in a cookieless era, but so far, figuring out how to use that data has been fraught with hurdles.
Because of data protection regulations like GDPR, brands can’t simply connect their first-party customer data with ad platforms and data partners. Whether they’re big tech players like Facebook and Google, major retail partners like Amazon and Walmart, or an individual news site, any data transfer needs explicit consent from the customers themselves. This makes data-sharing agreements lengthy ordeals and limits a brand’s ability to scale their marketing analytics and targeting capabilities across channels and run effective campaigns.
It’s not just the increasingly strict regulatory environment limiting first-party data use. Consumer demands for privacy are growing globally: A YouGov survey from 2021 found that 66% of consumers around the world feel tech companies have too much control over their personal data. But at the same time, customers want more personalization when they interact with a brand: A much-cited survey by Epsilon cited 80% of consumers aged 18-64 are more likely to do business with a company if it offers personalized experiences.
It’s a difficult balance to strike. But there’s a way for brands to collaborate on data without sharing the actual data. And this is data clean rooms.
How do data clean rooms work?
A data clean room (DCR) is a secure and neutral space for two or more parties to join their data together and analyze it. In the case of advertising, this analysis could be anything from simple audience matching to complex targeting models to measuring ad effectiveness.
The core idea of a clean room is, only encrypted data goes in, and only approved insights come out.
Here’s how the process would look, for example, if a publisher and brand want to combine their data for lookalike targeting on a publisher’s inventory:
- Brand and publisher upload encrypted customer data to the data clean room.
- Brand and publisher set controls around what type of targeting model can be run on the joint datasets, and what insights the respective party can glean from the data.
- The data is matched based on unique identifiers that the publisher and brand share, like an email address or phone number, or a combination of them.
- The approved lookalike model runs on the joint data and discovers segments within the publisher’s inventory that most resemble the brand’s high-value customers.
- The lookalike audience is extracted from the clean room and activated either via the publisher directly or via the brand DSP after the publisher had created a corresponding deal ID.
How do data clean rooms make partnering on first-party data easier?
Not every data clean room solves collaboration challenges in the same way. Clean rooms based on Confidential Computing, like Decentriq Media Clean Rooms, provide unique encryption-in-use protection for sensitive data. Confidential Computing produces hard proof that data remains protected and is not accessible throughout use, which can remove many compliance and legal hurdles that often keep a brand from using first-party data beyond its four walls.
1. Independent DCRs keep you in control of your data during a partnership
Closed ecosystems or walled gardens, often provided by big-tech players like Google and Meta, give marketers the ability to combine their first-party data with consumer data that lives within the walls of their partners’ environments. Marketers typically give up control and transparency over how their data is used and have to trust the tech giants to not misuse their data.
Independent providers provide a neutral ground for parties who want to collaborate on their first-party datasets. These parties can agree together on the scope of collaboration within the data clean room. The degree of control and transparency varies among independent providers and most of them have access to the data processed in their platform. Some providers, like Decentriq, make it possible for each party to set individual controls over the use of their own first-party data.
2. Confidential Computing-based DCRs ease compliance and legal hurdles
Most data clean rooms can’t guarantee that personal data is completely inaccessible at all times. This is why brands and publishers usually have to rely on purely contractual data privacy agreements with the DCR provider. Legally, this is not considered hard proof of data privacy and constitutes data transfer. So brands and publishers usually require consent from their customers and subscribers for the use of their data in the DCR.
Clean rooms built on Confidential Computing technology hard-wire security and data privacy into the platform itself, guaranteeing that data remains private during the entire process — from upload to storage to download, and uniquely, while computations are running. This guarantee is verifiable through logging the running computations, which means it’s not only more secure — it also reduces compliance hurdles for using first-party data. Additionally, if only aggregated insights leave this kind of clean room, it eliminates the need for marketing consent.
3. Flexible DCRs make data partnerships more scalable
The more complex and modular tech stacks become, the more interoperability is a primary concern. Compatibility with demand-side, supply-side, and other platforms will impact how usable the DCR is within an advertising workflow.
The strongest clean rooms will offer multiple overlapping approaches, such as direct integrations with popular platforms, an application programming interface (API) to handle automated workflows, and visual user interfaces (UIs) to serve different user groups — admins, marketing roles, and data scientists. Analytical flexibility for data scientists in the typical languages they use, like Python, SQL, or R, can empower more advanced use cases.
The most important trait is flexibility – how quickly a DCR can be adapted to try a new workflow or integrate with a new partner. This ensures the clean room will remain viable as your business needs grow and change.
Also, some data clean rooms have fixed methods for establishing the identity of a unique user between two datasets, for example, email addresses, telephone numbers, or ID5 identifiers. It’s essential that this aligns with how both brand and publisher track their users within their own first-party data, or else it won’t be possible to match audiences at all. Other data clean rooms are identity-method agnostic, meaning as long as the two parties have some overlapping identifier or can pull in an identity graph, they can combine the datasets and get insights.
Read our Media Clean Room white paper to learn more about evaluating data clean rooms.
Future-proof your brand with first-party data
Brands that can tap into their first-party data while respecting customer data privacy are future-proofing themselves against regulations, third-party cookie deprecation, and rising consumer concerns around data use.
By using data clean rooms, brands can use their valuable first-party data to collaborate with publishers, retailers, or even other brands in a controlled and secure environment. They can include data that had previously been too sensitive to touch, run more effective campaigns and gain deeper insights into their customers.
If you want to discuss how data clean rooms can help you use your customer data more effectively in a secure and compliant way, reach out to us for a chat!
This is an updated and expanded version of an article with the same title previously published on the Decentriq blog.