Data Clean Room: Data security and better marketing results
Valuable things belong in a safe for safekeeping. And not only in a bank but also in digital marketing. Data protection, privacy and security - that's what more and more users are demanding. The big players are reacting to this: Facebook announced in October 2021 that user campaign data will no longer be passed on to advertisers. And Google plans to abolish third-party cookies in 2023, further restricting data transfer. A cookie-free future is on the horizon. This means advertisers and brands must find new ways to collect and share consumer data compliantly. One of these ways is the use of data clean rooms.
What is a Data Clean Room?
A Data Clean Room is a protected environment where sensitive data can be processed and shared securely and confidentially. A vault for customer data. With the help of a Data Clean Room, companies can compare their customer data with other sources without revealing the identity of customers. This gives companies essential insights that they can use for marketing and advertising. This makes data clean rooms one of the critical tools for secure data sharing and a solution for privacy-compliant advertising in a cookie-free future.
How do Data Clean Rooms work?
Data Clean Rooms can be divided into six steps: Data is detected, utilised, analysed, enriched, segmented and activated. What exactly does this look like?
- At the beginning, different data sources are recognised and identified, including first-party data, CRM data or customer databases. 2. once the data is in a data clean room, the data is analysed, enriched and activated.
- Once the data is captured in a Data Clean Room, it is 'cleaned'. This means that any information that could help identify the people or company to which the data belongs is removed. For example, names, email addresses or other personal information is deleted to keep the data anonymous.
- Once the data is cleaned, the processed data sets are analysed in the Data Clean Room and checked for overlaps. If an overlap is found between two data sets, insights into the behaviour and needs of their customers can be derived.
- To further increase the value of the data, it is enriched with additional information, e.g. by integrating demographic data, interest profiles or behavioural data. In this way, the enhanced data provides a more comprehensive picture of the target group and enables a more precise and targeted approach.
-
The fourth step is to segment the data based on common characteristics, behaviours or preferences. This segmentation enables companies to carry out personalised marketing measures and respond individually to the needs of the target groups.
-
On this basis, advertising strategies can be implemented, optimised and fundamentally developed much more effectively and in a more targeted manner.
Use cases Data Clean Rooms: What can I use a Data Clean Room for?
You are now aware of what a Data Clean Room is and how it works in theory. But what is the benefit of a Data Clean Room for my company? How can I use these newly gained insights? The use cases of Data Clean Rooms are diverse but can be summarised into five main categories:
1. data consolidation to obtain complete customer IDs
Imagine a company has a global headquarters and local offices. The different locations collect information about their clientele on separate data sets. Thanks to Data Clean Rooms, this data can be unified and merged. Secure data sharing.
2. data enrichment to gain better insights into preferences and behaviour patterns
An example: thanks to Data Clean Rooms, an airline can share data with a luxury fashion brand to identify an affluent customer segment for a business-class offer.
3. campaign optimisation by targeting (or excluding) users
Imagine: Brand A wants to run an up-sell campaign on Publisher B's website. Thanks to data clean rooms, Publisher B can only play the ads to visitors who are already customers of Brand A for a particular product.
4. new customer acquisition by targeting users with specific characteristics (lookalikes)
For example, a home furnishings brand knows sales are strongly related to customer property ownership. Thanks to Data Clean Rooms, it can check its advertising partners to see if they have the potential to target property owners.
5. measuring the impact of the campaign
Brand A displays its ad on the website of publisher B. Thanks to Data Clean Rooms, Brand A determines whether a known user of B has come into contact with the ad. A can then select and compare the size of the shopping basket or the frequency of purchases in the D2C shop. Measurement at its best!
Amazon and Google are also already successfully using data clean rooms to improve the performance of their customers' advertising measures and to expand the offering of the Amazon Marketing Cloud and the Google Ads Data Hub.
In a nutshell: Using the Advantages of Data Clean Rooms
You already know how to use Data Clean Rooms and when to apply them. But you may be asking yourself: why use Data Clean Rooms at all? What benefits me and my company from introducing another new system and switching to a Data Clean Room platform? Firstly, you comply with data protection regulations by collecting, storing, analysing and sharing customer data in a GDPR-compliant way. Secondly, using data clean rooms builds trust with stakeholders, partners, customers and others and fosters long-term collaboration - especially when sharing your data sets. This "data collaboration" between several parties is revolutionary and offers companies an almost unlimited potential for innovation and improvement. This brings us to the third point: with the help of data clean rooms, you can improve your online marketing by combining and interpreting customer data from different sources. If matches are found, they can be used to gain insights into target groups, for a better understanding of the actual advertising impact or for campaign attribution, i.e. to develop future marketing strategies further.
5 Types of Data Clean Rooms
Other companies or organisations use and maintain different types of Data Clean Rooms. These are the five types you should keep in mind:
Walled Garden Data Clean Rooms:
A Walled Garden DCR is a closed ecosystem that securely connects first-party and personal data from large tech companies like Meta or Google.
Branded Data Clean Rooms:
Branded DCR is where big brands with deep customer insights use their data pool to enable advertising for other companies on their platforms.
Pure Play DCR are commercial offerings developed and maintained by specialist Data Clean Rooms providers.
Publishers Data Clean Rooms:
Publishers DCR are platforms of print, digital, TV or streaming publishers that use their users' data to provide marketers with better targeting.
Marketing Intermediaries Data Clean Rooms:
Marketing Intermediaries DCR are platforms developed and maintained by agencies and ad providers. They use the platform to compare and process data on behalf of their clients.
A safe for your valuables should be carefully selected, fit into your home, and installed by experts. The same applies to the Data Clean Room. To find the type and provider for your company, it helps to take an external look at your internal needs. We would happily support you in finding the Data Clean Room perfectly tailored to your company.
Curious?
You can find more information on the use of Data Clean Rooms and lots of helpful insights and tips for the concrete evaluation and selection of a provider in our Data Clean Room Guide "A World Without Cookies - WHAT'S NEXT?"
