The data clean room is a solution that can be used to protect customer privacy before buying ads. These rooms allow partners to work together safely and securely using data from their own, second-party, and third-party sources.
Data clean rooms are a neutral and secure software environment where publishers/media, advertisers/brands can match user data without sharing personally identifiable information.
As advertisers, publishers, and agencies adopt clean room technologies, they will continue to evolve. However, marketers and agencies still need to understand and learn key components.
Based on my personal experience and feedback from platforms and solutions available in the market, here are three of the most popular use cases for data clean rooms.
Campaign Measurement and Attribution
Measuring and Attribution of impact on marketing and advertising campaigns is one of the main practices when working with marketing and advertising data.
Clean rooms need to match data from customers before they can provide accurate measurement and Attribution. This will then help clean rooms and do what they are best at.
Clean rooms, when working at maximum capacity, can link first-party information with data behind walled gardens, connect campaigns to other data within protected environments, combine traditional and non-traditional measurement and attribution techniques, and compare the first-party information with merchant data readily available for more accurate and detailed insights.
Its new privacy standards require that clean-room methods of measurement and attribute data continue to exist on multiple media. The identities will be fragmented or aggregated into micro-cohorts.
Clean rooms must be able to integrate data and queries across all environments in order to provide real-time measurements and maximum flexibility. Marketers and agencies must still rely on capabilities like channel-level Attribution and cross-channel experiments, as well as an improvement of the media mix.
Analyse, segmentation, activation and analysis of audience insights
Due to legislative changes and increased data restrictions, the access and availability of first-party data have been severely limited. Data clean rooms are a solution to this problem, allowing parties to create rich, safe plans for audience engagement before, during, and after a campaign.
Applications that are based on clean room audiences can be…
- Attribute-based: User identity is enhanced through the use of data from another party.
- Performance-based: Transactional data is used to classify audiences according to motivation.
- Models that look like the previous categories: The audience is extended by models that mimic those in the two categories above.
After audience segments have been identified and built, an anonymous audience identifier is assigned. This identifier can then be used to activate other digital marketing tools – from advertising and email marketing to the site and application personalization.
First-Party Data Monetization Made Safer
The use and sale of third-party information have become less common due to privacy-centric legislation. This, along with the rise of walled gardens, makes it imperative for marketers and agencies to find and use new ways to monetize their first-party data.
Clean rooms can be used to monetize first-party data, as they are designed to protect data according to new privacy legislation.
In any market, it is common practice that the quality and quantity of the product sold will determine the price. The value of data sets from first-party sources will vary based on their ability to perform certain tasks, including optimizing personalization, boosting customer engagement and loyalty, and improving marketing performance.