Data clean rooms are a go-to solution for addressing customer privacy when modeling data prior to buying ads. They allow partners to collaborate safely and privately using their first- second-, and third-party data sets.
Essentially, data clean rooms a secure and neutral software environment in which publishers/media and advertisers/brands match their user data without sharing users' personally identifiable information with one another.
Clean room technologies will continue to evolve as advertisers, publishers, and agencies increase adoption; however, there are still key components marketers and agencies need to learn about and understand.
Here are three of the most prominent use cases for using data clean rooms, based on my own experience as well as feedback from the platforms and solutions in the marketplace.
1. Campaign Measurement and Attribution
Measuring and attributing the impact of marketing and advertising campaigns is usually one of the most central practices for working with customer, marketing, and advertising data.
To provide precise measurement and attribution data, clean rooms must first match customer data. That, in turn, will help optimize clean rooms to do what they do best.
When working at full capacity, clean rooms can successfully link first-party data with data that lies behind walled gardens, connect campaigns with other data in protected environments, merge traditional and nontraditional measurement and attribution methods, and compare first-party data with readily available merchant data to arrive at more detailed and accurate insights.
Because of new privacy standards, clean-room-enabled methods of measurement and attribution must prepare for data's continuing to exist across multiple mediums. Identities will remain fragmented or even become aggregated into micro-cohorts.
Clean rooms should have the ability to automate data integration and allow for querying across all environments to facilitate real-time measurement and maximum flexibility. Nonetheless, marketers and agencies will still need to rely on capabilities such as channel-level attribution, cross-channel experimentation, and an enhancement of the media mix model.
2. Audience Insights, Planning, Segmentation, Activation, and Analysis
As a result of legislative changes and increases in data restrictions, the union of first-party data sets has become more limited and inaccessible. Data clean rooms offer a way around that, improving parties' ability to develop rich and safe plans for audience activation before, during, and after the campaign has run its course.
Clean room audience-based applications can be...
- Attribute-based: User identities are enriched through another party's data.
- Performance-based: Transaction data is used to categorize audiences based on motivation.
- Lookalike-based: Audiences are extended through models that mimic the previous two categories.
Once audience segments are identified and built, they are assigned an anonymized audience identifier that can be deployed to other digital marketing tools for activation—from advertising and email marketing to site and app personalization.
3. Safer Monetization of First-Party Data
Rising privacy-centric legislation has resulted in the sale and use of third-party data as less common and less permissible. That, in addition to the simultaneous rise of walled gardens, means that finding and using new ways to monetize first-party data is paramount for marketers and agencies looking to profit from selling their own data or collaborating with outside partners.
Because clean rooms are equipped to protect consumer data in accordance with new privacy-focused legislation, they can facilitate the monetization of such first-party data in a secure domain.
As is standard practice in any marketplace, the ability to sell something—in this case, owned data—is contingent on the quantity and quality of what is being sold. The value of first-party data sets will fluctuate based on the data's ability to do certain things, such as optimize personalization, boost customer engagement and loyalty, enhance audience categorization, improve marketing performance, and calculate campaign ROI, to name a few.
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There are many uses for clean rooms. Although investing in them can require time, effort, and capital, the added ROI or improvement to marketing performance will help offset the investment cost.
The use cases in this article are just the starting points based on what I am seeing in today's marketplace. I expect many more use cases to arise as clean rooms are more readily adopted and their benefits are extracted.
For more information about data clean rooms, check out this primer for brands, agencies, publishers, and platforms, co-authored by the leading data clean room platforms and solution providers.
More Resources on Data Clean Rooms
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