Publishers and advertisers – it’s time to unite! With collaboration, both parties can win big. Data clean rooms are a critical component in maximizing this relationship because they give digital advertisers and publishers the right tools to collaborate on their first-party data and redefine the way they target and reach audiences.
In combination with deterministic IDs, data clean rooms help to increase the addressability of existing customers. They also provide a great way to improve the targeting potential of “unknown users” and the ROI of marketing efforts. This includes generating insights and enabling personalized experiences across the web – all while complying with data protection regulations.
While data clean room technology isn’t new, the applications are not always well understood. For instance, if there’s a need for secure and privacy-compliant infrastructure to check data records for overlaps to enable downstream use cases – data clean rooms are the best fit. That’s because common variables or identifiers such as email addresses and other deterministic IDs are used.
This provides valuable insights into target groups and customers and helps develop effective marketing strategies. The key here is that the original data sets always remain separate from other parties, with no access to each other’s data (i.e., between publishers and advertisers). In this way, each party retains sovereignty over its information, works in compliance with data protection regulations, and gains new insights on mutual data overlaps to foster a variety of marketing use cases.
New targeting and reach opportunities
Advertisers who control and use their first-party data have always looked for additional external data sources to increase their advertising efforts’ efficiency. However, they have often been hampered by data security and privacy concerns. These reservations can be addressed through data clean rooms, allowing everyone to better benefit from their own and others’ data in a privacy-safe way.
Publishers and advertisers have a comprehensive knowledge of their customers who have consented to use their first-party data. Independent data clean room partners can help overcome technological, legal, and data challenges all while making the data usable for collaboration between partners. In partially automated processes, selected data from advertisers and publishers are merged and sorted in a secure way. In collaboration with their preferred publishers, advertisers can increase their existing reach.
As a controlled, virtual ecosystem, data clean rooms open and connect closed spaces for advertisers and publishers and integrate seamlessly into a client’s existing tech stack. Collaborative partners work together in a privacy-compliant manner, deciding when and how to use their own data. It starts with matching defined data sets between both parties. Where it goes from there depends on what features the data clean room solution brings to the table regarding integration, automation, and activation.
Criteria for selecting a data clean room
Advertisers and publishers considering using data clean rooms should keep the following aspects in mind when making their selection:
- Is there sufficient first-party data available currently or in the future, and what is the value of this data for your business?
- Is there an opportunity for scaled reach and quality in terms of data & media? For example, via integrated machine learning technology?
- Which use cases are to be implemented?
- Consider internal company use cases vs. external data collaboration use cases (e.g. advertiser-publisher & retail media)
- Data/marketing insights
- Advertising use cases (such as retargeting, prospecting, and measurement and attribution)
- What is the relevance of these use cases for the business (strategic/commercial)?
- Which business units implement these use cases (BI/Data Science &/or Digital marketing/media) and how easy is it to access, control and activate data in the use cases?
- What security standards does the solution provide?
- How intuitive is the UI/handling of the solution for the different stakeholders?
- How integrated is the solution with existing ad tech?
- What is the level of automation for stakeholders?
Scalability through integrated retargeting and prospecting capabilities
Matching data from both partners enables downstream processing for retargeting use cases in all data clean room solutions. In addition, some data clean rooms today use machine learning based on large data sets to create lookalike models (statistical twins) for prospecting opportunities.
If these approaches are applied on the publisher side, scalable media use cases emerge for advertisers and agencies. Beyond the targeting options, some data clean room solutions are also integrated into the tech stack on the publisher side so that the use cases can run fully automatically, and the data is also loaded directly into the activation channels.
Thus, advertisers can continue to run targeted and scalable campaigns based on their data, even without third-party cookies. Publishers using data clean rooms can, in turn, build powerful data sets from their first-party data and gain extensive reach. This makes them more attractive to advertisers and strengthens their position against walled gardens like Meta and friends. These tech giants have long been collecting consent and data on a grand scale. And because their data sets give exclusive insights into target groups, they’re irresistible to advertisers.
With data clean rooms, advertisers have a new opportunity to improve the quality of their data and increase their reach. And, by collaborating with advertisers using data clean rooms, publishers who’ve lost ground to digital heavyweights have a chance to regain lost ground and get a better return on their investment.