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The future of third-party data cookies is uncertain. First-party data is part of the new strategy in online marketing – and data clean rooms offer an attractive approach to using them successfully as an alternative.

Data cleanroom – DCR for short – is a term that is currently becoming more and more popular in online marketing. Because after the possible elimination of third-party data cookies, advertising strategists are currently looking for new approaches to measure advertising measures, generate important product and marketing insights and address various target groups in a personalized manner. What is important, however, is that consumers’ privacy must be preserved.

DCR: Not as difficult as it seems

The term data cleanroom initially sounds rather bulky and not very practical. In practice, however, the concept is very catchy and has therefore been used in marketing for years. DCR is a shared technological infrastructure – mostly cloud-based – in which several partners can check and update their large data sets for overlaps. To do this, they use common variables or identifiers such as e-mail addresses, for example. If matches are found during the comparison, they can then be used: for insights into the target groups and customers, for a better understanding of the actual advertising effect, or for attribution modeling, i.e. for models with which future marketing strategies can be developed. Your own, original data sets always remain separate from those of the other party. Each of the data partners thus retains sovereignty over their information and gains valuable knowledge, for example about target groups or their marketing performance. He lets these insights flow into the control of his advertising, for example, by choosing the channels that are most relevant for lookalikes to his current customers and potentials. Even statistical models for anonymous personalized targeting are conceivable.

How is consumer privacy protected?

The data is encrypted and processed in such a way that it can be used across the board without partners being able to see the original data. As a result, not only is full sovereignty over the entered data retained at all times but no individual customers can be identified. With user consent, users can still be tracked to the point of sale – for customer journey analysis and attribution – but only at the first-party level and by a cleanroom partner. A second cleanroom partner can contribute their own data for pattern recognition. Both partners ultimately receive insights, reports, or a model for their targeting.

The comprehensive use of the data sets with simultaneous separation is made possible by an abstraction of the data on cohorts as well as machine learning. This form of data collaboration offers two decisive advantages over today’s ecosystem.

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