Against the backdrop of tightening regulatory requirements for data privacy, primarily within the GDPR framework and the phased deprecation of third-party cookies, marketing practice faces a fundamental conflict: the drive for deep personalization conflicts with the need for strict protection of user information. This study focuses on Data Clean Rooms (DCR) as a central mechanism for resolving this contradiction in the context of brand partnerships in the event industry. The aim of the research is to develop a conceptual model for the application of DCR to enable secure interaction between event organizers and sponsor brands, allowing for personalized communications and accurate ROI assessment without exchanging raw personal data. Methodologically, the study draws on a systematic review of academic work on privacy-enhancing technologies (PETs), a comparative analysis of architectural approaches to building DCRs, and an empirical analysis of case studies. The results show that DCRs leveraging such technological foundations as secure multiparty computation and confidential computing deliver efficiency gains: lead conversion increases by 63 percent, the accuracy of partner selection by 40 percent, and the number of errors in CRM campaigns decreases by 45 percent. The conclusions confirm the initial hypothesis: DCRs constitute a technologically viable tool for building a sustainable, data-driven partnership model in the events sector, aligning commercial objectives with ethical standards of data processing. The material is addressed to marketers, event organizers, data specialists, and developers of technology platforms.

Data Clean Room, brand partnerships, event marketing, personalization, data privacy, GDPR, Privacy-Enhancing Technologies, ROI, first-party data, Secure Multi-Party Computation

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