Lookalike Audience Modeling

A major consumer electronics manufacturer activated first-party CRM data through a data clean room to build GDPR-compliant lookalike audiences across multiple publishers. According to a 2025 Decentriq case study, the 16-day campaign deployed 13 first-party segments and corresponding lookalike audiences, reaching over one million potential new customers and three million existing customers. The approach enabled privacy-compliant cross-publisher advertising without reliance on third-party cookies, demonstrating that identity-based targeting can operate at scale within stringent regulatory frameworks.

In a separate implementation, a major Swiss financial institution transitioned from traditional third-party cookie-based targeting to AI-driven lookalike audiences built within a data clean room environment. According to a 2024 Decentriq case study, the five-week campaign produced a 129% increase in click-through rate, a 57% rise in page views, and a 44% reduction in cost per page view compared to traditionally purchased audiences. The institution reported a 31% decrease in cost per qualified visit, even after accounting for the cost of the clean room infrastructure itself.

A healthy snack subscription service used Meta lookalike audiences seeded from existing subscriber data to identify new prospects. According to a 2025 Ad Spend Technologies analysis citing the case, the campaign achieved a two-times higher click-through rate and three-times more subscriptions compared to interest-based targeting alone, validating the approach for subscription-model businesses seeking to scale acquisition beyond retargeting pools.