First-Party Data Strategy and Enrichment

A European automaker collaborated with a major media publisher to test first-party data collaboration against traditional cookie-based targeting. Using a secure data clean room, the automaker matched its customer records with the publisher's audience data to generate high-quality seed segments for lookalike modeling. According to an InfoSum case study, the first-party data strategy delivered an 18% increase in conversion rate, a 38% improvement in target-profile ad delivery, and a 19% lower cost per click compared to the cookie-based control group. The automaker's cost per action also dropped by 15%, demonstrating that privacy-compliant data collaboration can outperform legacy tracking methods on both efficiency and effectiveness metrics.

In a separate implementation, the same automaker's Polish division worked with an AI-powered marketing platform to segment its first-party audience by engagement level and model interest. According to a Zeta Global case study, the campaign achieved a 14% increase in conversion rate, exceeding the initial 10% target, while also reducing cost per click by 17% compared to historical benchmarks. The approach categorized audiences into low, medium, and high engagement tiers and tailored messaging across programmatic, search, and social channels accordingly. A large general-merchandise retailer in North America launched a retail media network built on its first-party data assets and reported reaching $500 million in net new revenue within four years, according to McKinsey, underscoring the monetization potential of well-structured first-party data ecosystems.