Targeted advertising has become a prime vehicle of the digital economy, leveraging users’ browsing behaviors to deliver personalized ads. However, the programmatic bidding mechanisms for these ads are often unclear, raising concerns about transparency and accountability. To address this challenge, we propose a novel measurement method that uses header bidding to gain access to raw bidding data. By setting up several user personas with varying interests and demographics, our system using OpenWPM observes how advertisers’ bidding strategies respond to specific user actions, such as clicking on banner ads. Our experiments reveal the impact of these behaviors on bid prices and the number of bids received, providing quantitative insights into how user profiles are valued in ad auctions. Furthermore, we analyze the correlation between bid prices and bidding activity, offering a deeper understanding of the dynamics driving targeted advertising. This work contributes to enhancing transparency in programmatic advertising and sheds light on the value of user behavior in digital ecosystems.