Online services increasingly collect behavioral data without users’ explicit awareness. While seemingly free, providers profit through personalized advertising based on behavioral insights and inferred preferences. As such profiling increases privacy risks, users often hesitate to accept tracking via consent options in cookie banners. In the context of free online services, fair data handling includes not only control but also a fair distribution of the value generated from personal data. Distributive justice refers to users’ perceptions of whether their outcomes are fair compared to the advertising profits gained by providers. Yet, it remains unclear how perceived privacy concerns, benefits, and distributive justice influence users’ acceptance of tracking. To address this gap, we conducted an experimental study examining two serial mediation paths. We find a suppression effect involving perceived benefits and distributive justice, indicating an ambivalent role of monetary rewards. Our findings inform the design of fair, data-driven business models and consent mechanisms.