Online display advertising is a hostile medium for field experiments. Display-ad effects are tiny and necessitate large-scale experiments. The experimenter has limited control because ad exposure is jointly determined by advertisers, users, algorithms, and market competition. As such, online display ads provide useful lessons for experimenters at the frontier of digital research more generally. Display-ad experiments place renewed focus on old topics like statistical power and compliance as well as on newer issues like identity fragmentation, experimental spillovers, and incrementality optimization. In this guide, I review these challenges, best practices, and new developments.