It is often recommended to investigate causal research questions by considering an ideal experiment. An ideal experiment describes the study a researcher would carry out if there weren't practical, ethical, or resource-related constraints (e.g., Angrist and Pischke 2008). First, we review whether and how methodologists define and advocate using ideal experiments (IEs). Second, we introduce the more general notion of ideal research designs (IRDs), discuss their components, and contrast them with actual research designs (ARDs). IRDs go beyond IEs in that they also speak to issues such as measurement errors that are rarely the focus of IEs. Third, we discuss an IRD and corresponding ARD to explain the various components of an IRD. Fourth, we introduce research design graphs (RDGs) which may be used to visualize and compare some essential components of IRDs/ARDs. Fifth, departing from our systematic account, we review applied examples of whether and how researchers have used IEs and IRDs in applied empirical research. While we find few examples, they attest to the usefulness of IRDs to benchmark actual research designs (ARDs) of previously realized or planned studies.