Benchmarking refers to the systematic comparison of results from an observational study to those from a reference randomized trial that addresses the same causal question. Although comparing observational findings with randomized trial results is not new in epidemiology and medicine, the formalization of this comparison as a structured “benchmarking” approach is relatively recent and has emerged largely alongside the development of the target trial emulation framework (see Hernán and Robins 2016 AJE). Under the target trial emulation framework, observational analyses are explicitly designed to emulate a hypothetical well-defined randomized trial. In contrast, benchmarking involves emulating the design and analytic approach of a reference trial that is actually conducted, thereby enabling a principled and transparent comparison between an observational estimate and randomized trial result where the causal questions are aligned. Benchmarking against reference trials can be an important diagnostic that informs understanding of the fitness of the design, data, and analytic approach before moving on to conduct observational studies that address expanded questions with new endpoints, populations, or comparators – where the target trial to emulate is hypothetical. This playlist introduces the conceptual basis of benchmarking, highlights large-scale empirical evaluations, and showcases contemporary applications in pharmacoepidemiology and methods evaluation.