Realist evaluations, a form of theory-driven evaluation, aim to explain how, why, for whom, and to what extent a complex health intervention works (or does not work). Realist evaluations are often "methods-flexible" and encourage the appropriate use of a range of evidence types that provide explanatory value. However, there is a lack of guidance in the published literature on how to identify and develop the methods and tools for realist evaluation data collection to contribute to this purpose. This article contributes to evaluation research and practice by providing an in-depth reflection on the experience of a realist researcher in planning and conducting a recent realist evaluation by describing the critical decision points and considerations taken throughout the data collection process.