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In this contribution, I focus on nested sampling as it is applied in sequential quantitative-qualitative mixed methods research. The function of this design element is to integrate quantitative and qualitative data. I refer to a specific type of recommendation that has proved particularly useful for the analysis of social milieus. An important feature of this approach is that the quantitative sample is divided into subgroups in order to then collect more qualitative data than would otherwise be the case. I present two projects in which nested sampling was implemented in this respect, but each in a different way. Subsequently, recipe and result will be compared. This reveals a number of discrepancies that are of interest both from a methodological point of view and in terms of research application. Above all, it will become clear that nested sampling is not only applicable to the analysis of social milieus. The same approach can also be applied to the analysis of complex causal relationships. But it may be difficult to provide all subgroups with sufficient qualitative cases. As I will show, nested sampling can be employed and implemented in such studies as well. However, the effort involved should not be underestimated.