Population differentiation is often quantified using putatively neutral genetic markers. While adaptive (i.e., selection-driven) genetic markers are becoming increasingly popular, they are mostly used for research on evolutionary processes, such as local adaptation or speciation. Here, we use simulations to evaluate the potential of adaptive genetic data for estimating population differentiation under a range of gene flow, population size, and selection scenarios. Our results suggest that reduced migration can lead to more pronounced genetic differentiation in adaptive versus neutral genetic differentiation, provided that a difference in local selection pressures among spatial locations exists (i.e., spatial selection gradients). These results encourage the use of adaptive genetic data for quantifying genetic differentiation, even in studies focusing on contemporary or recent processes, such as habitat loss and fragmentation. Furthermore, our results illustrate that not testing for selection in putatively neutral markers may lead to incorrect inferences about the processes underlying population differentiation.