Image-based profiling quantitatively assesses the effects of perturbations on cells by capturing a breadth of changes via microscopy. Here we provide two complementary protocols to help explore and interpret data from image-based profiling experiments. In the first protocol, we examine the similarity among perturbed cell samples using data from compounds that cluster by their mechanism of action (MOAs). The protocol includes steps to examine feature-driving differences between samples using Morpheus software, and how to visualize correlations between features and treatments to create interpretable heatmaps. In the second protocol, we show how to interactively explore images together with the numerical data, while we provide scripts to create visualizations of representative single cells and image sites to understand how changes in features are reflected in the images. Together, these two tutorials help biologists and researchers interpret their image-based data to speed up research.