Most researchers studying the relation between social media use and well-being find small to no associations, yet policymakers and public stakeholders keep asking for more evidence. One way the field is reacting is by inspecting the variation around average relations—with the goal of describing individual social media users. Here, we argue that this approach produces findings that are not as informative as they could be. Our analysis begins by describing how the field got to this point. Then, we explain the problems with the current approach of studying variation and how it loses sight of one of the most important goals of a quantitative social science: generalizing from a sample to a population. We propose a principled approach to quantify, interpret, and explain variation in average relations by: (1) conducting model comparisons, (2) defining a region of practical equivalence and testing the theoretical distribution of relations against that region, (3) defining a smallest effect size of interest and comparing it against the theoretical distribution. We close with recommendations to either study moderators as systematic factors that explain variation or to commit to a person-specific approach and conduct N=1 studies and qualitative research.