The study of the relation between social media use and well-being is at a critical junction. Many researchers 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 such an approach risks losing sight of the most important outcomes of a quantitative social science: estimates of the average relation in a large group. Our analysis begins by describing how the field got to this point. Then, we explain the problems of the current approach of studying variation. Next, we propose a principled approach to quantify, interpret, and explain variation in average relations: (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 conduct N = 1 studies and qualitative research.