Empirical models of strategic games are central to much analysis in marketing and economics. However, two challenges in applying these models to real-world data are that such models often admit multiple equilibria and that they require strong informational assumptions. The first implies that the model does not make unique predictions about the data, and the second implies that results may be driven by strong a priori assumptions about the informational setup. This article summarizes recent work that seeks to address both issues and suggests some avenues for future research.