The interest in membrane heterogeneity started with two biological questions: how is the plasma membrane organized on a microscopic scale and what is the influence of this structure on biological processes? The earliest model that set out to answer these questions was the homogeneous fluid mosaic (S. J. Singer and G. L. Nicolson, Science, 1972, 175, 720–731). This model was refined by including heterogeneity (Fig. 1), where either the lipid composition or the proteins were given the leading role. Both concepts are in the process of being reconciled in the light of new experiments on lipid–protein interactions. Those interactions range from specific chemical to unspecific and purely physical. The latter comprise membrane curvature mediated interactions which have recently been shown to influence a large number of biological processes. In parallel to the conception of refined models, new experimental techniques to determine membrane microstructure were developed. Single-molecule fluorescence has emerged as one of the leading technologies since it delivers the required spatial resolution and can be employed in living cells. In a complementary approach artificial model systems are used to study specific biophysical aspects of membranes in isolation and in a controllable way. Nowadays, artificial membranes have outgrown their initial status as simplistic mock cells: a rich spectrum of different phases and phase transitions and the unique possibility to study membrane material properties make them an exciting subject of research in their own right (U. Seifert, Adv. Phys., 1997, 46(1), 13–137, S. L. Veatch and S. L. Keller, Biochim. Biophys. Acta, 2005, 1746(3), 172–185). In this review we discuss state-of-the-art models for membrane microstructure on the basis of key experiments. We show how phase separated artificial membranes can be used to gain fundamental insight into lipid composition based heterogeneity and membrane mediated interactions. Finally, we review the basics of single-molecule tracking experiments in live cells and a new unbiased analysis method for single-molecule position data.