Particle laden flows are of relevant interest in many industrial and natural systems. When the carrier flow is turbulent, a striking feature is the tendency of particles denser than the fluid to inhomogeneously distribute in space, forming clusters and depleted regions. This phenomenon, known as "preferential concentration", has now been extensively investigated since the 1960s. The commonly invoked turbophoretic effect, responsible for the centrifugation of heavy particles outside the turbulent vortices, has recently got more complex by other additional mechanisms which have been shown to potentially play an important role in segregating the particles (for instance particles with moderate Stokes number have been shown to preferentially stick to low-acceleration points of the carrier flow). As a matter of fact a complete frame for accurately describing and modeling the particle-flow interaction is not yet available and basic questions, as the existence or not of a typical cluster size or of a typical cluster life-time-scale, still remain to be answered. This requires further quantitative investigations of preferential concentration (both from experiments and numerics) as well as dedicated mathematical tools in order to analyze the dispersed phase, its structuring properties and its dynamics (from individual particle level up to clusters level). This review focuses on the description of the techniques available nowadays to investigate the preferential concentration of inertial particles in turbulent flows. We first briefly recall the historical context of the problem followed by a description of usual experimental and numerical configurations classically employed to investigate this phenomenon. Then we present the main mathematical analysis techniques which have been developed and implemented up to now to diagnose and characterize the clustering properties of dispersed particles. We show the advantages, drawbacks and complementarity of the different existing approaches. To finish, we present physical mechanisms which have already been identified as important and discuss the expected breakthrough from future investigations.