We present an experimental characterization of preferential concentration and clustering of inertial particles in a turbulent flow obtained from Voronoï diagram analysis. Several results formerly obtained from various data processing techniques are successfully recovered and further analyzed with Voronoï tesselations as the main single tool. We introduce a simple and nonambiguous way to identify particle clusters. We emphasize the maximum preferential concentration for particles with Stokes numbers around unity and the self-similar nature of clustering and we report new unpredicted results concerning clusters inner concentration dependence on Stokes number and global seeding density. Some of these experimental observations can be consistently interpreted in the context of the so-called sweep-stick mechanism. Finally, we stress the great potential of Voronoï analysis that offers important openings for new investigations of particle laden flows in terms, for instance, of simultaneous Lagrangian statistics of particle dynamics and local concentration field.