The evaluation of privacy-preserving techniques for LBS is often based on simulations of mostly random user movements that only partially capture real deployment scenarios. We claim that benchmarks tailored to specific scenarios are needed, and we report preliminary results on how they may be generated through an agent-based contextaware simulator. We consider privacy preserving algorithms based on spatial cloaking and compare the experimental results obtained on two benchmarks: the first based on mostly random movements, and the second obtained from the context-aware simulator. The specific deployment scenario is the provisioning of a friend-finder-like service on weekend nights in a big city. Our results show that, compared to the contextaware simulator, the random user movement simulator leads to significantly different results for a spatial-cloaking algorithm, under-protecting in some cases, and over-protecting in others.