This paper sheds light on the trade-os between privacy and utility in mobility-based geographic datasets. We aim at nd-ing out whether it is possible to protect the privacy of the users in a dataset while, at the same time, maintaining intact the utility of the information that it contains. In particular, we focus on geo-indistinguishability as a privacy-preserving sanitization methodology, and we evaluate its eects on the utility of the Geolife dataset. We test the sanitized dataset in two real world scenarios: 1. Deploying an infrastructure of WiFi hotspots to ooad the mobile trac of users living, working, or commuting in a wide geographic area; 2. Simulating the spreading of a gossip-based epidemic as the outcome of a device-to-device communication protocol. We show the extent to which the current geo-indistinguishability techniques trade privacy for utility in real world applications and we focus on their eects at the levels of the population as a whole and of single individuals.