Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? We propose a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that mobility diversity, defined in terms of the entropy of the individual users’ trajectories, exhibits significant correlation with two different socio-economic indicators and the highest importance in regression and classification models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through Big Data by means of new statistical indicators that “nowcast†the socio-economic development of a territory.