This is the introductory chapter to the edited collection on 'Data-Driven Personalisation in Markets, Politics and Law' (Cambridge University Press, 2021) that explores the emergent pervasive phenomenon of algorithmic prediction of human preferences, responses and likely behaviours in numerous social domains – ranging from personalised advertising and political microtargeting to precision medicine, personalised pricing and predictive policing and sentencing. This chapter reflects on such human-focused use of predictive technology, first, by situating it within a general framework of profiling and defends data-driven individual and group profiling against some critiques of stereotyping, on the basis that our cognition of the external environment is necessarily reliant on relevant abstractions or non-universal generalisations. The second set of reflections centres around the philosophical tradition of empiricism as a basis of knowledge or truth production, and uses this tradition to critique data-driven profiling and personalisation practices in its numerous manifestations.