Personalized pricing and consumer privacy

Advances in data collection enable firms to use consumer information for personalized pricing. In Clavor'a Braulin's (2023) symmetric two-dimensional model, this reduces prices and profits, while partial privacy yields the highest profits. Extending the model to asymmetric firms and vertically differentiated products, we show that these results are not robust under sizable asymmetries. Partial privacy may harm both firm and industry profits, while no privacy can outperform other regimes. Consumer welfare also depends on asymmetry: when large, partial privacy maximizes consumer surplus. These findings challenge prior literature and inform the design of privacy protection regulations.