Impact of the Invisibles: Personalized Pricing on Platform with Anonymous Users

As data privacy regulations expand consumers’ control over personal data, e-commerce platforms and sellers increasingly face users whose data cannot be used for targeting or pricing. This paper studies how such information withholding reshapes competition in digital marketplaces. We develop a two-stage model of platform segmentation and pricing competition and introduce “fuzzy segmentation,” whereby the platform strategically pools privacy-preserving users with selectively grouped data-sharing consumers. Our analysis yields three main insights. First, fuzzy segmentation softens competition and increases seller profits, contrasting with the canonical intuition that horizontal segmentation tends to intensify price competition. Second, contrary to the intuition that privacy protects consumers from price discrimination, privacy-preserving consumers may face higher prices. Third, some data-sharing consumers may experience negative spillovers due to their inclusion in the mixed segment with privacy-preserving users. These results reveal unintended consequences of data privacy regulation: although privacy rules may enhance consumers’ control over personal information, they can also alter market segmentation in ways that raise prices for both privacy-preserving users and some data-sharing consumers. From a strategic perspective, the results show how privacy-driven incomplete information can be leveraged as a profit-enhancing force in e-commerce platforms.