When Does Homogenization Reduce Competition in Algorithmic Personalized Pricing?

This paper explores the implications for market competition of increasing homogenization between personalized pricing algorithms. Our analysis reveals that higher homogenization (correlated outcomes) diminishes consumer welfare. Furthermore, as consumers become more price sensitive, firms are increasingly incentivized to compromise on the accuracy of their predictions in exchange for coordination. Our results underscore the potential anti-competitive effects of algorithmic pricing and highlight the need for refined antitrust approaches in the era of digital markets.