While the possibility of algorithmic price discrimination and algorithmic collusion in conduct cases has been extensively discussed in the global antitrust community in recent years, there has been much more limited discussion in the context of mergers. In this article, we aim to fill this gap by discussing some potential implications of algorithmic pricing on market definition, unilateral effects, coordinated effects, and remedies. Specifically, we discuss the following topics and related questions:

• Market definition. How to account for algorithm-enhanced market/customer segmentation and identify relevant antitrust markets when prices are set by a “blackbox” algorithm.
• Unilateral effects. How to use merging parties’ pricing algorithms to conduct merger simulations.
• Coordinated effects. How the recent scholarship can inform analysis of potential coordinated effects in merger investigations.
• Remedies. Why data compatibility and collusion risk are important considerations when analyzing the divestiture of a merging parties’ pricing algorithm.