Methods for machine learning, or ML, are becoming more accessible, and consumer-generated data is on the rise, both of which are transforming marketing strategies. Researchers and marketers still have a long way to go before they fully grasp the myriad ways in which ML applications might help businesses gain and keep an edge in the marketplace. This study systematically evaluates the academic and corporate literature to present a taxonomy of marketing use cases based on machine learning. The authors have discovered 11 common use cases that fall into four distinct groups that reflect the core areas of leverage for machine learning in marketing: shopper fundamentals, consuming experience, decisions, and financial impact. The literature highlights practical implications for researchers and marketers by discussing the taxonomy's found repeating patterns and providing an analytical structure for analyzing it and extension.