In digital platform ecosystems, complementary products are crucial for generating consumer value. The increasing diffusion of data-based innovation and Artificial Intelligence affect how complementors develop such complements. Current theorizations on "data network effects" emphasize potential value contribution by data and Machine Learning (ML), but lack insights on complement level and complementors’ value capture, e.g., through product personalization. Thus, we examine how complementors’ use of data and ML relate to consumer value and empirically investigate 7,062 iOS mobile gaming apps. Our study contributes to research and provides insights to platform participants by 1) extending data-enabled learning conceptualizations to the complement level and revealing that a broader data scope and ML capability are positively related to consumer value; 2) highlighting the role of value capture as complement personalization diminishes the value contribution of data and ML; and 3) finding evidence for a substitution effect between data scope and ML.