This study explores how data-driven decision-making dimensions influence successful growth hacking implementation in platform-based enterprises employing fuzzy set Qualitative Comparative Analysis. Focusing on five key dimensions of data-driven decision-making (i.e., learning orientation, technological infrastructure, data analysis skills, proactive process management, and knowledge renewal), the research aims to uncover the configurations of these dimensions that most significantly contribute to successful growth hacking performance outcomes. By analysing combinations of these conditions, the study seeks to determine which conditions are necessary and sufficient for achieving the highest growth hacking performance outcomes. The findings provide actionable insights for platform-based businesses, guiding them on how to structure and prioritise their data-driven approaches for optimised growth hacking outcomes.