Driven by digital transformation, the integration of big data has become ubiquitous across industries, including product development. "Data-Driven Product Design" (DDPD) refers to the use of data throughout the product development process to inform decisions. However, a comprehensive understanding of the implementation of DDPD remains underexplored. This study addresses this gap by defining DDPD and developing a taxonomy based on a literature review and analysis of 26 case studies. The definition serves as the basis for a comprehensive taxonomy including 11 dimensions and 37 characteristics, which provides a structured framework to better understand how companies can leverage data in product development. The taxonomy advances theoretical understanding and provides practical insights for practitioners to improve decision-making and product design processes. This research contributes to the growing body of knowledge on DDPD by providing both researchers and industry professionals with an actionable framework to guide the adoption and implementation.