The work aims todesign the existing product data system and develop a product data platform to ensure the standardization and personalization of product data, so as to meet the demand of dynamic users for product data management and solve the problems of low efficiency of existing product data management, messy underlying data and limited technology of data management platforms. From the perspective of dynamic user demands, a product data system design method combining fuzzy Kano model and fuzzy analytic hierarchy process (FAHP) was proposed. First, the Voice of the Customer (VoC) method was used to collect and analyze the demands of interested parties. The fuzzy Kano model was used to classify the collected user demands and find the key demand factors. Then the importance of the key demand factors was sorted through the FAHP model. Finally, the factors were corrected through the clustering analysis demand correlation analysis. The underlying design basis of product data systems was obtained and applied to the design of technical data management platforms, and the design results were evaluated quantitatively by efficiency index. This method can significantly improve the data cleanliness and effectiveness, meet the demands of multiple users for product data management, and also provide a feasible and reliable idea for the construction of the localization of product data management platforms.