The work aims to provide the personalized printing platform with a method used to improve the customer satisfaction and efficient optimization. With the research methods of kano and QFD model, and taking the common personalized printing platform as the research object, the 10 product service demand indicators were summarized in the form of questionnaire, etc. These indicators were respectively subject to kano classification and calibration of satisfaction and importance. The mathematical model was used to modify the importance of different product services, so as to obtain the final importance of each product service attribute. The slope values of such two attributes as online designed service and data transmission speed were respectively 1.0091 and 2.6981, and the important degrees were 0.6025 and 0.5974, respectively. These two attributes were prioritized for the platform optimization, and the optimization order of each attribute of the personalized printing platform was obtained based on such parameters as kano type and importance, etc. From the perspective of customer demand, the key points for design and optimization are provided for the personalized printing platform.