Abstract: To address the issues of time-consuming and laborious, as well as low efficiency of traditional product designing, user profiles and a modeling method for iterative product designing is proposed. The proposed method can effectively capture use attitudes towards product features, providing a new baseline for enterprises to conduct product iteration. First, the user information attributes and online user comments are obtained by web crawler technology. A conceptual model of three-dimensional user profiles is established by integrating product information attributes. Based on product features, a profile model is developed using Word2vec technology and sentiment analysis from two dimensions: user attention and quality satisfaction. Then, by analyzing the overall user profile with the fine-grained feature profile of products, a product optimization strategy is determined using the K-value method, emphasizing both core advantageous features and features for optimization. Finally, a case study is conducted using a certain camera as an example to analyze data-driven iterative product designing. Results show that the proposed method can effectively explore the core demand of users and provide enhanced product design solutions for enterprises to expedite product iterations.