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.

Key words: online comment, user profiles, product iteration, data-driven, sentiment analysis