<p>This paper presents a multi-objective planning approach for individualized product configuration guided by web behavioural information. The method addresses the challenges of high costs associated with gathering customer requirements and the low efficiency of existing product configuration processes. Using a decomposition technique based on “product-attribute-feature words,” key characteristics of individualized products are extracted, enabling in-depth mining of customer behaviour data from the web. This data informs the creation of a customer requirement acquisition and processing model driven by keyword triggers. Combined with a modular design approach, an evaluation system for individualized product configuration is developed. The model focuses on optimizing customer satisfaction, economic efficiency, and environmental performance. A multi-objective planning model is established for individualized product configuration, and an enhanced non-dominated sorting genetic algorithm II, NSGA-II algorithm is employed to generate optimized configuration options, providing diverse choices for customers. The effectiveness and practicality of this method are demonstrated through a case study involving air purifiers.</p>