Market competition information is an important basis for small and medium enterprises (SMEs) decision-making when conducting iterative product design, which included information on competitive analysis, user experience and satisfaction, production capacity, and R&D capability. In the previous New Product Development (NPD) process, Customer Requirements (CRs) and Market Competition Information (CIs) often need to be corrected through market surveys and questionnaires. To explore how to analyze competitors’ products by mining the market sales, user reviews and other data of Internet shopping platforms, which plays a crucial role in product iteration decision making, this paper proposes an Apriori-Latent Dirichlet Allocation (A-LDA) competitive information mining model based on multi-source text data, which uses text mining and analysis to obtain the competitive information contained in users’ online reviews by generalizing and summarizing the syntactic structure and candidate word sets of market-oriented competitive information. By summarizing and summarizing the syntactic structure and candidate word sets for MCI, the model uses text mining and analysis to obtain objective information about user needs and market competition contained in users’ online comments, so as to analyze competitors’ product-related information, thus obtaining decision-making information about product design iteration for the enterprise. Finally, through the empirical analysis of product attributes, online comments, and sales data of countertop dishwashers of four different brands, the results show that this method can provide a reference for enterprises to obtain the market competition information for product iteration design decision-making.