Research On Product Competition Information Mining And Differentiated Innovation Opportunities Based On Online Reviews

Nowadays,e-commerce is developing rapidly and is an important part of the development of China’s digital economy.However,the current e-commerce market is fiercely competitive and product homogenisation is high.In order to maintain a competitive edge in the marketplace,companies must consider the implementation of differentiation strategies that make their products unique.Obtaining product competition information is the preparation for product differentiation.Traditional methods of market research,such as questionnaires and telephone interviews,have shortcomings such as the high cost of research and the long time it takes.While online product reviews are feedback from customers after they have purchased products or services,online review mining can be another cost-effective and efficient channel for companies to gain market intelligence.The research in this article is based on a review of existing research theories and methods,proposes a framework for information mining of product competition and differentiated innovation opportunities based on online reviews,and verifies the feasibility of this method with practical cases.First,the LDA(Latent Dirichlet Allocation)topic model is used to extract potential topics for online reviews of the product to be analysed and to analyse changes in online review topics to obtain the product features that consumers are interested in.Second,by analysing the themes of positive and negative reviews of different products,we can obtain the competitive advantages and disadvantages of the products.Finally,based on the product competition information,the innovation goal of product differentiation is established and the innovation opportunities of product differentiation are identified from the perspective of innovation genetics theory.To test the effectiveness of the research method,this thesis takes four humidifier products on the Amazon platform as examples.The results of the study found that using the LDA topic model to analyse online reviews of products not only helps companies to understand the product features that consumers care about and how the product performs in different aspects of the market,but also allows them to grasp the real usage scenarios and actual needs of users.The online reviews reflect the product features that consumers are concerned about,covering six main aspects: functionality,operation,hardware,quality,customer service and operational effectiveness,and reveal information about needs of users and the usage scenarios such as the season,weather and time of day they use the product.Through the analysis of differences in comment topic content and topic intensity,the study identified the unique competitive advantages and disadvantages of the four products.This thesis combines these product competitive information to establish four differentiation objectives in terms of quality,ease of use,functionality and service,and uses innovation genetics theory to construct differentiation innovation paths and identify specific differentiation innovation opportunities based on the differentiation objectives.The research framework proposed in this study provides a theoretical basis for companies to gain competitive intelligence from user reviews,expands the area of application of innovation genetics theory,and provides a viable way for firms to find opportunities for product differentiation.