Research On Dynamic Customer Requirements Identification Based On Online Initial And Supplementary Reviews

The constant expansion of e-commerce has allowed more consumers to spend online,which has led them to release user-generated-content related to products or services on the Internet to express their personal consumption experiences.These online reviews not only have an important influence on consumers’ purchasing decisions,but also have important reference value for manufacturers to improve the design of products and services.Current researches mostly identify customer needs based on online initial reviews and extend them to the entire life cycle of the customer relationship.However,it ignores the valuable information contained in the supplementary reviews.Supplementary reviews contain the mature experience that customers can only get after they have a lot of experience.The emergence of the supplementary review makes up for the lack of immature and untrue information in the initial review.Therefore,it is necessary to combine online initial reviews and supplementary reviews to dig deeply into dynamic customer requirements to identify the changing rules of customer requirements.This thesis first reviews the related theories and research findings of customer requirements identification and dynamic customer satisfaction based on online reviews.Then,taking online initial reviews and supplementary reviews as two levels of consumer experience,a study framework for identifying dynamic customer needs based on online reviews is constructed.It primarily contains four steps which are user review data crawling for online initial reviews and supplementary reviews,LDA-based review text topic extraction,machine learning-based product attribute sentiment analysis,and overall customer satisfaction analysis,product attribute classification,and user requirement priority analysis based on joint analysis and Kano model.Finally,based on the initial and supplementary online reviews of the laptops and mobile phones of JD.com,this research explores the changing trend of customer satisfaction and important product attribute categories and identifies dynamic customer requirements.The results show that logistics,fan,and storage of laptops change from attractive attributes to basic attributes,price changes from attractive attributes to one-dimensional attributes,and price,photography,and running speed of mobile phones change from basic attributes to attractive attributes.This thesis combines initial reviews and supplementary online reviews to propose an effective method to identify dynamic customer requirements.The research can expand the study field of customer requirements identification and dynamic customer satisfaction by taking advantage of online reviews.Furthermore,the findings may help manufacturers comprehensively mine and insight into the rules of customer requirement and preference for products and services,and make reasonable product design and improvement strategies.