Research On Product Design Optimization Based On Online Review DIPCA Analysis

Customer demand-oriented business strategy is the trend,and how to accurately explore customer demand is particularly important.Investigating customer needs through traditional interviews and questionnaires is costly.And its quality often depends on various factors such as the respondents’ willingness to participate and the complexity of the questionnaire.Also,it is not very time-sensitive.The development of online shopping platforms has created the conditions for the creation of online reviews.Online reviews often contain information about customers’ dissatisfaction with the product and a large number of demand preferences,which is of great value for product improvement.Moreover,review information can be obtained from public online platforms in a short period of time and at low cost,which has become an important source for obtaining customer demand.Accordingly,a competitive and dynamic approach to product design optimization has been proposed based on online reviews for mining customer needs.First,a customer focus attribute identification model has been constructed.Crawlers and other techniques were used to obtain online review data for the target and competitive products.After pre-processing the original data,the trained LDA model was used to extract the product attributes that customers in the target market care about.Then,the performance of the target product was measured and its much-needed improvement attributes were obtained.The Baidu API sentiment index was invoked to quantify customer satisfaction for each attribute of the target product and competitive products,respectively.Using the obtained results as the product attribute performance values.Traditional Importance-Performance Analysis(IPA),Importance-Performance Competitor Analysis(IPCA),and Dynamic Importance-Performance Competitor Analysis(DIPCA)were compared.The more comprehensive and scientific approach was used to explore product improvement attributes.Finally,the attributes to be improved were further analyzed using the three-element marking method.And the customer fine-grained requirements were uncovered and the product improvement strategy was generated.The proposed method was specified and validated by taking OPPO K7 x 5G phone and Redmi note9 5G phone as examples.The results show that:(1)The customer focus attribute identification model can effectively extract the important product attributes that customers focus on.(2)DIPCA analysis can help the target product to effectively obtain the competitive difference situation between each attribute and the competitive products.It captures the dynamic evolution of customer-focused attributes in the target market and assists the product in finding its much-needed improvement attributes in a comprehensive manner.(3)The three-factor tagging method can precisely uncover the fine-grained needs of customers,identify the usage situations and specific problems that lead to customer dissatisfaction,and help generate product optimization design solutions.