Research On Demand Analysis Of J Company’s Personalized Products

With the improvement of residents’ living standards,the personalized products have become important consumption demands in the new consumer era.The C2 M mode(Customer to Manufacturer)realizes the message interchange from the customer end(C end)to the manufacturing end(M end).Through the collection and analysis of consumer behavior data,it can guide the manufacturing end to design and produce with the goal of satisfying personalized needs of users.E-commerce platforms effectively connect both sides of supply and demand.With the help of massive consumption data and technical resources,E-commerce platforms will play an increasingly important role in the practice of product personalization based on the C2 M model.Taking J company as the research object,this paper divides the demand analysis of J company’s personalized products into three stages: demand identification,demand filtering and demand transformation.Firstly,it uses data mining technology to identify the needs of personalized products,which are divided into three steps: demand acquisition,demand processing and demand expression.In the demand acquisition part,python language is utilized to extract user comments and in the demand processing stage,word segmentation is carried out after eliminating invalid data.In the demand expression stage,word frequency statistics and keyword extraction are performed on the user review text,and KJ method is applied to build the initial personalized demand hierarchy model of the product.Then,based on the KANOUtility theory,this essay screens the demand for personalized products in two aspects: demand classification and demand filtering.When demand classification is carried out,the demands of personalized products are divided into 5 categories based on KANO questionnaire and fuzzy clustering method.In the demand filtering part,based on utility theory,the one-dimensional demand and attractive demand of retention are evaluated from five indicators,such as market maturity,market popularity and cost consumption,then the comprehensive interval utility value is calculated and the personalized demand that has the most critical impact on product renewal is selected.Finally,this paper transforms the needs of personalized products based on the KANO-QFD model,that is,from personalized needs to technical needs.After confirming the initial importance of the personalized demand based on the KANO category of the personalized demand,it is revised.Subsequently,the technical demands of the product are determined and the house of quality is built,which is the foundation of constructing relationship matrix between personalized and technical needs to calculate the importance and weight of technical needs through the independent collocation method,and conducting technical competitiveness analysis.This paper takes S brand sweeping robot as an example to carry out a complete demand analysis.It identifies the personalized demands of the most significant effect on product updates and translates them into technical demands to provide design reference for developers,verifying the feasibility of the demand analysis method for personalized products.This method is consistent with the "Reverse Customization Five-step Method" of J Company,and has certain reference significance for the demand analysis of J Company in the practice of products customization.