Research On Potential Customer Mining Based On Commodity Comment Information

The development and popularization of Internet technology has driven the prosperity of e-commerce market.More and more consumers like to make online shopping on the network platform and make their own comments.These commodity reviews have become an important form of online word-of-mouth,which has a profound impact on the purchase decisions of potential customers and marketing strategies of enterprises.Nowadays,electronic commerce has entered the era of big data.The problems of large amount of comment text information,non-standard text information,strong timeliness and different information quality have not only brought difficulties to consumers to make correct purchase decisions,it also brings great challenges to the information mining work of enterprises.At present,the competition of e-commerce market is becoming increasingly fierce.Enterprises should pay more attention to the value of online comment information,extract useful information from large and complex online review information,effectively excavate potential customer groups,timely discover consumer demand information,targeted adjustment of product composition and making corresponding marketing strategies,which will transform potential customers into real customers,and then obtain higher efficiency and market competitive advantage,promote brand image and the popularity,it has the important realistic significance and the value.This paper takes the product iPhone8,which was sold in the mainland of China in October of 2017 years,as an example.Through extensive sample survey and correlation regression analysis,the characteristic attributes of customer preference are obtained.To establish the index system of potential customer's commodity comment preference as the basis of text analysis.Through web crawler technology,nearly 10000 comments were collected on Weibo,Dianping and other network platforms,text preprocessing and affective polarity analysis were carried out to construct the mining method for the potential customers of the iPhone8 mobile phone.According to the idea of commodity comment information emotion analysis model based on feature attribute,data capture,data preprocessing,ontology construction,implicit feature recognition are done.Through emotional polarity analysis,a series of weight values of each characteristic attribute of iPhone8 mobile phone are obtained.Based on this,the judgment criteria of potential customers are constructed.That is,with each characteristic attribute as a variable and each weight as a function of the coefficient,the score is arranged in order from high to low,and according to the needs of the product and market environment,a standard line,the user corresponding to the comment above the standard line,is called latent.In customer proportion.Finally,according to the research results,the paper puts forward the mining work based on the potential customer group,and puts forward the strategy of enterprise development and product innovation from the product development stage,the product release stage and the product leading stage.Also for other products to provide empirical cases for reference.