Research On Influencing Factors Of Fresh E-commerce Consumer Satisfaction And Sales Forecast

The implementation and development of the "Internet+" action plan has promoted the deep integration of the Internet and traditional industries,thus greatly driving the rapid development of fresh product e-commerce.With the continuous increase of online goods,the safety and convenience of online payment,as well as the change of people’s lifestyle and the improvement of living standards,fresh product e-commerce is full of vitality.The actual consumers of fresh products e-commerce are often unable to have physical access to the goods,so most of the time,they can only form an understanding of the goods through merchant publicity and consumer reviews,and this way can not guarantee that the actual consumers can fully understand the information of their pre-ordered goods.This information asymmetry and the false publicity of some merchants on the platform have led to the decrease of consumers’ trust and satisfaction in e-commerce products or merchants.Therefore,how to effectively identify the key factors affecting consumer satisfaction of fresh electricity,how to continue to improve the quality of service of the e-commerce platform or businesses,how to accurately predict the sales of fresh electricity products,has become a scientific researchers,ecommerce platforms,buyers and sellers and other widely concerned and urgent problems to be solved.To improve customer satisfaction and business service efficiency,this paper carried out research on influencing factors of customer satisfaction and sales volume forecast of fresh products,and formed the following achievements:1.Based on the online reviews of consumers,the factors affecting consumer satisfaction are mined,and the key factors are identified according to the LDA model,in order to make merchants better understand the psychology of consumers,and then provide theoretical guidance for the improvement of consumer satisfaction of online fresh products.2.The emotional value of comment statements was calculated,and the intuitionistic fuzzy TOPSIS model was used to rank the consumer satisfaction of fresh fruit products,so as to more truly reflect the actual needs of consumers,so as to provide more effective and high-quality services for the platform and merchants.3.According to the characteristics of fresh products,the management mode of ecommerce and the advantages of prediction algorithm,the GM-Markov model is introduced to forecast the sales volume of fresh products to enable merchants to rationally allocate resources and solve the problem of store shortage and inventory.The identification of key factors in the research results of this paper can help the e-commerce platform to better understand consumer demand,and provide theoretical guidance for the improvement of fresh e-commerce service ability and the construction of standardization system.Meanwhile,according to the GM-Markov model,this paper makes a prediction study on its periodical sales volume,which can also provide reference value for the offline sales and operation of fresh products.