Analysis of Factors Influencing Consumers' Satisfaction with Online Fresh Food Shopping

Abstract

With the development of Internet technology, more and more people choose online shopping, resulting in an increasing amount of online review data. It is crucial to mine information about users' feelings from these reviews to obtain factors that affect customer satisfaction. This article uses crawler technology to obtain the review data of JD supermarket hairy crabs. After data preprocessing, it extracts five characteristic factors that affect satisfaction, including logistics, specifications, taste, freshness and quality. Then, it uses a Likert scale to quantify and score the data, and establishes a customer satisfaction factor model based on Bayesian network, which is compared with a neural network model. Evaluation criteria include accuracy, precision, and recall. The research results show that the customer satisfaction model based on Bayesian network has the best measurement effect, which can output the influence degree and correlation of each factor on satisfaction, and provide relevant suggestions for producers and other stakeholders.