基于文本挖掘的生鲜电商顾客满意度研究

Research on Customer Satisfaction of Fresh Food E-commerce Based on Text Mining

运用Python爬虫获取在线评论,通过词频统计和K-means方法得到顾客满意度评价体系的指标,通过TF-IDF方法计算出各指标的权重,从而得到生鲜产品的总体满意度。结果表明:消费者对生鲜产品的服务和价格的满意度相对较高,对包装的满意度相对较低;消费者对海鲜水产的满意度最高,对新鲜水果的满意度最低。最后为提高生鲜平台顾客满意度提出针对性建议。

Python crawler was used to obtain online reviews,the index of customer satisfaction evaluation system was obtained through word frequency statistics and K-means method,calculate the weight of each index through TF-IDF method,and the overall satisfaction status of fresh products was get.The results show that consumers have relatively high satisfaction with the service and price of fresh products,and relatively low satisfaction with packaging.Consumers have the highest satisfaction with seafood and aquatic products,and the lowest satisfaction with fresh fruits.Finally,targeted suggestions were put forward for improving customer satisfaction of fresh food e-commerce.