基于K-Means的EMS天津地区顾客满意度研究

K-Means based research on Tianjin EMS customer satisfaction

针对顾客满意度研究中影响因素多样性和满意度等级差异的问题,提出一种基于因子分析和聚类分析的顾客满意度评估方法。该方法首先运用因子分析从多个观测变量中提取关键潜在因子,揭示数据中的内在结构;然后利用K-Means聚类方法得到高、低满意度等级的顾客群体。经对比发现:高满意度群体影响因素单一,仅有“知名度”1个方面;低满意度群体影响因素复杂,包括“信誉度”“配套设施”“货损率”“投诉渠道便利性”“长期使用意图”5个方面。在此基础上,结合用户人群画像进一步分析差异成因,提出具有针对性的满意度提升策略,为改善快递企业的顾客满意度提供参考。

This paper presents a customer satisfaction evaluation approach based on factor analysis and cluster analysis in response to the diversity of contributing factors and disparities in satisfaction levels in customer satisfaction research.The factor analysis is used in this approach to separate important prospective factors from numerous observational variables and reveal the internal structure of the data;Furthermore,the K-Means clustering method was used to obtain the customer groups with high and low satisfaction levels,and it was found that the influencing factors of the high satisfaction group were single,and that is“popularity”.The influencing factors of low satisfaction groups are complex,including five aspects:“credibility”,“supporting facilities”,“cargo damage rate”,“convenience of complaint channels”and“long-term use intention”;Combined with the user group portrait,the causes of differences are further analyzed,and targeted satisfaction improvement strategies are proposed to provide reference for improving customer satisfaction of express delivery enterprises.