摘要
为提升国家电网公司客户服务中心主动服务质量,降低客户投诉风险,开展了用户感知度模型的分析研究工作。用户感知度模型分析,采用K-Means聚类算法进行聚类,通过分析、归纳用户对故障停电事件的感知度,将用户进行感知度划分。通过构建用户感知度模型,首次实现故障事件用户感知分类,为个性化主动服务提供决策依据。用户感知度模型对客户服务业务应用具有重要意义,基于感知度划分结果,可为用户提供个性化主动服务。
To improve the active service quality of State Grid Corporation Customer Service Center and reduce the risk of customer complaints, this paper studied the user perception model. The user perception model is analyzed and the K-Means clustering algorithm is used to classify the user level according to the perception degree on outage accidents. By building user perception model, a user perception classification of outage accidents is achieved for the first time, which provided decision basis for personalized active service. The user perception model for the customer service business application is of great significance. Based on the perception results, power enterprises can provide users with personalized service actively.
出处
《电力信息与通信技术》
2016年第1期33-37,共5页
Electric Power Information and Communication Technology
