Customer complaints monitoring with customer review data analytics: An integrated method of sentiment and statistical process control analyses
Customer complaints monitoring with customer review data analytics: An integrated method of sentiment and statistical process control analyses
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DOI：
10.1016/j.aei.2021.101304
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
Juram Kim;Chiehyeon Lim
中科院分区：
文献类型：
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作者：
Juram Kim;Chiehyeon Lim
这项研究提出了一种数据驱动的方法来监控客户投诉，以实现高效的服务质量管理。认识到客户评论的价值是“客户的声音”的池，我们提出了一种情绪和统计过程控制分析的集成方法。使用客户回顾数据进行统计过程控制分析，将研究和应用的范围从供应商的角度扩展到以客户为中心的服务质量管理。情绪分析能够从客户评论数据中系统地识别客户满意度分数，而统计过程控制图分析能够及早发现重大客户投诉并防止服务故障。两种分析的集成使以可接受的时间和成本监测客户投诉成为可能。我们使用移动游戏服务应用并验证了所提出的方法，为其实施和定制提供了指导。随着时间的推移，拟议的方法有望成为监测客户投诉的有效工具，从而实现响应性和预防性的质量管理。
This study presents a data-driven method to monitor customer complaints for efficient service quality management. Recognising the value of customer reviews as a pool of 'voice of the customer', we propose an integrated method of sentiment and statistical process control analyses. The use of customer review data for statistical process control analysis extends the scope of research and application from the supplier perspective to customer-centric service quality management. The sentiment analysis enables systematic identification of a customer satisfaction score from customer review data while the statistical process control chart analysis allows early detection of significant customer complaints and prevents service failures. The integration of two analyses makes it possible to monitor customer complaints at acceptable time and cost. We applied and validated the proposed method using a mobile game service, offering a guideline for its implementation and customisation. The proposed method is expected to be used as an effective tool for customer complaints monitoring over time, which enables responsive and preventive quality management.