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Customer satisfaction and natural language processing
DOI:10.1016/j.jbusres.2020.11.065.png)
摘要
En 中文
This study uses natural language processing in order to increase knowledge concerning customer satisfaction. A total of 12,000 customer returns were analyzed, 6,800 of which contained freely expressed qualitative feedback. Eight themes emerge from the analysis and bring to light the factors influencing satisfaction. It is also noted that satisfaction is not vertical or horizontal but can involve a more or less important combination of themes. This study also shows the link between the level of satisfaction and the number of themes addressed, thus challenging traditional approaches that do not seem to distinguish the discursive differences between satisfied and dissatisfied customers. Finally, this investigation lays the foundations for automatic and personalized processing of customer comments.
Keyword:
Satisfaction
Customer experience
Customer voice
NLP
Artificial intelligence
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.8
论文数:
1.0W
被引数:
8.7W
机构
暂无机构信息
引用论文
The financial impact of loyalty programs in the hotel industry: A social exchange theory perspective
Revisiting the Satisfaction-Loyalty Relationship: Empirical Generalizations and Directions for Future Research
JOURNAL OF RETAILING
IF10.2

