Getting insights from the voices of customers: Conversation mining at a contact center
Getting insights from the voices of customers: Conversation mining at a contact center
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DOI：
10.1016/j.ins.2008.11.026
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发表时间：
2009-05-13
影响因子：
8.1
通讯作者：
Roy, Shourya
中科院分区：
文献类型：
--
作者：
Takeuchi, Hironori;Subramaniam, L. Venkata;Roy, Shourya
需要分析客户和代理之间的业务导向对话，以获得可用于提高产品和服务质量、运营效率和收入的有价值见解。对于这样的分析，关键是要确定适当的文本片段和表达方式，特别是当文本数据由完整的抄本组成时，这些抄本通常是冗长和冗余的。在本文中，我们提出了一种方法来确定重要的部分，从对话中寻找变化的准确性的分类器，旨在区分不同的业务成果。然后，我们使用文本挖掘来提取关键实体（见解）之间的重要关联。我们使用汽车租赁服务中心的真实的生活数据的方法，使机会发现的有效性。(C)2008年爱思唯尔公司All rights reserved.
Business-oriented conversations between customers and agents need to be analyzed to obtain valuable insights that can be used to improve product and service quality, operational efficiency, and revenue. For such an analysis, it is critical to identify appropriate textual segments and expressions to focus on, especially when the textual data consists of complete transcripts, which are often lengthy and redundant. In this paper, we propose a method to identify important segments from the conversations by looking for changes in the accuracy of a categorizer designed to separate different business outcomes. We then use text mining to extract important associations between key entities (insights). We show the effectiveness of the method for making chance discoveries by using real life data from a car rental service center. (C) 2008 Elsevier Inc. All rights reserved.