HotSpots: Visualizing Edits to a Text
44893Authors
nan
Abstract
Compared to the telephone, email based cus- tomer care is increasingly becoming the pre- ferred channel of communication for corpora- tions and customers. Most email-based cus- tomer care management systems provide a method to include template texts in order to re- duce the handling time for a customer’s email. The text in a template is suitably modified into a response by a customer care agent. In this paper, we present two techniques to im- prove the effectiveness of a template by pro- viding tools for the template authors. First, we present a tool to track and visualize the ed- its made by agents to a template which serves as a vital feedback to the template authors. Second, we present a novel method that au- tomatically extracts potential templates from responses authored by agents. These meth- ods are investigated in the context of an email customer care analysis tool that handles over a million emails a year. 1
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Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 264–273, Honolulu, October 2008. c⃝2008 Association for Computational Linguistics HotSpots: Visualizing Edits to a Text Srinivas Bangalore AT&T Labs – Research 180 Park Ave Florham Park, NJ 07932 srini@research.att.com David Smith AT&T Labs – Research 180 Park Ave Florham Park, NJ 07932 dsmith@research.att.com Abstract Compared to the telephone, email based cus- tomer care is increasingly becoming the pre- ferred channel of communication for corpora- tions and customers. Most email-based cus- tomer care management systems provide a method to include template texts in order to re- duce the handling time for a customer’s email. The text in a template is suitably modified into a response by a customer care agent. In this paper, we present two techniques to im- prove the effectiveness of a template by pro- viding tools for the template authors. First, we present a tool to track and visualize the ed- its made by agents to a template which serves as a vital feedback to the template authors. Second, we present a novel method that au- tomatically extracts potential templates from responses authored by agents. These meth- ods are investigated in the context of an email customer care analysis tool that handles over a million emails a year. 1 Introduction Email based customer care is increasingly becom- ing the preferred channel of communication for cor- porations and customers compared to the conven- tional telephone-based customer care. For cus- tomers, email channel offers several advantages – there are no tedious menus to navigate, there is no waiting time to reach an operator, the request can be formulated at the customer’s pace and additional material supporting the case can be attached to the email. There is also a record of the service re- quest for the customer unlike the telephone-based customer care. However, there are also limitations of the email channel. The most significant one is that the customer-agent interaction could be drawn out over successive emails spanning over several days as opposed to being resolved in one or two telephone calls. For corporations, the asynchronous nature of email-based customer care offers signifi- cant opportunities to reduce operations cost by ef- fective load balancing compared to telephone-based customer care. It is quite common for an email cus- tomer care agent to work on several cases simulta- neously over a period of a few hours. Email chan- nel also offers higher bandwidth for corporations to send additional information in the form of web links, images and video or audio instructions. The effectiveness of customer care in the email channel is measured using two competing metrics: Average Handling Time (AHT) and Customer Ex- perience Evaluation (CEE). AHT measures the time taken from when a customer email is opened to the time when the response is sent out. This time is typ- ically averaged over a period of a week or a month for reporting purposes. CEE measures customer sat- isfaction through a survey of a random subset of cus- …
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Labeled Text
Compared to the telephone, email based customer care is increasingly becoming the preferred channel of communication for corporations and customers. Most email-based customer care management systems provide a method to include template texts in order to reduce the handling time for a customer’s email. The text in a template is suitably modified into a response by a customer care agent. In this paper, we present two techniques to improve the effectiveness of a template by providing tools for the template authors. First, we present a tool to track and visualize the edits made by agents to a template which serves as a vital feedback to the template authors. Second, we present a novel method that automatically extracts potential templates from responses authored by agents. These methods are investigated in the context of an email customer care analysis tool that handles over a million emails a year. 1
Publication Details
- Paper ID:
- 44893
- Year:
- 2008
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan