Text mining methods applied to insurance company customer calls : a case study
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001 | MAP20200011637 | ||
003 | MAP | ||
005 | 20200413180242.0 | ||
008 | 200408e20200302usa|||p |0|||b|eng d | ||
040 | $aMAP$bspa$dMAP | ||
084 | $a217 | ||
245 | 1 | 0 | $aText mining methods applied to insurance company customer calls$b: a case study$cXiyue Liao...[El al.] |
520 | $aThe purpose of this case study is to develop a process for a U.S. personal lines insurance company to improve its customer service, make call center operations more efficient, and reduce costs by analyzing customer calls. Text mining methods such as topic modeling and sentiment analysis are used to study approximately 10,000 nonclaim customer calls from 2016. Results show the most frequent topics of calls and how customer sentiment differs between topics, which will allow the company to adjust its customer service accordingly. | ||
650 | 4 | $0MAPA20080590567$aEmpresas de seguros | |
650 | 4 | $0MAPA20080589189$aAtención al cliente | |
650 | 4 | $0MAPA20090013650$aOpinión del cliente | |
650 | 4 | $0MAPA20080553241$aAsegurados | |
650 | 4 | $0MAPA20080571566$aCasos prácticos | |
651 | 1 | $0MAPA20080638337$aEstados Unidos | |
700 | 1 | $0MAPA20200007654$aLiao, Xiyue | |
700 | 1 | $0MAPA20200007647$aChen, Guoqiang | |
700 | 1 | $0MAPA20200007661$aKu, Ben | |
700 | 1 | $0MAPA20200007678$aNarula, Rahul | |
700 | 1 | $0MAPA20200007685$aDuncan, Janet | |
773 | 0 | $wMAP20077000239$tNorth American actuarial journal$dSchaumburg : Society of Actuaries, 1997-$x1092-0277$g02/03/2020 Tomo 24 Número 1 - 2020 , p. 153-163 |