{"title":"从呼叫中心记录中提取“破碎的期望”:原因和方式","authors":"A. Koca, A. Brombacher","doi":"10.1145/1358628.1358795","DOIUrl":null,"url":null,"abstract":"Currently, despite the explicit industrial consideration to improve the appeal and usability of technically sound electronics products, users increasingly seem to have dissatisfactory experiences in interacting with them. These unforeseen experiences (attributable to specifications omissions, usability/learnability problems, or specific usage context) lead to a large and increasing share of unknown field complaints. To correct and prevent such complaints or user reports, we promote effective exploitation of call centers: Valuable usage data is retrievable from the field by adopting a user-centered failure classification model that we developed. We also report on the supporting results of a test from applying our model to a set of call center data.","PeriodicalId":310204,"journal":{"name":"CHI '08 Extended Abstracts on Human Factors in Computing Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Extracting \\\"broken expectations\\\" from call center records: why and how\",\"authors\":\"A. Koca, A. Brombacher\",\"doi\":\"10.1145/1358628.1358795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, despite the explicit industrial consideration to improve the appeal and usability of technically sound electronics products, users increasingly seem to have dissatisfactory experiences in interacting with them. These unforeseen experiences (attributable to specifications omissions, usability/learnability problems, or specific usage context) lead to a large and increasing share of unknown field complaints. To correct and prevent such complaints or user reports, we promote effective exploitation of call centers: Valuable usage data is retrievable from the field by adopting a user-centered failure classification model that we developed. We also report on the supporting results of a test from applying our model to a set of call center data.\",\"PeriodicalId\":310204,\"journal\":{\"name\":\"CHI '08 Extended Abstracts on Human Factors in Computing Systems\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CHI '08 Extended Abstracts on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1358628.1358795\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CHI '08 Extended Abstracts on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1358628.1358795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting "broken expectations" from call center records: why and how
Currently, despite the explicit industrial consideration to improve the appeal and usability of technically sound electronics products, users increasingly seem to have dissatisfactory experiences in interacting with them. These unforeseen experiences (attributable to specifications omissions, usability/learnability problems, or specific usage context) lead to a large and increasing share of unknown field complaints. To correct and prevent such complaints or user reports, we promote effective exploitation of call centers: Valuable usage data is retrievable from the field by adopting a user-centered failure classification model that we developed. We also report on the supporting results of a test from applying our model to a set of call center data.