Yu Jin, N. Duffield, Alexandre Gerber, P. Haffner, Wen-Ling Hsu, G. Jacobson, S. Sen, Shobha Venkataraman, Zhi-Li Zhang
{"title":"Large-scale app-based reporting of customer problems in cellular networks: potential and limitations","authors":"Yu Jin, N. Duffield, Alexandre Gerber, P. Haffner, Wen-Ling Hsu, G. Jacobson, S. Sen, Shobha Venkataraman, Zhi-Li Zhang","doi":"10.1145/2018602.2018607","DOIUrl":null,"url":null,"abstract":"In this paper, we study the Location-based Reporting Tool (LRT), a smartphone application for collecting large-scale feedback from mobile customers. Using one-year data collected from one of the largest cellular networks in the US, we compare LRT feedback to the traditional customer feedback channel -- customer care tickets. Our analysis shows that, due to the light-weight design, LRT encourages customers to report more problems from anywhere and at any time. In addition, we find LRT users access network services more intensively than other mobile users, and hence are more likely to experience and are more sensitive to network problems. All these render LRT feedback a valuable information source for early detection of emerging network problems.","PeriodicalId":387856,"journal":{"name":"W-MUST '11","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"W-MUST '11","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2018602.2018607","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, we study the Location-based Reporting Tool (LRT), a smartphone application for collecting large-scale feedback from mobile customers. Using one-year data collected from one of the largest cellular networks in the US, we compare LRT feedback to the traditional customer feedback channel -- customer care tickets. Our analysis shows that, due to the light-weight design, LRT encourages customers to report more problems from anywhere and at any time. In addition, we find LRT users access network services more intensively than other mobile users, and hence are more likely to experience and are more sensitive to network problems. All these render LRT feedback a valuable information source for early detection of emerging network problems.
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