Large-scale app-based reporting of customer problems in cellular networks: potential and limitations

Authors:
Yu Jin;Nick Duffield;Alexandre Gerber;Patrick Haffner;Wen-Ling Hsu;Guy Jacobson;Subhabrata Sen;Shobha Venkataraman;Zhi-Li Zhang
Affiliations:
AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;AT&T Labs - Research, Florham Park, NJ, USA;University of Minnesota, Minneapolis, MN, USA
Venue:
Proceedings of the first ACM SIGCOMM workshop on Measurements up the stack
Year:
2011

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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.