att_abstract={{Abstract—Effective management of large-scale cellular data
networks is critical to meet customer demands and expectations.
Customer calls for technical support provides direct indication as
to the issues and problems customers encounter. In this paper we
study the customer tickets – free-text recordings and classifications
by customer support agents – collected at a large cellular network
provider, with two inter-related goals: i) to characterize and
understand the major factors which lead to customers to call
and seek support; and ii) to utilize such customer tickets to
help identify potential network problems. For this purpose, we
develop a novel statistical approach to model customer call rates
which account for customer-side factors (e.g., user tenure and
handset types) as well as geo-locations. We show that most calls
are due to customer-side factors and can be well captured by the
model. Furthermore, we also demonstrate that location-specific
deviations from the model provide a good indicator of potential
network-side issues. The latter is corroborated with the detailed
analysis of customer tickets and other independent data sources
(non-ticket customer feedback and network performance data).}},
	att_authors={nd1321, ag1971, ph2326, wh5769, gj2418, sv1623, ss2864},
	att_tags={customer care, umts, network troubleshooting, cellular networks},
	author={Yu Jin and Nicholas Duffield and Alexandre Gerber and Patrick Haffner and Wen-ling Hsu and Guy Jacobson and Shobha Venkataraman and Zhi-Li Zhang and Subhabrata Sen},
	institution={{in Proc. IEEE INFOCOM Mini-Conference}},
	title={{Making Sense of Customer Tickets in Cellular Networks}},