Abstract
To compete, cellular network operators must be very responsive to their customer needs. One effective approach that could make a business more productive is anticipatory decisions while considering customer’s problem. Communication Service Providers must have greater insights into their own Call Details Record data in order to gauge and tune up the company’s performance. CSPs must promptly react to ever changing competitive environment by providing quick and personalized services. However, reacting quickly to changing customer expectations is not a simple task. In this paper, a method has been proposed in order to tackle this challenging problem. Proposed solution is using CDR data as the primary data source to detect valued social networks and monitored the QOS provided to the identified valued social network. Calls of valued customers will be prioritized by inserting priority tag in MSC. The final step of proposed technique deduces a proactive approach in order to retain the high revenue generating customers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wipro Council for Industry Research: A value based approach to improve customer experience, Wipro Technologies (2012)
Sybase, Inc.: Communications Service Providers and Sybase a brochure (2010)
Ovum: Telco business and investment trends for IT, November 2011
Sharma, A., Panigrahi, P.K.: A neural network based approach for predicting customer churn in cellular network services. Int. J. Comput. Appl. 27(11), 26–31 (2011). ISSN 0975-8887
Burez, J., Van den Poel, D.: CRM at a pay-TV company: using analytical models to reduce customer attrition by targeted marketing for subscription services. Expert Syst. Appl. 32(2), 277–288 (2006)
Van den Poel, D., Larivière, B.: Customer attrition analysis for financial services using proportional hazard models. Eur. J. Oper. Res. 157, 196–217 (2004)
Ranjan, J.: Business intelligence: concepts, components, techniques and benefits. J. Theor. Appl. Inf. Technol. 9(1), 60–70 (2009)
Brighten Godfrey, P., Shenker, S., Stoica, I.: Minimizing churn in distributed systems. ACM SIGCOMM 36(4), 147–158 (2006)
Kumar, P.: Impact of business intelligence systems in Indian telecom industry. Bus. Intell. J. 5(2), 358 (2012)
From big data to knowledge: value chain for CSP. Business white paper, Microsoft and Windows are U.S. registered trademarks of Microsoft Corporation. Google™ is a trademark of Google Inc., Hewlett-Packard Development Company (2013)
Choudhury, D., Paul, A.: Community detection in social networks: an overview. Int. J. Res. Eng. Technol. 02(special issue: 02) (2013). eISSN 2319-1163, pISSN 2321-7308
Tantipathananandh, C., Berger-Wolf, T.Y.: Finding communities in dynamic social networks. In: 11th IEEE international conference on data mining (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Khan, N., Shah, A., Khan, S.A., Anjum, A.R. (2018). Proactive Business Intelligence to Give Best Customer Experience to Valued Social Networks in Telecoms. In: Bi, Y., Kapoor, S., Bhatia, R. (eds) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. IntelliSys 2016. Lecture Notes in Networks and Systems, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-319-56994-9_46
Download citation
DOI: https://doi.org/10.1007/978-3-319-56994-9_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56993-2
Online ISBN: 978-3-319-56994-9
eBook Packages: EngineeringEngineering (R0)