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Large-Scale Data Analytics pp 101–127Cite as

Customer Analyst for the Telecom Industry

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Abstract

The telecommunications industry is particularly rich in customer data, and telecom companies want to use this data to prevent customer churn, and improve the revenue per user through personalization and customer acquisition. Massive-scale analytics tools provide an opportunity to achieve this in is a flexible and scalable way. In this context, we have developed IBM Customer Analyst, a components library to analyze customer behavioral data and enable new insights and business scenarios based on the analysis of the relationship between users and the content they create and consume. Due to the massive amount of data and large number of users, this technology is built on IBM Infosphere BigInsights and Apache Hadoop. In this work, we first describe an efficient user profiling framework, with high user profiling quality guarantees, based on mobile web browsing log analysis. We describe the use of the Open Directory Project categories to generate user profiles. We then describe an end-to-end analysis flow and discuss its challenges. Last, we validate our methods through extensive experiments based on real data sets.

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Notes

  1. 1.

    Some countries in fact require some kind of registration to take place but it is not a technological or business requirement.

  2. 2.

    http://www.dmoz.org/.

  3. 3.

    http://lucene.apache.org/.

  4. 4.

    http://www-01.ibm.com/software/data/infosphere/biginsights/.

  5. 5.

    http://code.google.com/p/jaql/.

  6. 6.

    http://rvs.github.com/oozie/index.html.

  7. 7.

    http://www.json.org/.

  8. 8.

    http://www.wikipedia.org/.

  9. 9.

    http://nutch.apache.org/.

  10. 10.

    http://www-01.ibm.com/software/analytics/spss/.

  11. 11.

    http://www.w3.org/RDF/.

  12. 12.

    http://www-01.ibm.com/software/ebusiness/jstart/bigsheets/.

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Acknowledgements

The authors would like to thank Shai Erera and Gilad Barkai for the useful discussions about implementation issues. We also thank Haggai Roitman for sharing thoughts and ideas. Finally, we thank Matin Jouzdani for his support to make it a successful project.

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Authors and Affiliations

  1. IBM Haifa Research Lab, Haifa, Israel

    David Konopnicki & Michal Shmueli-Scheuer

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  1. David Konopnicki
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  2. Michal Shmueli-Scheuer
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Correspondence to David Konopnicki .

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Editors and Affiliations

  1. IBM Research - Ireland, Mulhuddart, Ireland

    Aris Gkoulalas-Divanis

  2. IBM Research - Zurich, Rüschlikon, Switzerland

    Abderrahim Labbi

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Konopnicki, D., Shmueli-Scheuer, M. (2014). Customer Analyst for the Telecom Industry. In: Gkoulalas-Divanis, A., Labbi, A. (eds) Large-Scale Data Analytics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-9242-9_4

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  • DOI: https://doi.org/10.1007/978-1-4614-9242-9_4

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-9241-2

  • Online ISBN: 978-1-4614-9242-9

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