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EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing pp 279–286Cite as

Randomized Agent-Based Model for Mobile Customer Retention Behaviour Prediction

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Abstract

Due to the development of technology, mobile phones have a crucial role in human life. Multiple sim card phones and a single person using multiple mobile phones are common nowadays. Telecommunication is a major area where big data technologies are needed. Competition among the telecommunication companies is high due to customer churn. Customer retention in telecom companies is one of the major problems. In this paper, we propose a Randomized Method (RM) using Map and Reduce big data functions to avoid data duplication in the customer call data of telecommunication application. We use agent-based model (ABM) to predict the complex customer behaviour for the retention of customers with a particular telecommunication service. Agent-based model increases the prediction accuracy due to its dynamic nature of agents. ABM suggests rules based on mobile user variable features using multiple agents. This paper shows the effectiveness RM with MapReduce along with agent-based model to predict customer retention behaviour. The benefit of this proposed system is simple, cost-effective and flexible prediction model with high business value.

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Author information

Authors and Affiliations

  1. Information Technology, School of Engineering, Cochin University of Science and Technology, Kochi, India

    N. Sandhya

  2. Department of Computer Science, Cochin University of Science and Technology, Kochi, India

    Philip Samuel

  3. Department of ship Technology, Cochin University of Science and Technology, Kochi, India

    Mariamma Chacko

Authors
  1. N. Sandhya
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  2. Philip Samuel
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  3. Mariamma Chacko
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Editor information

Editors and Affiliations

  1. Department of Computer Science & Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Anandakumar Haldorai

  2. Department of Computer Science & Engineering, Presidency University, Bengaluru, India

    Arulmurugan Ramu

  3. Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Sudha Mohanram

  4. Department of Electrical Engineering, Faculty of Engineering, University of Malaysia, Kuala Lumpur, Kuala Lumpur, Malaysia

    Chow Chee Onn

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Sandhya, N., Samuel, P., Chacko, M. (2020). Randomized Agent-Based Model for Mobile Customer Retention Behaviour Prediction. In: Haldorai, A., Ramu, A., Mohanram, S., Onn, C. (eds) EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-19562-5_28

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  • DOI: https://doi.org/10.1007/978-3-030-19562-5_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19561-8

  • Online ISBN: 978-3-030-19562-5

  • eBook Packages: EngineeringEngineering (R0)

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