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A Collaborative Model for Customer Retention on User Service Experience

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Advances in Computer Communication and Computational Sciences

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 924))

Abstract

The traditional brick-and-mortar economy that we are accustomed to is transforming into a realm that is fully digitized. To enable such an age with modern businesses, differential services through multiple providers must be utilized. This compels service providers to collaborate with one another to maximize their payoffs. The paper suggests a model based on machine learning algorithms to tag loyal customers and provides them better quality of service (QoS) experiences to retain them in a system, thereby affecting the overall payoffs of the e-business as retention of loyal customers proves to be less expensive as compared to acquiring new customers.

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Author information

Authors and Affiliations

  1. Accurate Institute of Management and Technology, Greater Noida, India

    Pushpa Singh

  2. Cochin University of Science & Technology, Kochi, India

    Vishwas Agrawal

Authors
  1. Pushpa Singh
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  2. Vishwas Agrawal
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Corresponding author

Correspondence to Vishwas Agrawal .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Missouri–St. Louis, St. Louis, MO, USA

    Sanjiv K. Bhatia

  2. CSED, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

    Krishn K. Mishra

  4. Department of Information Technology, Rajkiya Engineering College, Azamgarh, Uttar Pradesh, India

    Munesh C. Trivedi

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Singh, P., Agrawal, V. (2019). A Collaborative Model for Customer Retention on User Service Experience. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 924. Springer, Singapore. https://doi.org/10.1007/978-981-13-6861-5_5

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