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A Hybrid Machine Learning Approach for Customer Loyalty Prediction

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Book cover Neural Computing for Advanced Applications (NCAA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1449))

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Abstract

Customer loyalty prediction is one of the most common applications of machine learning in Customer Relationship Management (CRM). Many research studies have tried to compare the effectiveness of different machine learning techniques applied for the model development. Also due to the simplicity and effectiveness, customer purchase behavioral attributes, such as, Recency, Frequency, and Monetary Value (RFM) are commonly used for predicting the customer lifetime value as a measure of loyalty. However, since RFM focuses on the purchase behaviours of customers only, it often overlooks the effect of other important factors to loyalty such as customer satisfaction and product experience. In this paper, a two-stage hybrid machine learning approach is designed to address this. Firstly, both unsupervised clustering and supervised classification model are used in the predication model building in order to realize the possible incremental value of hybrid model combining two learning techniques. Secondly, the proposed model is trained with behavourial RFM attributes and attitudinal factors such as customer satisfaction and product attributes, in order to better capture the influencing factors to loyalty.

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Authors and Affiliations

  1. School of Computer Science, Faculty of Technology, University of Sunderland, London, UK

    Hiu Fai Lee & Ming Jiang

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  1. Hiu Fai Lee
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  2. Ming Jiang
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Correspondence to Hiu Fai Lee .

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Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Haijun Zhang

  2. Nanfang College of Sun Yat-sen University, Guangzhou, China

    Zhi Yang

  3. Hefei University of Technology, Hefei, China

    Zhao Zhang

  4. Chongqing University, Chongqing, China

    Zhou Wu

  5. South China Normal University, Guangzhou, China

    Tianyong Hao

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Lee, H.F., Jiang, M. (2021). A Hybrid Machine Learning Approach for Customer Loyalty Prediction. In: Zhang, H., Yang, Z., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2021. Communications in Computer and Information Science, vol 1449. Springer, Singapore. https://doi.org/10.1007/978-981-16-5188-5_16

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  • DOI: https://doi.org/10.1007/978-981-16-5188-5_16

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  • Online ISBN: 978-981-16-5188-5

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