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Combining unsupervised and supervised classification for customer value discovery in the telecom industry: a deep learning approach

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Abstract

Customer behaviour analysis in a telecom market is a challenging task in the customer relationship management area. In this paper, we propose a customer behaviour recognition model that combines unsupervised classification and supervised classification methods. First, considering the complexity and uncertainty of consumption behaviour, a hybrid model of K-means clustering, the entropy method and customer portrait analysis is applied to segment customers. Second, the segmentation results are subsequently incorporated into the proposed multi-head self-attention-based nested long short-term memory classifier to evaluate the performance of customer behaviour recognition. Third, the proposed framework is applied to a real case obtained from the China telecom market. The results indicate that our model is significantly superior to other traditional customer behaviour classification models. In addition, medium-value customers will make full use of the mobile traffic packet, and the package utilization rate of high-value groups is lower, which may benefit the precision marketing of telecom companies.

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Acknowledgements

This paper was supported by the National Natural Science Foundation of China (No. 72071070), the Fundamental Research Funds for the Central Universities (No. JZ2020HGTB0038), the National Natural Science Foundation of China (Nos. 71601063, 72071058).

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Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, China

    Yang Zhao, Zhen Shao, Wei Zhao, Jun Han, Qingru Zheng & Ran Jing

  2. Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Ministry of Education, Hefei, 230009, China

    Zhen Shao

  3. Ministry of Education Engineering Research Center for Intelligent Decision-Making and Information System Technologies, Hefei, 230009, China

    Zhen Shao

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  1. Yang Zhao
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  3. Wei Zhao
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  4. Jun Han
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  5. Qingru Zheng
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  6. Ran Jing
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Contributions

YZ: Methodology, Data curation, Writing-review & editing, Supervision. ZS: Methodology, Conceptualization, Funding acquisition. WZ: Visualization. JH: Validation, Visualization. QZ: Methodology, Software, Visualization. Ran Jing: Writing-original draft.

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Correspondence to Zhen Shao.

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Zhao, Y., Shao, Z., Zhao, W. et al. Combining unsupervised and supervised classification for customer value discovery in the telecom industry: a deep learning approach. Computing 105, 1395–1417 (2023). https://doi.org/10.1007/s00607-023-01150-4

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Mathematics Subject Classification