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Customer Retention Prediction with CNN

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Data Mining and Big Data (DMBD 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1071))

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Abstract

The prediction of customer retention provides competitive advantage to enterprises. When customer purchases more with satisfaction, it will increase customer retention. Customer repurchase behavior represents customer with satisfaction on enterprise to buy again resulting in customer retention. In e-commerce and telemarketing, trust and loyalty are key factors influencing customer repurchase behavior. In the past, most researches were relied on questionnaire survey to collect data. The drawbacks of such approach are those participants may not be willing to fill the lengthy questions which caused low data collection rate and even low quality data being collected. This study is to apply data driven techniques to extract information from transaction logs in ERP system utilized to compute trust and loyalty based on the verified formulation. The values of defined trust and loyalty are treated as independent variables to predict customer repurchase behavior by Convolutional Neural Networks (CNNs). The prediction accuracy reaches 84%.

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Author information

Authors and Affiliations

  1. Department of Business Administration, National Central University, No. 300, Jhongda Road, Jhongli City, 32001, Taoyuan County, Taiwan (R.O.C.)

    Yen Huei Ko, Ping Yu Hsu, Yang Ruei Jheng & Zhi Chao Luo

  2. Department of Industrial Engineering and Management, Ming Chi University of Technology, No. 84, Gongzhuan Road, Taishan Dist., New Taipei City, 24301, Taiwan (R.O.C.)

    Ming Shien Cheng

Authors
  1. Yen Huei Ko
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  2. Ping Yu Hsu
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  3. Ming Shien Cheng
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  4. Yang Ruei Jheng
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  5. Zhi Chao Luo
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Corresponding author

Correspondence to Ming Shien Cheng .

Editor information

Editors and Affiliations

  1. Department of Machine Intelligence, Peking University, Beijing, China

    Ying Tan

  2. Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Ko, Y.H., Hsu, P.Y., Cheng, M.S., Jheng, Y.R., Luo, Z.C. (2019). Customer Retention Prediction with CNN. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2019. Communications in Computer and Information Science, vol 1071. Springer, Singapore. https://doi.org/10.1007/978-981-32-9563-6_11

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  • DOI: https://doi.org/10.1007/978-981-32-9563-6_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9562-9

  • Online ISBN: 978-981-32-9563-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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