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A Literature Review of Data Mining Techniques for Enhancing Digital Customer Engagement

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  • Mona Mosa

    (Arab Academy for Science, Technology, and Maritime Transport, Egypt)

  • Nedaa Agami

    (Cairo University, Egypt)

  • Ghada Elkhayat

    (Alexandria University, Egypt)

  • Mohamed Kholief

    (Arab Academy for Science, Technology, and Maritime Transport, Egypt)

Abstract

The evolution of the customer engagement concept had a positive impact on how business and customers interact. The term digital customer engagement emerged to empower such interaction via encouraging customers to use digital channels. Data mining techniques can help in identifying patterns, generating insights, and making predictions for a massive amount of data. The purpose of this paper is to explore the current literature on data mining techniques to enhance digital customer engagement and review the impact of data mining on analyzing customer's attributes and its key performance indicators influenced by digital customer engagement and affecting business success. The scope of the review encompasses the state of the art of scientific methodologies and models applied to identify customers with the highest potential towards digital engagement. A critical analysis also identified gaps in the literature. This study is the first to explicitly consider data mining techniques for enhancing digital customer engagement with a comprehensive analysis of customer's attributes in different domains.

Suggested Citation

  • Mona Mosa & Nedaa Agami & Ghada Elkhayat & Mohamed Kholief, 2020. "A Literature Review of Data Mining Techniques for Enhancing Digital Customer Engagement," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 16(4), pages 80-100, October.
    • Handle: RePEc:igg:jeis00:v:16:y:2020:i:4:p:80-100
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