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

Mona Mosa, Nedaa Agami, Ghada Elkhayat and Mohamed Kholief
Additional contact information
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

International Journal of Enterprise Information Systems (IJEIS), 2020, vol. 16, issue 4, 80-100

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.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJEIS.2020100105 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jeis00:v:16:y:2020:i:4:p:80-100

Access Statistics for this article

International Journal of Enterprise Information Systems (IJEIS) is currently edited by Gianluigi Viscusi

More articles in International Journal of Enterprise Information Systems (IJEIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().