Application of data mining techniques in customer relationship management: A literature review and classification

By Eric Wai Ting Ngai, Xiu Li, Dorothy C. K. Chau. 2009

1,308 citations recorded by the source corpus.

Subfields: Information Systems, Marketing, Organizational Behavior and Human Resource Management, Recommender Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Caiming Xiong
2. Richard Socher
3. Eric Wai Ting Ngai
4. Farnoosh Khodakarami
5. Yolande E. Chan
6. Victor Zhong
7. Yong Hu
8. Graham Neubig

In Marketing

1. Eric Wai Ting Ngai
2. Farnoosh Khodakarami
3. Yolande E. Chan
4. Victor Zhong

In Organizational Behavior and Human Resource Management

1. Eric Wai Ting Ngai
2. Farnoosh Khodakarami
3. Yolande E. Chan
4. Muhammad Turki Alshurideh

In Recommender Systems

1. Caiming Xiong

Citations in the corpus

• Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning (2017, background): “Relational databases store a vast amount of today’s information and provide the foundation of applications such as medical records (Hillestad et al., 2005), financial markets (Beck et al., 2000), and customer relations management (Ngai et al., 2009).”
• Exploring the role of customer relationship management (CRM) systems in customer knowledge creation (2014, background): “It involves selecting, exploring and modeling large amounts of data to uncover previously unknown patterns, and ultimately comprehensible information, from large databases’’ [44,64].”
• Loyalty program effectiveness: Theoretical reviews and practical proofs (2020, background): “One of the good loyalty programs uses is that it can be used to target customers or classified or segmented them then targeted them easily based on the loyalty program objectives (Ngai et al., 2009).”
• Deep learning detecting fraud in credit card transactions (2018, methodology): “More recently, Deep Learning algorithms have been used in areas that require the prediction of human behavior such as customer relationship management, recommendation systems and mobile advertising [5]-[7].”
• The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature (2011, background): “Each was classified according to the following steps [53].”
• Survey on Deep Neural Networks in Speech and Vision Systems (2019, background): “However, recent advancements in IS are permeating almost every aspect of our life with the introduction of intelligent transportation [1-10], intelligent diagnosis and health monitoring for precision medicine [11-14], robotics and automation in home appliances [15], virtual online assistance [16], e”
• Conceptualising electronic word of mouth activity: An input‐process‐output perspective (2011, neutral): “Source: Ngai et al. (2009) Discussion on classification results Exclude”
• How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study (2015, neutral): “…review of articles dealing with ‘big data’ related topics based on a similar approach used by Ngai and Wat (2002) in electronic commerce, (E. W. T. Ngai, Xiu, & Chau, 2009) in CRM and data mining and (E. W. T. Ngai, Moon, Riggins, & Yi, 2008), (Samuel Fosso Wamba, Abhijith Anand, & Lemuria…”