Rfm Feature Engineering
RFM Feature Engineering is a methodological construct in customer analytics that operationalizes customer behavior by transforming raw transactional data into the composite RFM (Recency, Frequency, Monetary) features, distinguishing it from general feature engineering through its specific theoretical grounding in behavioral scoring and temporal purchasing dynamics.
23
Publications
1.7K
Citations
77
Authors
37
Institutions
Publications per year
2017–2026
12
Parents
23
1–5 of 23
77
2
h-index
National Yunlin University of Science and Technology, Taiwan
1 publications · 28 citations
1
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1
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1
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University of Electronic Science and Technology of China, China
1 publications · 32 citations
1
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1–5 of 77
37
National Yunlin University of Science and Technology
Douliu, Taiwan
2 h-index
4 publications
904 citations
National Chung Cheng University
Minxiong, Taiwan
2 h-index
5 publications
291 citations
Kütahya Dumlupınar Üniversitesi
Kütahya, Türkiye
1 h-index
1 publications
137 citations

Maulana Abul Kalam Azad University of Technology, West Bengal
Kolkata, India
1 h-index
3 publications
108 citations

Gono University
Dhaka, Bangladesh
1 h-index
1 publications
29 citations

Beijing University of Posts and Telecommunications
Beijing, China
1 h-index
4 publications
132 citations

London South Bank University
London, United Kingdom
1 h-index
3 publications
735 citations
University of Wisconsin–Madison
Madison, United States
1 h-index
1 publications
33 citations
1–8 of 37
2 publications · 123 citations
2
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2 publications · 495 citations
2
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1 publications · 245 citations
1
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BSR · 1 publications · 26 citations
1
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Conference · 1 publications · 33 citations
1
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