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Fast RFM Model for Customer Segmentation

Authors:

Linlin TangAuthors Info & Claims

WWW '22: Companion Proceedings of the Web Conference 2022

Pages 965 - 972

https://doi.org/10.1145/3487553.3524707

Published: 16 August 2022 Publication History

Abstract

With booming e-commerce and World Wide Web (WWW), a powerful tool in customer relationship management (CRM), called the RFM analysis model, has been used to ensure that major enterprises make more profit. Combined with data mining technologies, the CRM system can automatically predict the future behavior of customers to raise customer retention rate. However, a key issue is that the existing RFM analysis models are not efficient enough. Thus, in this study, a fast algorithm based on a compact list-based data structure is proposed along with several efficient pruning strategies to address this issue. The new algorithm considers recency (R), frequency (F), and monetary/utility (M) as three different thresholds to discover interesting patterns where the R, F, and M thresholds combined are no less than the user-specified minimum values. More significantly, the downward-closure property of frequency and monetary metrics are utilized to discover super-itemsets. Then, an extensive experimental study demonstrated that the algorithm outperforms state-of-the-art algorithms on various datasets. It is also demonstrated that the proposed algorithm performs well when considering the frequency metric alone.

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Cited By

Li RZhang JHe S(2024)Research on User Behavior Prediction Based on Random Forest Algorithm with RFM Model2024 4th International Conference on Computer Science and Blockchain (CCSB)10.1109/CCSB63463.2024.10735665(133-137)Online publication date: 6-Sep-2024
https://doi.org/10.1109/CCSB63463.2024.10735665
de Oliveira MRosa FDiniz de Souza A(2024)A Method Based on Customer Success Metrics for Software Product Usability AssessmentHCI International 2024 – Late Breaking Papers10.1007/978-3-031-76803-3_2(23-41)Online publication date: 6-Dec-2024
https://doi.org/10.1007/978-3-031-76803-3_2
Kanca SÖzcan TÇelikbilek Y(2023)Bir Tekstil Perakendecisinin Müşterileri İçin RFM Modeli ile Müşteri SegmentasyonuThe Journal of International Scientific Researches10.23834/isrjournal.13397538:3(393-409)Online publication date: 27-Oct-2023
https://doi.org/10.23834/isrjournal.1339753
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Index Terms

Fast RFM Model for Customer Segmentation
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

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Information & Contributors

Information

Published In

cover image ACM Conferences

WWW '22: Companion Proceedings of the Web Conference 2022

April 2022

1338 pages

ISBN:9781450391306

DOI:10.1145/3487553

Editors:
Frédérique Laforest
INSA Lyon, France
,
Raphaël Troncy
EURECOM, France
,
Lionel Médini
Université Lyon 1, France
,
Ivan Herman
W3C / retired

Copyright © 2022 ACM.

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Publication History

Published: 16 August 2022

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Funding Sources

National Key-Research and Development Program of China
National Natural Science Foundation of China
Guangzhou Basic and Applied Basic Research Foundation

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WWW '22

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SIGWEB

WWW '22: The ACM Web Conference 2022

April 25 - 29, 2022

Virtual Event, Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Li RZhang JHe S(2024)Research on User Behavior Prediction Based on Random Forest Algorithm with RFM Model2024 4th International Conference on Computer Science and Blockchain (CCSB)10.1109/CCSB63463.2024.10735665(133-137)Online publication date: 6-Sep-2024
https://doi.org/10.1109/CCSB63463.2024.10735665
de Oliveira MRosa FDiniz de Souza A(2024)A Method Based on Customer Success Metrics for Software Product Usability AssessmentHCI International 2024 – Late Breaking Papers10.1007/978-3-031-76803-3_2(23-41)Online publication date: 6-Dec-2024
https://doi.org/10.1007/978-3-031-76803-3_2
Kanca SÖzcan TÇelikbilek Y(2023)Bir Tekstil Perakendecisinin Müşterileri İçin RFM Modeli ile Müşteri SegmentasyonuThe Journal of International Scientific Researches10.23834/isrjournal.13397538:3(393-409)Online publication date: 27-Oct-2023
https://doi.org/10.23834/isrjournal.1339753
ASLANTAŞ GGENÇGÜL MRUMELLİ MÖZSARAÇ MBAKIRLI G(2023)Customer Segmentation Using K-Means Clustering Algorithm and RFM ModelK-Means Kümeleme Algoritması ve RFM Modeli Kullanarak Müşteri SegmentasyonuDeu Muhendislik Fakultesi Fen ve Muhendislik10.21205/deufmd.202325741825:74(491-503)Online publication date: 15-May-2023
https://doi.org/10.21205/deufmd.2023257418
Pitka TBucko J(2023)Segmenting Customers with Data Analytics Tools: Understanding and Engaging Target AudiencesActa Informatica Pragensia10.18267/j.aip.22012:2(357-378)Online publication date: 10-Oct-2023
https://doi.org/10.18267/j.aip.220
Ahmed Mohammed SSaeed M(2023)Business Intelligence Model for Customer Targeting Using Fuzzy-C-Means and FP-Growth2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA)10.1109/eSmarTA59349.2023.10293648(1-8)Online publication date: 10-Oct-2023
https://doi.org/10.1109/eSmarTA59349.2023.10293648
Hariram SRaja Subramanian RKamalakannan PReddy MDhanasekaran SIshvarya M(2023)Customer Segmentation Analysis leveraging Machine Learning Algorithms2023 IEEE International Conference on Contemporary Computing and Communications (InC4)10.1109/InC457730.2023.10263179(1-8)Online publication date: 21-Apr-2023
https://doi.org/10.1109/InC457730.2023.10263179
Chen CGan WChen JWan S(2023)FSKY-Miner: Fast Mining of Skyline Patterns2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00136(795-802)Online publication date: 21-Dec-2023
https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00136
Pillai PKulkarni P(2023)A Study on Heuristic and Non-Heuristic Clustering Techniques for Customer Segmentation2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10307705(1-5)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10307705
Wan SDeng JGan WChen JYu P(2022)Fast Mining RFM Patterns for Behavioral Analytics2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)10.1109/DSAA54385.2022.10032434(1-10)Online publication date: 13-Oct-2022
https://doi.org/10.1109/DSAA54385.2022.10032434
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