A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs

Selcuk Cebi; Cengiz Kahraman; Basar Oztaysi; Sezi Cevik Onar

doi:10.1007/978-3-031-97985-9_72

A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs

Selcuk Cebi^*, Cengiz Kahraman, Basar Oztaysi, Sezi Cevik Onar

^*Corresponding author for this work

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This study proposes a fuzzy inference-based loyalty program aimed at enhancing customer loyalty by considering shopping frequency, average spending, and subscription behavior. Developed to overcome the limitations of traditional loyalty programs, the proposed system analyzes customer behavioral data to offer personalized discounts. The model uses shopping frequency, average spending, and recency as input parameters, which are modeled using fuzzy logic to calculate a customer loyalty score. These scores are then utilized to determine tailored discount rates based on customer profiles. The performance of the model was validated through a case study, demonstrating its effectiveness in increasing customer satisfaction and encouraging repeat purchases. This approach provides businesses with a data-driven and flexible framework for designing loyalty programs.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference
Editors	Cengiz Kahraman, Basar Oztaysi, Selcuk Cebi, Sezi Cevik Onar, Cagri Tolga, Irem Ucal Sari, Irem Otay
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	655-663
Number of pages	9
ISBN (Print)	9783031979842
DOIs	https://doi.org/10.1007/978-3-031-97985-9_72
Publication status	Published - 2025
Event	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 - Istanbul, Turkey Duration: 29 Jul 2025 → 31 Jul 2025

Publication series

Name	Lecture Notes in Networks and Systems
Volume	1528 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025
Country/Territory	Turkey
City	Istanbul
Period	29/07/25 → 31/07/25

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

Customer loyalty
Fuzzy inference system
Loyalty program
Mamdani

Access to Document

10.1007/978-3-031-97985-9_72

Cite this

Cebi, S., Kahraman, C., Oztaysi, B., & Onar, S. C. (2025). A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs. In C. Kahraman, B. Oztaysi, S. Cebi, S. Cevik Onar, C. Tolga, I. Ucal Sari, & I. Otay (Eds.), Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference (pp. 655-663). (Lecture Notes in Networks and Systems; Vol. 1528 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-97985-9_72

Cebi, Selcuk ; Kahraman, Cengiz ; Oztaysi, Basar et al. / A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs. Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. editor / Cengiz Kahraman ; Basar Oztaysi ; Selcuk Cebi ; Sezi Cevik Onar ; Cagri Tolga ; Irem Ucal Sari ; Irem Otay. Springer Science and Business Media Deutschland GmbH, 2025. pp. 655-663 (Lecture Notes in Networks and Systems).

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title = "A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs",

abstract = "This study proposes a fuzzy inference-based loyalty program aimed at enhancing customer loyalty by considering shopping frequency, average spending, and subscription behavior. Developed to overcome the limitations of traditional loyalty programs, the proposed system analyzes customer behavioral data to offer personalized discounts. The model uses shopping frequency, average spending, and recency as input parameters, which are modeled using fuzzy logic to calculate a customer loyalty score. These scores are then utilized to determine tailored discount rates based on customer profiles. The performance of the model was validated through a case study, demonstrating its effectiveness in increasing customer satisfaction and encouraging repeat purchases. This approach provides businesses with a data-driven and flexible framework for designing loyalty programs.",

keywords = "Customer loyalty, Fuzzy inference system, Loyalty program, Mamdani",

author = "Selcuk Cebi and Cengiz Kahraman and Basar Oztaysi and Onar, \{Sezi Cevik\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 ; Conference date: 29-07-2025 Through 31-07-2025",

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Cebi, S, Kahraman, C , Oztaysi, B & Onar, SC 2025, A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs. in C Kahraman, B Oztaysi, S Cebi, S Cevik Onar, C Tolga, I Ucal Sari & I Otay (eds), Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. Lecture Notes in Networks and Systems, vol. 1528 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 655-663, 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025, Istanbul, Turkey, 29/07/25. https://doi.org/10.1007/978-3-031-97985-9_72

A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs. / Cebi, Selcuk; Kahraman, Cengiz ; Oztaysi, Basar et al.
Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. ed. / Cengiz Kahraman; Basar Oztaysi; Selcuk Cebi; Sezi Cevik Onar; Cagri Tolga; Irem Ucal Sari; Irem Otay. Springer Science and Business Media Deutschland GmbH, 2025. p. 655-663 (Lecture Notes in Networks and Systems; Vol. 1528 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Oztaysi, Basar

AU - Onar, Sezi Cevik

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - This study proposes a fuzzy inference-based loyalty program aimed at enhancing customer loyalty by considering shopping frequency, average spending, and subscription behavior. Developed to overcome the limitations of traditional loyalty programs, the proposed system analyzes customer behavioral data to offer personalized discounts. The model uses shopping frequency, average spending, and recency as input parameters, which are modeled using fuzzy logic to calculate a customer loyalty score. These scores are then utilized to determine tailored discount rates based on customer profiles. The performance of the model was validated through a case study, demonstrating its effectiveness in increasing customer satisfaction and encouraging repeat purchases. This approach provides businesses with a data-driven and flexible framework for designing loyalty programs.

AB - This study proposes a fuzzy inference-based loyalty program aimed at enhancing customer loyalty by considering shopping frequency, average spending, and subscription behavior. Developed to overcome the limitations of traditional loyalty programs, the proposed system analyzes customer behavioral data to offer personalized discounts. The model uses shopping frequency, average spending, and recency as input parameters, which are modeled using fuzzy logic to calculate a customer loyalty score. These scores are then utilized to determine tailored discount rates based on customer profiles. The performance of the model was validated through a case study, demonstrating its effectiveness in increasing customer satisfaction and encouraging repeat purchases. This approach provides businesses with a data-driven and flexible framework for designing loyalty programs.

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A2 - Oztaysi, Basar

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A2 - Cevik Onar, Sezi

A2 - Tolga, Cagri

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ER -

Cebi S, Kahraman C , Oztaysi B, Onar SC. A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs. In Kahraman C, Oztaysi B, Cebi S, Cevik Onar S, Tolga C, Ucal Sari I, Otay I, editors, Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference. Springer Science and Business Media Deutschland GmbH. 2025. p. 655-663. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-97985-9_72

A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs

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Bibliographical note

Keywords

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