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

^*Bu çalışma için yazışmadan sorumlu yazar

Endüstri Mühendisliği Bölümü

Yildiz Technical University
WP2-EELISA University Alliance

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference
Editörler	Cengiz Kahraman, Basar Oztaysi, Selcuk Cebi, Sezi Cevik Onar, Cagri Tolga, Irem Ucal Sari, Irem Otay
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	655-663
Sayfa sayısı	9
ISBN (Basılı)	9783031979842
DOI'lar	https://doi.org/10.1007/978-3-031-97985-9_72
Yayın durumu	Yayınlandı - 2025
Etkinlik	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025 - Istanbul, Türkiye Süre: 29 Tem 2025 → 31 Tem 2025

Yayın serisi

Adı	Lecture Notes in Networks and Systems
Hacim	1528 LNNS
ISSN (Basılı)	2367-3370
ISSN (Elektronik)	2367-3389

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025
Ülke/Bölge	Türkiye
Şehir	Istanbul
Periyot	29/07/25 → 31/07/25

Bibliyografik not

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

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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; Hac. 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. editör / 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",

year = "2025",

doi = "10.1007/978-3-031-97985-9\_72",

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booktitle = "Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference",

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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, hac. 1528 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 655-663, 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025, Istanbul, Türkiye, 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; Hac. 1528 LNNS).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - A Fuzzy Inference-Based Dynamic Discount Algorithm Proposal for Customer Loyalty Programs

AU - Cebi, Selcuk

AU - Kahraman, Cengiz

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.

KW - Customer loyalty

KW - Fuzzy inference system

KW - Loyalty program

KW - Mamdani

UR - https://www.scopus.com/pages/publications/105012924535

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

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AN - SCOPUS:105012924535

SN - 9783031979842

T3 - Lecture Notes in Networks and Systems

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EP - 663

BT - Intelligent and Fuzzy Systems - Artificial Intelligence in Human-Centric, Resilient and Sustainable Industries, Proceedings of the INFUS 2025 Conference

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A2 - Oztaysi, Basar

A2 - Cebi, Selcuk

A2 - Cevik Onar, Sezi

A2 - Tolga, Cagri

A2 - Ucal Sari, Irem

A2 - Otay, Irem

PB - Springer Science and Business Media Deutschland GmbH

T2 - 7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025

Y2 - 29 July 2025 through 31 July 2025

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, editörler, 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

Özet

Yayın serisi

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Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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