Optimising customer retention: An AI-driven personalised pricing approach

Yasin Ortakci; Huseyin Seker

doi:10.1016/j.cie.2024.109920

Optimising customer retention: An AI-driven personalised pricing approach

Yasin Ortakci^*, Huseyin Seker

^*Corresponding author for this work

Karabuk University

Research output: Contribution to journal › Article › peer-review

3 Citations (SciVal)

Original language	English
Article number	109920
Journal	Computers and Industrial Engineering
Volume	188
DOIs	https://doi.org/10.1016/j.cie.2024.109920
Publication status	Published (VoR) - Feb 2024

Funding

This work was supported by the Scientific and Technological Research Council of Türkiye (TÜBİTAK) under the BIDEB-2219 International Postdoctoral Research Fellowship Programme grant number 1059B192101063 .

Funders	Funder number
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	1059B192101063, BIDEB-2219

Keywords

Artificial intelligence
Customer churn
Feature selection
Machine learning
Personalised pricing

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10.1016/j.cie.2024.109920

Cite this

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title = "Optimising customer retention: An AI-driven personalised pricing approach",

keywords = "Artificial intelligence, Customer churn, Feature selection, Machine learning, Personalised pricing",

author = "Yasin Ortakci and Huseyin Seker",

note = "Publisher Copyright: {\textcopyright} 2024 Elsevier Ltd",

year = "2024",

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doi = "10.1016/j.cie.2024.109920",

language = "English",

volume = "188",

journal = "Computers and Industrial Engineering",

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AU - Ortakci, Yasin

AU - Seker, Huseyin

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KW - Machine learning

KW - Personalised pricing

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JO - Computers and Industrial Engineering

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Optimising customer retention: An AI-driven personalised pricing approach

Funding

Keywords

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