Research Article
BibTex RIS Cite

Artificial Intelligence-Powered Customer Relationship Management System (CRM-AI)

Year 2025, Volume: 6 Issue: 2, 7 - 12
https://doi.org/10.53608/estudambilisim.1800171

Abstract

This study involves developing an AI-powered Customer Relationship Management (CRM) system that aims to digitize and optimize businesses' customer management processes. The developed system securely stores customer data in a central database, tracks customer interactions, and analyzes them using AI algorithms. The project integrates HTML, CSS, JavaScript, PHP, and MySQL technologies to create interactive dashboards for both managers and employees. The AI module analyzes customer behavior, predicts trends, and provides strategic decision support to businesses. The study concluded that data analytics-based decision processes increase customer satisfaction, improve administrative efficiency, and provide businesses with a competitive advantage.

References

  • Alnofeli K. K., Akter, S., Yanamandram, V. 2025. Unlocking the power of AI in CRM: A comprehensive multidimensional exploration, Journal of Innovation & Knowledge, 10(3).1-23. https://doi.org/10.1016/j.jik.2025.100731
  • Woo, Y.J., Junsung, P., Heejun, P. 2024. The impact of AI-enabled CRM systems on organizational competitive advantage: A mixed-method approach using BERTopic and PLS-SEM, Heliyon, 10(16). https://doi.org/10.1016/j.heliyon.2024.e36392
  • Ledro, C., Nosella A., Vinelli A., Dalla Pozza I., Souverain T. 2025. Artificial intelligence in customer relationship management: A systematic framework for a successful integration, Journal of Business Research, 199, 115531. https://doi.org/10.1016/j.jbusres.2025.115531
  • Şeker, P. 2025. Türkiye’de dijital pazarlama stratejilerinde yapay zekânın CRM uygulamalarındaki kullanımı, Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 18(1), 447–462. https://doi.org/10.25287/ohuiibf.1571107
  • Ünal Kestane, S. 2024. CRM (Customer Relationship Management) kavramı üzerine yapılan çalışmaların vosvıewer ile bibliyometrik analizi. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 33(1), 311-329. https://doi.org/10.35379/cusosbil.1396955
  • Berson, A., Smith, SJ., Thearling, K. 2000. Building Data Mining Applications for CRM, McGraw-Hill, ISBN: 978-0071344449.
  • Wang, H., Strong, S. 2022. Web-based customer relationship management systems: Design and implementation, Information Systems Frontiers, 6(1), 5–17.
  • Hernández, M. 2023. Database design for CRM systems: Ensuring data quality and scalability, Information Sciences, 612, 85–96.
  • Kumar, V., Reinartz, W. 2018. Customer Relationship Management: Concept, Strategy, and Tools, Springer.
  • Payne, R., Frow, P. 2019. The CRM value chain: Implementing relationship marketing, Journal of Marketing Management, 22, 135–168.
  • Elgendy, N., Elragal, A. 2019. Big Data Analytics in Support of the Decision Making Process, Procedia Computer Science, 100, 1071–1084. https://doi.org/10.1016/j.procs.2016.09.251
  • Lamba, T. 2021. Artificial Intelligence in CRM: Enhancing Customer Insights, Procedia Economics and Finance, 48, 225–230.
  • Khanna, A.N. 2024. Performance evaluation of AI-enabled CRM systems, IEEE Access, 11, 85732–85745.
  • Choudhury, P.H., Tripathi, L. 2024. Machine learning techniques for CRM: Predicting customer behavior and churn, Expert Systems with Applications, 231, 120–135.
  • Rizzo, F.A., Dutta, G.O. 2023. Secure AI frameworks for customer relationship management systems, IEEE Transactions on Engineering Management, 71(2), 522–538.

Yapay Zekâ Destekli Müşteri İlişkileri Yönetim Sistemi (CRM-AI)

Year 2025, Volume: 6 Issue: 2, 7 - 12
https://doi.org/10.53608/estudambilisim.1800171

Abstract

Bu çalışma, işletmelerin müşteri yönetimi süreçlerini dijitalleştirerek optimize etmeyi amaçlayan yapay zekâ destekli bir Müşteri İlişkileri Yönetim (CRM) sistemi geliştirilmesini kapsamaktadır. Geliştirilen sistem, müşteri verilerinin merkezi bir veritabanında güvenli biçimde saklanmasını, müşteri etkileşimlerinin takip edilmesini ve yapay zekâ algoritmaları ile analiz edilmesini sağlamaktadır. Proje kapsamında; HTML, CSS, JavaScript, PHP ve MySQL teknolojileri entegre edilerek hem yöneticiler hem de çalışanlar için etkileşimli paneller tasarlanmıştır. Yapay zekâ modülü, müşteri davranışlarını analiz ederek eğilim tahmini yapmakta ve işletmelere stratejik karar desteği sunmaktadır. Çalışmanın sonucunda, veri analitiği tabanlı karar süreçlerinin müşteri memnuniyetini artırdığı, yönetimsel verimliliği geliştirdiği ve işletmelere rekabet avantajı sağladığı gözlemlenmiştir.

References

  • Alnofeli K. K., Akter, S., Yanamandram, V. 2025. Unlocking the power of AI in CRM: A comprehensive multidimensional exploration, Journal of Innovation & Knowledge, 10(3).1-23. https://doi.org/10.1016/j.jik.2025.100731
  • Woo, Y.J., Junsung, P., Heejun, P. 2024. The impact of AI-enabled CRM systems on organizational competitive advantage: A mixed-method approach using BERTopic and PLS-SEM, Heliyon, 10(16). https://doi.org/10.1016/j.heliyon.2024.e36392
  • Ledro, C., Nosella A., Vinelli A., Dalla Pozza I., Souverain T. 2025. Artificial intelligence in customer relationship management: A systematic framework for a successful integration, Journal of Business Research, 199, 115531. https://doi.org/10.1016/j.jbusres.2025.115531
  • Şeker, P. 2025. Türkiye’de dijital pazarlama stratejilerinde yapay zekânın CRM uygulamalarındaki kullanımı, Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 18(1), 447–462. https://doi.org/10.25287/ohuiibf.1571107
  • Ünal Kestane, S. 2024. CRM (Customer Relationship Management) kavramı üzerine yapılan çalışmaların vosvıewer ile bibliyometrik analizi. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 33(1), 311-329. https://doi.org/10.35379/cusosbil.1396955
  • Berson, A., Smith, SJ., Thearling, K. 2000. Building Data Mining Applications for CRM, McGraw-Hill, ISBN: 978-0071344449.
  • Wang, H., Strong, S. 2022. Web-based customer relationship management systems: Design and implementation, Information Systems Frontiers, 6(1), 5–17.
  • Hernández, M. 2023. Database design for CRM systems: Ensuring data quality and scalability, Information Sciences, 612, 85–96.
  • Kumar, V., Reinartz, W. 2018. Customer Relationship Management: Concept, Strategy, and Tools, Springer.
  • Payne, R., Frow, P. 2019. The CRM value chain: Implementing relationship marketing, Journal of Marketing Management, 22, 135–168.
  • Elgendy, N., Elragal, A. 2019. Big Data Analytics in Support of the Decision Making Process, Procedia Computer Science, 100, 1071–1084. https://doi.org/10.1016/j.procs.2016.09.251
  • Lamba, T. 2021. Artificial Intelligence in CRM: Enhancing Customer Insights, Procedia Economics and Finance, 48, 225–230.
  • Khanna, A.N. 2024. Performance evaluation of AI-enabled CRM systems, IEEE Access, 11, 85732–85745.
  • Choudhury, P.H., Tripathi, L. 2024. Machine learning techniques for CRM: Predicting customer behavior and churn, Expert Systems with Applications, 231, 120–135.
  • Rizzo, F.A., Dutta, G.O. 2023. Secure AI frameworks for customer relationship management systems, IEEE Transactions on Engineering Management, 71(2), 522–538.
There are 15 citations in total.

Details

Primary Language Turkish
Subjects Satisfiability and Optimisation, Modelling and Simulation, Planning and Decision Making
Journal Section Research Articles
Authors

Ahmet Albayrak 0000-0002-2166-1102

Arafat Şentürk 0000-0002-9005-3565

Mecid El Temir 0009-0000-2364-4229

Publication Date November 4, 2025
Submission Date October 9, 2025
Acceptance Date October 21, 2025
Published in Issue Year 2025 Volume: 6 Issue: 2

Cite

IEEE A. Albayrak, A. Şentürk, and M. El Temir, “Yapay Zekâ Destekli Müşteri İlişkileri Yönetim Sistemi (CRM-AI)”, Journal of ESTUDAM Information, vol. 6, no. 2, pp. 7–12, doi: 10.53608/estudambilisim.1800171.

Journal of ESTUDAM Information is indexed by Index Copernicus, Google ScholarASOS Index and ROAD index.