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The paper presents a deep learning model for improving customer loyalty management in the business-to-business (B2B) field. In industries where technology is continuously evolving and competition is fierce, it is critical to maintain client loyalty and improve customer satisfaction. To generate a competitive advantage, the project aims to construct a deep learning-supported model to meet these objectives. The research is covered methodologies involving artificial intelligence algorithms such as deep learning to analyze customer behavior and preferences. Customer data was obtained from ERP systems. Afterwards, deep learning models CNN, RNN and LSTM architectures were applied for modelling. The developed B2B-DL model has achieved high success in predicting customer behavior and offering customized offers. Improvements in customer loyalty management will bring great benefits to companies by causing customer satisfaction rates to increase significantly and customer loss to be reduced. Therefore, the study is showed that the use of deep learning methods in the B2B industry can play an important role in customer loyalty management. In the study, LSTM architecure was achieved the best performance with the accurate valuse as %86
| Eser Adı (dc.title) | Campaign and Loyalty Management in B2B Field with Deep Learning Methods |
| Yazar (dc.contributor.author) | Zeki ORALHAN |
| Yazar (dc.contributor.author) | Burcu ORALHAN |
| Tür (dc.type) | Bildiri |
| Açık Erişim Tarihi (dc.date.available) | 2023-12-31 |
| Alt Tür (dc.type.alttur) | Sözel |
| Alt Tür 1 (dc.type.alttur1) | uluslararası |
| Dergi, konferans, armağan kitap adı (dc.relation.journal) | 3 rd International Conference on Design, Research and Development |
| Yayıncı (dc.publisher) | Orclever Science&Resarch Group |
| Tarih (dc.date.issued) | 2023 |
| Yayının İlk Sayfa Sayısı (dc.identifier.startpage) | 37 |
| Yayının Son Sayfa Sayısı (dc.identifier.endpage) | 37 |
| ORCID No (dc.contributor.orcid) | https://orcid.org/0000-0003-2841-6115 |
| Özet (dc.description.abstract) | The paper presents a deep learning model for improving customer loyalty management in the business-to-business (B2B) field. In industries where technology is continuously evolving and competition is fierce, it is critical to maintain client loyalty and improve customer satisfaction. To generate a competitive advantage, the project aims to construct a deep learning-supported model to meet these objectives. The research is covered methodologies involving artificial intelligence algorithms such as deep learning to analyze customer behavior and preferences. Customer data was obtained from ERP systems. Afterwards, deep learning models CNN, RNN and LSTM architectures were applied for modelling. The developed B2B-DL model has achieved high success in predicting customer behavior and offering customized offers. Improvements in customer loyalty management will bring great benefits to companies by causing customer satisfaction rates to increase significantly and customer loss to be reduced. Therefore, the study is showed that the use of deep learning methods in the B2B industry can play an important role in customer loyalty management. In the study, LSTM architecure was achieved the best performance with the accurate valuse as %86 |
| Dil (dc.language.iso) | İNGİLİZCE |
| DOI Numarası (dc.identifier.doi) | YOK |
| Konu Başlıkları (dc.subject) | Yapay zeka |
| İsmi Geçen (dc.identifier.ismigecen) | Üniversite ismi geçen |
| Dizin Platformu (dc.relation.platform) | Google Scholar |
| WOS Kategorileri (dc.identifier.wos) | Diğer |