Evaluation of Customer Loss Analysis for Marketing Campaigns in the Banking Sector

Recep Dur; Sabri Koçer; Özgür Dündar

Makale detayları

Evaluation of Customer Loss Analysis for Marketing Campaigns in the Banking Sector

Yazarlar:

Recep Dur | Sabri Koçer | Özgür Dündar

Yayıncı:

Gazi University

Ana Başlıklar:

Mühendislik

Dergi:

Politeknik Dergisi Vol.26 Issue 2, pp.759-764

Belge Tipi:

Makale

Yayın Tarihi:

5/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001293100

pISSN:

2147-9429

Anahtar kelimeler:

Özet:

 In this study, customer loss analysis conducted for mobile marketing campaigns in the banking sector. Mobile marketing is a frequently used marketing method, and SMS Short Message Service is the most commonly used mobile marketing tool due to its wide range of customers. However, mobile marketing activities may cause customer loss in case of irrelevant and frequent submission if customers dont want to receive advertising notifications. The data set used in the analysis includes 22 attributes belonging to 29,635 customers and class information about whether customers block marketing SMS. The obtained data set was classified by logistic regression, artificial neural networks and support vector machines, and the classification performances of the algorithms were compared. Results show that all three methods have similar accuracy, precision, recall and F-score values while Logistic regression method is slightly better than others.

 In this study, customer loss analysis conducted for mobile marketing campaigns in the banking sector. Mobile marketing is a frequently used marketing method, and SMS Short Message Service is the most commonly used mobile marketing tool due to its wide range of customers. However, mobile marketing activities may cause customer loss in case of irrelevant and frequent submission if customers dont want to receive advertising notifications. The data set used in the analysis includes 22 attributes belonging to 29,635 customers and class information about whether customers block marketing SMS. The obtained data set was classified by logistic regression, artificial neural networks and support vector machines, and the classification performances of the algorithms were compared. Results show that all three methods have similar accuracy, precision, recall and F-score values while Logistic regression method is slightly better than others.

 In this study, customer loss analysis conducted for mobile marketing campaigns in the banking sector. Mobile marketing is a frequently used marketing method, and SMS Short Message Service is the most commonly used mobile marketing tool due to its wide range of customers. However, mobile marketing activities may cause customer loss in case of irrelevant and frequent submission if customers dont want to receive advertising notifications. The data set used in the analysis includes 22 attributes belonging to 29,635 customers and class information about whether customers block marketing SMS. The obtained data set was classified by logistic regression, artificial neural networks and support vector machines, and the classification performances of the algorithms were compared. Results show that all three methods have similar accuracy, precision, recall and F-score values while Logistic regression method is slightly better than others.

 Bu çalışmada, bankacılık sektöründe mobil pazarlama kampanyalarına yönelik müşteri kayıp analizi gerçekleştirilmiştir. Mobil pazarlama sıklıkla kullanılan bir pazarlama yöntemi olup SMS Short Message ServiceKısa Mesaj Hizmeti ulaştığı geniş kullanım kitlesi sebebiyle en sık kullanılan mobil pazarlama aracıdır. Bununla beraber alakasız ve sık gönderim gibi etkenlerden dolayı müşteriler reklam bildirimi almak istemeyebilirler ve mobil pazarlama faaliyetleri sebebiyle müşteri kaybı yaşanabilir. Analizde kullanılan veri setinde 29.635 müşteriye ait 22 öznitelikler ve müşterilerin pazarlama SMSlerini engelleyip engellemediğine dair sınıf bilgisini içermektedir. Elde edilen veri seti lojistik regresyon, yapay sinir ağları ve destek vektör makineleri ile sınıflandırılarak algoritmalara ait sınıflandırma performansları karşılaştırılmıştır. Her üç yöntemin doğruluk, kesinlik, duyarlılık ve F-Skor değerleri birbirine yakın çıkarken Lojistik regresyon diğer sınıflandırma yöntemlerinden az da olsa daha iyi sonuç vermiştir.

Makale detayları

Evaluation of Customer Loss Analysis for Marketing Campaigns in the Banking Sector

Yazarlar:

Recep Dur | Sabri Koçer | Özgür Dündar

Yayıncı:

Gazi University

Ana Başlıklar:

Mühendislik

Dergi:

Politeknik Dergisi Vol.26 Issue 2, pp.759-764

Belge Tipi:

Makale

Yayın Tarihi:

5/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001293100

pISSN:

2147-9429

Classification

customer churn analysis

data mining

machine learningSınıflandırma

müşteri kayıp analizi

veri madenciliği

makine öğren

Sayı

Makale detayları

Yazarlar: Recep Dur | Sabri Koçer | Özgür Dündar

Yayıncı: Gazi University

Ana Başlıklar: Mühendislik

Dergi: Politeknik Dergisi Vol.26 Issue 2, pp.759-764

Belge Tipi: Makale

Yayın Tarihi: 5/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001293100

pISSN: 2147-9429

Sayı

Yazarlar:

Recep Dur | Sabri Koçer | Özgür Dündar

Yayıncı:

Gazi University

Ana Başlıklar:

Mühendislik

Dergi:

Politeknik Dergisi Vol.26 Issue 2, pp.759-764

Belge Tipi:

Makale

Yayın Tarihi:

5/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001293100

pISSN:

2147-9429