The Effect of Customer Behavior on Conversion Rates in Digital Marketing Campaigns: Data Analytics and Random Forest Model Approach

Bilge Doğanlı

Makale detayları

The Effect of Customer Behavior on Conversion Rates in Digital Marketing Campaigns: Data Analytics and Random Forest Model Approach

Yazarlar:

Bilge Doğanlı

Yayıncı:

Ahmet Arif EREN

Ana Başlıklar:

Büyük Veri

Dergi:

Politik Ekonomik Kuram Vol.9 Issue 2, pp.596-610

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001350868

pISSN:

2587-2567

Anahtar kelimeler:

Özet:

 This study was conducted by analyzing the data of customers participating in a digital marketing campaign and examining the factors affecting conversion rates. As a result of the calculated Exploratory Data Analysis EDA, it was determined that age, income, website interactions and advertising expenditure variables had significant effects on conversion. In the modeling phase, the Random Forest classification algorithm was used to estimate conversion rates. The overall accuracy score of the model was calculated as 88.12. However, it was observed that the model was weak in predicting the No Conversion class, but on the contrary, it showed high performance in the Conversion class. This situation, which arises from the unbalanced data distribution, shows that class balance strategies can be used to improve the model. The results of the analysis show that advertising expenditures, website visits and click-through rates have significant effects on conversion. These findings emphasize that digital marketing strategies should be optimized with personalized approaches.

 This study was conducted by analyzing the data of customers participating in a digital marketing campaign and examining the factors affecting conversion rates. As a result of the calculated Exploratory Data Analysis EDA, it was determined that age, income, website interactions and advertising expenditure variables had significant effects on conversion. In the modeling phase, the Random Forest classification algorithm was used to estimate conversion rates. The overall accuracy score of the model was calculated as 88.12. However, it was observed that the model was weak in predicting the No Conversion class, but on the contrary, it showed high performance in the Conversion class. This situation, which arises from the unbalanced data distribution, shows that class balance strategies can be used to improve the model. The results of the analysis show that advertising expenditures, website visits and click-through rates have significant effects on conversion. These findings emphasize that digital marketing strategies should be optimized with personalized approaches.

 This study was conducted by analyzing the data of customers participating in a digital marketing campaign and examining the factors affecting conversion rates. As a result of the calculated Exploratory Data Analysis EDA, it was determined that age, income, website interactions and advertising expenditure variables had significant effects on conversion. In the modeling phase, the Random Forest classification algorithm was used to estimate conversion rates. The overall accuracy score of the model was calculated as 88.12. However, it was observed that the model was weak in predicting the No Conversion class, but on the contrary, it showed high performance in the Conversion class. This situation, which arises from the unbalanced data distribution, shows that class balance strategies can be used to improve the model. The results of the analysis show that advertising expenditures, website visits and click-through rates have significant effects on conversion. These findings emphasize that digital marketing strategies should be optimized with personalized approaches.

 Bu çalışma, e ticaret siteleri aracılığı ile alışverişlerini gerçekleştiren ve bir dijital pazarlama kampanyasına katılan müşterilerin verilerinin analiz edilerek, dönüşüm conversion oranlarını etkileyen faktörlerin incelenmesi ile gerçekleştirilmişti. Hesaplanan Keşifsel Veri Analizi EDA sonucunda, yaş, gelir, web sitesi etkileşimleri ve reklam harcamaları değişkenlerinin, dönüşüm üzerinde önemli etkiler yarattığı tespit edilmiştir. Modelleme aşamasında, dönüşüm oranlarını tahmin etmek için Random Forest sınıflandırma algoritması kullanılmıştır. Modelin genel doğruluk skoru 88.12 olarak hesaplanmıştır. Ancak, modelin Dönüşüm Yok sınıfını tahmin etmede zayıf kaldığı, bunun aksine Dönüşüm sınıfında yüksek bir performans sergilediği görülmüştür. Dengesiz veri dağılımından kaynaklanan bu durum, modelin iyileştirilmesi için sınıf dengesi stratejilerinin kullanılabileceğini göstermektedir. Analiz sonuçları, reklam harcamaları, web sitesi ziyaretleri ve tıklama oranlarının dönüşüm üzerinde önemli etkileri olduğunu göstermektedir. Bu bulgular, dijital pazarlama stratejilerinin kişiselleştirilmiş yaklaşımlarla optimize edilmesi gerektiğini vurgulamaktadır.

Makale detayları

The Effect of Customer Behavior on Conversion Rates in Digital Marketing Campaigns: Data Analytics and Random Forest Model Approach

Yazarlar:

Bilge Doğanlı

Yayıncı:

Ahmet Arif EREN

Ana Başlıklar:

Büyük Veri

Dergi:

Politik Ekonomik Kuram Vol.9 Issue 2, pp.596-610

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001350868

pISSN:

2587-2567

Digital Marketing

Customer Conversion

Data Analytics

Random Forest

Campaign PerformanceDijital Pazarlama

Müşteri Dönüşümü

Veri Analitiği

Random Forest

Kampanya Performansı

Sayı

Makale detayları

Yazarlar: Bilge Doğanlı

Yayıncı: Ahmet Arif EREN

Ana Başlıklar: Büyük Veri

Dergi: Politik Ekonomik Kuram Vol.9 Issue 2, pp.596-610

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001350868

pISSN: 2587-2567

Sayı

Yazarlar:

Bilge Doğanlı

Yayıncı:

Ahmet Arif EREN

Ana Başlıklar:

Büyük Veri

Dergi:

Politik Ekonomik Kuram Vol.9 Issue 2, pp.596-610

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001350868

pISSN:

2587-2567