Direct Marketing Campaign Response Analysis using Logistic Regression, CART and Support Vector Machines

Ankit Bansal

Abstract: Direct marketing remains a pivotal strategy for businesses aiming to engage customers with personalized content. This article explores how analytics can enhance the effectiveness of direct marketing campaigns by predicting customer responses. By leveraging statistical models and machine learning, businesses can optimize their marketing efforts, reduce costs, and improve conversion rates. In this paper we will focus on comparison of multiple machine learning techniques and learn why SVM (Support vector machine) can be helpful in these type of use cases.

Keywords: Direct Marketing, Customer Response, Analytics, Machine Learning, Predictive Modeling, Conversion Rate, Data Science, SVM, Support vector machine

How to Cite?: Ankit Bansal, "Direct Marketing Campaign Response Analysis using Logistic Regression, CART and Support Vector Machines", Volume 10 Issue 9, September 2021, International Journal of Science and Research (IJSR), Pages: 1808-1813, https://www.ijsr.net/getabstract.php?paperid=SR21917102249, DOI: https://dx.doi.org/10.21275/SR21917102249