Predicting Ad Click-Through Rates in Digital Marketing with Support Vector Machines - Thosporn Sangsawang (Bright Publisher, 2024)
This study investigates the effectiveness of Support Vector Machines (SVM) in predicting click-through rates (CTR) in digital marketing campaigns. Utilizing a dataset comprising user demographic and behavioral data, the research aims to develop a predictive model to forecast ad clicks accurately. The primary objectives include conducting exploratory data analysis (EDA), preprocessing data, training the SVM model, and evaluating its performance using standard metrics. The dataset includes features such as Daily Time Spent on Site, Age, Area Income, Daily Internet Usage, and Gender. Key findings from the EDA reveal that