Predicting-Ad-Clicks-Classification-by-Using-Machine-Learning

This skill implements a logistic regression classification model to predict which users are likely to click on ads, addressing inefficient broad-based ad strategies. It analyzes customer behavior patterns including age, income, internet usage, and site engagement time to identify the target demographic most likely to convert. The model identifies key factors influencing ad click likelihood, enabling personalized content delivery and income-level targeting. By replacing a 50% baseline click rate strategy with targeted predictions, this approach significantly reduces wasted ad spend and improves campaign ROI. Marketing teams use these insights to implement age-targeted and income-based ad strategies.