Customer Behavior Prediction

Overview

This project builds an end-to-end machine learning pipeline to predict user behavior based on browsing activity and engagement patterns.

Problem Statement

Can user purchase intent be predicted from website browsing behavior?

This project simulates an e-commerce customer analytics scenario where browsing behavior is used to predict potential purchase intent.

Dataset Preview

User Activity Logs

User Profiles

Training Labels

Feature Engineering

Raw browsing logs were transformed into behavioral features including:

• Total session duration
• Average session duration
• Visit frequency
• Product-specific page visits
• Engagement metrics
• Log-transformed activity

Machine Learning Pipeline

Raw Logs → Feature Engineering → Standardization → Logistic Regression → Prediction

Tech Stack

• Python
• Pandas
• NumPy
• Scikit-learn

Next Steps

• Analyze which behavioral features contribute most to prediction
• Improve model interpretability for business decision-making
• Test the model on unseen customer behavior data