Technologies Used: R, Python
• Identified 4500 potential churn customers by developing ML models using Logistic Regression, Decision Tree and mitigated 36% by offering them discounts
• Initiated a new payment method to solve delivery problems that satisfied customers and increased unit sales to 6.5%
• Revamped coupon mailing strategy for 3 customer segments by clustering using K-means and identifying the most engaging coupons leading to a 12% estimated increase in headcount
• Built machine learning pipelines using python, optimized XGBoost model by adding new features to improve precision rate to 76% for the likelihood of purchase by analyzing consumer behavior
