Customer Segmentation: RFM ANALYSIS USING PYTHON

• Conducted Recency, Frequency, Monetary analysis to segment customer data | • Improved customer targeting by 20%

MOVIE CONTENT-BASED RECOMMENDATION SYSTEM

• Implemented content-based recommendation filtering using Python and scikit-learn | • Achieved a user satisfaction rate of 90%

NETFLIX SUBSCRIPTION FORECASTING

• Utilized SARIMA for time-series analysis to forecast subscription rates | • Achieved 95% accuracy in predicting Q3 subscription numbers for 2023.

ETL PIPELINES USING AWS

• Designed and deployed ETL pipelines using Airflow, AWS S3, and Redshift | • Reduced data processing time by 30%

A/B TESTING USING PYTHON

• Conducted A/B tests to compare the effectiveness of two marketing campaigns. | • Identified the more effective campaign, leading to a 15% increase in customer engagement.

HR ANALYSIS USING POWERBI

• Created interactive dashboards to visualize HR metrics | • Improved HR decision-making by providing actionable insights

Customer Churn Prediction Model Using Python

This project demonstrates how to build a machine-learning model to predict customer churn using a telecommunications company dataset.

Cohort Analysis Using Python

This project aims to understand Customer Behavior and Retention over Time.