A data-driven approach with explainable artificial intelligence for customer churn prediction in the telecommunications industry

Perform a comprehensive analysis of over 10,000 Android apps in the Google Play Store. Explore app categories, user reviews, and sentiments. Gain insights to drive growth and retention strategies.

This project implements a customer churn prediction model using Recency, Frequency, and Monetary (RFM) analysis. It classifies customers into "Churned" or "Retained" categories using a logistic regression model based on customer behavior. The model helps businesses identify at-risk customers and design targeted retention strategies.

Comprehensive customer acquisition systems covering modern lead generation, conversion optimization, and customer onboarding methodologies. Build sustainable customer acquisition processes.

A learning guide for engineers who want to retain more, stress less, and actually enjoy the process.

AI-Enhanced Customer Retention System (AIECRS) is an AI-based system designed to predict customer churn and suggest retention strategies.

Banking Churn Dashboard - Risk Segmentation & Retention KPIs using Excel, SQL & Power BI.