Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.

Unlock actionable insights and boost customer retention with this Power BI project. Analyze and visualize risk factors to proactively prevent churn. ➡️

The Customer Churn table contains information on all 7,043 customers from a Telecommunications company in California in Q2 2022. We need to predict whether the customer will churn, stay or join the company based on the parameters of the dataset.

Analysis and Prediction of the Customer Churn Using Machine Learning Models (Highest Accuracy) and Plotly Library

Customer Churn Analysis Report using powerbi

Marketing Analytics

Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.

Customer Churn Analysis with Neural Network

Telecom Customer segmentation and Churn Prediction

Build and evaluate logistic regression model using PySpark 3.0.1 library.

This project focuses on a fictitious software company, Churn Buster, that is pitching their tool to Telecom Inc., a fictitious wireless service company. Churn Buster has built a predictive model to reduce Telecom Inc.'s customer churn

My solution for DataCamp case study "Analyzing Customer Churn in Power BI".

Hello, this is my final project with my friend when I joined Fresh Graduate Academy Program at Binar Academy in 2023.

In this project, we embark on an exciting journey to explore and analyze customer churn within the Telecom network service using the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework.

This shows my complete Power BI dashboards with real world data provided by PWC Switzerland. This is a Forage virtual internship where I got to use, analyze and gain valuable insights using real world data

This project leverages Power BI to analyze customer churn patterns across segments, offering strategies to enhance retention.

This project involves helping a telecoms company better understand its customer churns.

Customer retention is a critical stage for customer relationship management (CRM), especially for established businesses after their initial exponential growth. Churn management or attrition management is important as when customers leave, there arenegative impacts on revenues. Churn analytics has been widely applied to proactive customer retent…

We utilize customer account data to visualize churn rate based on various factors. Additionally, we predict customer churn using a logistic regression model provided by scikit-learn.