Exploratory Data Analysis

Repositorio del proyecto de predicción del problema Telco Customer Churn (kaggle)

Analyze IBM Telco Customer data to offer valuable insights for data-driven decision-making on customer retention to reduce churn

Neste projeto será realizado o processo de EDA (Exploratory Data Analysis) com foco na análise de Churn a partir do datas ser Bank Customer Churn Dataset, que pode ser encontrado no Kaggle e disponibilizado por Gaurav Topre.

Developed a desktop application, that uses ML algorithms to accurately predict customer churn based on customer details. The application helps to identify customers at risk of churning using regression models.

This project develops a machine learning model to predict customer churn for a California-based telecom company using data from 7043 customers. Our goal is to enhance customer retention strategies through detailed data analysis and feature engineering.

This project aims to conduct an analysis of costumers behavior and perception of the brand, by implementing different marketing analytics techniques and methods: RFM (recency, frequency, monetary) model, churn classification, MBA (market basket analysis) and sentiment analysis.

Churn score analysis predicts customer attrition likelihood by analyzing historical data, enabling proactive retention strategies. Machine learning algorithms are often utilized to develop precise churn prediction models, aiding in customer retention efforts.

Focused customer retention programs

Utilizing machine learning tools to forecast customer churn. Explore visualizations highlighting unique profiles of churning and non churn customers, providing valuable insights for retention strategies.

visualisation of churn data of a bank

✨ The current project is a basic approach of data analysis and machine learning modeling to get business insights and propose strategies of customer segmentation and churn prediction to mitigate the high churn rate.

Tree methods for customer churn prediction. Creating a model to predict whether or not a customer will Churn .

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

using Power BI and python libraries

A data analysis project with customers' data of a telecom company.

This Repository Contains Microsoft Power BI Projects.

Customer churn rate analysis within a telecom service provider

The credit churn data analysis aims to investigate the factors that contribute to customer attrition in a credit card company. The dataset used in this analysis contains information on customer demographics, credit card usage, and other relevant variables.