Identifying factors that resulted in Customer Churn
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Updated
Sep 21, 2020 - Jupyter Notebook
Identifying factors that resulted in Customer Churn
ChurnRadar: Unveiling Customer Churn Patterns with Predictive Insights
Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.
Churn Analyzer: Analyze and understand user churn rate in your PostgreSQL database effortlessly.
Worked on three use cases- Churn data analysis, Movie recommendation engine and Intrusion detection system.
Repositório destinado a documentar o desafio de Data Science da Alura #alurachallengedatascience1
This is task 2 of 3 from the Power BI PwC Switzerland Virtual Internship organized in partnership with Forage
News Publishing Company Project
Redução da taxa de evasão de clientes (Churn Rate)
Customer Churn Analysis using R & RStudio
NGO Fund Raising Attrition Churn Modelling
Customer churn is a common analysis conducted by businesses since the cost of client retention is lower than the cost of acquiring new clients.
Importance of churn Analysis and some concept upon it
Predicting user churn for a mobile health app called Diabesties. Capstone project for Galvanize Phoenix Data Science Immersive, October 2017.
Fun fact: It is more valuable to hold on to an existing customer than to acquire new ones. Source: Trust me
Data Mining for Telco Customer Data Using SAS Miner
Customer Churn Analytics with R of a telecommunications company.
Churn rate visualizations in Python
Develop an overview dashboard for managers utilizing a telecom industry user churn dataset to present insights on the current churn situation.
Add a description, image, and links to the churn-analytics topic page so that developers can more easily learn about it.
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