quocduyenanhnguyen/Customer-Churn-Analytics-project

In this project, I visualized and built Random Forest model for gas and electricity datasets to investigate whether customer churn is affected by price sensitivity and what are the other factors that affect customer churn.

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Software I used:

Tableau : for visualizing data

RStudio : for building model

Description:

• In this project, I analyzed the gas and electricity datasets by visualizing the datasets with Tableau, building a Random Forest model in RStudio, and making my conclusion based on my analysis in order to investigate whether customer churn is driven by price sensitivity and what factors are more likely to affect customer churn.

• I visualized the two original datasets by joining the two tables with common fields and then visualized the data on Tableau, and then I cleaned the two datasets to include a few more features (energy and power off-peak price differences in December and preceding January) with a higher predictive power before building my model.

• The dataset is from the BCG Analytics virtual experience program on Forage, which you can find here: https://www.theforage.com/virtual-internships/prototype/Tcz8gTtprzAS4xSoK/GAMMA-Virtual-Experience-Program?ref=B9eCovg2z2SaHryXC, and my badge of completion for the program can be found here: https://www.theforage.com/badges/B9eCovg2z2SaHryXC/n5u6Sv5StZrmfB4QQ/Badge%20of%20completion%20for%20the%20Open-Access%20Data%20Science%20&%20Advanced%20Analytics%20Virtual%20Experience%20Program/Quoc%20Duyen%20Anh%20(Anna)?ref=B9eCovg2z2SaHryXC.