This analysis and post were completed with the following situation in mind:
You’re a general manager for a cellular provider. Your company sells cell phone plan subscriptions to customers in the United States. Looking through a report on your company’s performance last month, you immediately notice something troubling: you’ve signed thousands of new customers, but you’re falling short of revenue targets.
You know that revenue is a composition of new business, upsell, and churn. A lack of new business doesn't appear to be the issue and upsell is of less immediate concern. You decide to investigate customer churn, the loss of customers using your product or subscribing to your services.
A detailed description of the overall process and results of the analysis can be found in this post.
├── Data # Data folder
├── Figures # Folder containing data visualizations
├── Other_notebooks # Folder containing initial notebook
├── Customer_churn_analysis_Final.ipynb # Main Jupyter notebook, contains analysis
├── README.md
└── requirements.txt # Packages required to run code in notebook
This project uses:
- Anaconda, a package and environment management tool
- Python 3.7, along with the packages/libraries found in the requirements.txt file
If you would like to follow the analysis locally and have the above tools:
- Fork and clone this repository
- In your terminal, navigate to the directory where you cloned this repository and run the following:
pip install -r requirements.txt
You should then be able to run the exploration and analysis in the provided Customer_churn_analysis_Final Jupyter Notebook.