Table of Contents
Telco Customer Churn focuses on the analysis of customer churn data from a telecom company to develop targeted customer retention strategies. This project leverages a dataset with comprehensive customer information, including services used, account details, and demographics.
- Churn: Identifies customers who left in the last month.
- Services: Details on subscribed services like phone, internet, and streaming.
- Account Information: Customer tenure, contracts, payment methods, and charges.
- Demographics: Information on gender, age range, partners, and dependents.
- Analyze customer churn patterns.
- Utilize predictive analytics for identifying at-risk customers.
- Formulate focused retention strategies.
The project is an exploration into customer behavior modeling to enhance retention efforts and mitigate churn-related challenges for service-oriented businesses.
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Clone the repository
git clone https://github.com/jpcadena/PrDS_2024__TelcoCustomerChurn.git
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Change the directory to root project
cd PrDS_2024__TelcoCustomerChurn -
Install Poetry package manager
pip install poetry
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Install the project's dependencies
poetry install
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Activate the environment
poetry shell
- Replace the real datasets in the data/raw directory as the ones uploaded are small samples with 5 rows.
- Execute with console
python main.py
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Distributed under the MIT License. See LICENSE for more information.
