https://github.com/md-emon-hasan/ml-project-customer-segmentation
📈 Implementing clustering algorithms, it provides valuable insights that can targeted marketing strategies, improve customer relationship management.
https://github.com/md-emon-hasan/ml-project-customer-segmentation
analytics churn-prediction custom-elements customer-segmentation kmeans-clustering marketing-analytics rfm rfm-analysis
Last synced: 7 months ago
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📈 Implementing clustering algorithms, it provides valuable insights that can targeted marketing strategies, improve customer relationship management.
- Host: GitHub
- URL: https://github.com/md-emon-hasan/ml-project-customer-segmentation
- Owner: Md-Emon-Hasan
- License: mit
- Created: 2024-11-04T17:26:50.000Z (11 months ago)
- Default Branch: master
- Last Pushed: 2024-11-04T17:47:03.000Z (11 months ago)
- Last Synced: 2025-01-13T08:46:20.039Z (9 months ago)
- Topics: analytics, churn-prediction, custom-elements, customer-segmentation, kmeans-clustering, marketing-analytics, rfm, rfm-analysis
- Language: Jupyter Notebook
- Homepage:
- Size: 31.5 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Customer Segmentation Project
## Project Description
This project aims to utilize machine learning for **customer segmentation** by analyzing purchasing behavior. Through clustering techniques, specifically K-means, businesses can identify distinct customer groups, allowing for more targeted marketing strategies and enhanced customer relationship management.
## Key Features
- **Data Cleaning**: Efficiently preprocess raw data to prepare it for analysis.
- **Exploratory Data Analysis**: Visualize customer data to uncover patterns and insights.
- **K-Means Clustering**: Apply clustering algorithms to segment customers based on their behavior.
- **Data Visualization**: Generate insightful visualizations that illustrate customer segments.
## Technologies Used
- **Programming Language**: Python
- **Libraries**:
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Scikit-learn
- **Environment**: Jupyter Notebook
## Getting Started
To run this project locally, follow these steps:
1. **Clone the Repository**:
```bash
git clone https://github.com/Md-Emon-Hasan/ML-Project-Customer-Segmentation.git
```
2. **Navigate to the Project Directory**:
```bash
cd ML-Project-Customer-Segmentation
```
3. **Install Dependencies**:
Make sure you have Python installed, then run:
```bash
pip install -r requirements.txt
```
4. **Run the Jupyter Notebook**:
Start Jupyter Notebook with:
```bash
jupyter notebook
```
Open the file `Customer_Segmentation.ipynb` to view and execute the analysis.
## Dataset
The dataset used in this project is located in the `data/` folder. It contains various customer attributes that serve as the basis for segmentation analysis. Ensure to inspect the dataset and understand its structure before proceeding.
## Results and Insights
This project produces several key visualizations that help illustrate the differences between customer segments. Insights gained from these visualizations can inform marketing strategies and enhance customer engagement efforts.
## How to Contribute
We welcome contributions! If you have ideas for improvements, please fork the repository and submit a pull request, or open an issue to discuss your suggestions.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more information.
## Contact
For any inquiries or feedback, feel free to reach out:
- **Md Emon Hasan**
- **Email:** [iconicemon01@gmail.com](mailto:iconicemon01@gmail.com)
- **WhatsApp:** [+8801834363533](https://wa.me/8801834363533)
- **GitHub:** [Md-Emon-Hasan](https://github.com/Md-Emon-Hasan)
- **LinkedIn:** [Md Emon Hasan](https://www.linkedin.com/in/md-emon-hasan)
- **Facebook:** [Md Emon Hasan](https://www.facebook.com/mdemon.hasan2001/)