Market Segmentation using Clustering

Overview

This project focuses on customer segmentation using machine learning clustering techniques. The aim is to help businesses segment their customers based on shared characteristics for offering personalized services like savings plans, loans, and wealth management.

Objective

• Apply clustering algorithms to segment customers.
• Provide insights into customer behavior and needs to businesses.
• Use the segmentation model for targeted marketing strategies.

Technologies Used

• Python: Programming language
• Pandas & NumPy: Data manipulation and processing
• Scikit-learn: Machine learning algorithms for clustering
• Matplotlib & Seaborn: Data visualization libraries for graphs

Files

• Market_Segmentation.ipynb: Jupyter Notebook with the code for customer segmentation using clustering.
• customer_data.csv: The dataset used for segmentation. (if applicable)

How to Run

1. Clone the repository:

   git clone https://github.com/yourusername/your-repository-name.git

2. Install dependencies:

   pip install -r requirements.txt

3. Open the Jupyter Notebook:

   jupyter notebook

4. Run the Market_Segmentation.ipynb notebook to see the clustering process in action.

Outcome

The project segments customers into different groups based on their characteristics. This segmentation can help businesses target customers more effectively with personalized services.

Contact

For any questions or suggestions, feel free to contact me at theadeelahmed@hotmail.com.