This project focuses on customer segmentation using a dataset from Kaggle. The goal is to segment customers into distinct groups based on their purchasing behaviors and demographic details, allowing for more targeted marketing strategies.
Customer segmentation is a crucial strategy for businesses to understand their customer base, improve customer satisfaction, and enhance marketing efforts. By grouping customers based on their similarities, businesses can tailor their strategies to meet the specific needs of each segment.
This project utilizes a dataset from Kaggle and employs various machine learning techniques to segment customers effectively.
The dataset used in this project can be found on Kaggle: Customer Segmentation Dataset. It contains information about customers' purchasing behavior and demographics.
To run this project locally, please ensure you have Python 3.x installed. Follow the steps below to set up the environment:
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Clone the repository: git clone https://github.com/yourusername/customer-segmentation.git cd customer-segmentation
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Create a virtual environment: python -m venv venv
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Activate the virtual environment: On Windows: venv\Scripts\activate On macOS/Linux: source venv/bin/activate
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Install the required packages
To run the project, use the following command: python main.py This will execute the segmentation algorithm and produce the output, including visualizations and segment details.
The segmentation results include visualizations of the customer segments, cluster analysis, and insights into each segment's characteristics.