Sales Data Analysis and Customer Segmentation Dashboard

Project Description

This project involves analyzing sales data to track key metrics such as total sales, monthly trends, and product performance. Additionally, it includes customer segmentation using k-means and hierarchical clustering to identify different customer segments based on their purchasing behavior. The data analysis and visualizations are displayed through a professional, attractive, and responsive Flask web application.

Table of Contents

• Project Description
• Features
• Installation
• Usage
• Data
• Results
• Contributing
• License

Features

• Sales Data Analysis
• Monthly Sales Trends Visualization
• Top Products by Sales Visualization
• Customer Segmentation using K-means Clustering
• Customer Segmentation using Hierarchical Clustering
• Professional and Responsive Web Dashboard

Installation

1. Clone the repository:

   git clone https://github.com/your-username/sales-data-analysis-dashboard.git
   cd sales-data-analysis-dashboard

2. Create and activate a virtual environment:

   python -m venv env
   source env/bin/activate  # On Windows use `env\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

Usage

1. Place your sales data CSV file in the data/ directory.
2. Run the Flask application:

   python app.py

3. Open your web browser and go to http://127.0.0.1:5000/ to view the dashboard.

Data

The sales data should be in CSV format with the following columns:

• Row ID
• Order ID
• Order Date
• Ship Date
• Ship Mode
• Customer ID
• Customer Name
• Segment
• Country
• City
• State
• Postal Code
• Region
• Product ID
• Category
• Sub-Category
• Product Name
• Sales

Results

Monthly Sales Trends

Top Products by Sales

Customer Segmentation (K-means Clustering)

Customer Segmentation (Hierarchical Clustering)

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any changes or improvements.

License

This project is licensed under the MIT License - see the LICENSE file for details.