📊 Marketing Campaign Analysis Dashboard

🚀 Overview

This is an interactive Streamlit dashboard for analyzing marketing campaign data using Plotly visualizations. The dashboard provides insights into customer demographics, spending habits, and campaign effectiveness.

🎯 Features

• Key Metrics Display: Quick insights into total customers, average income, and recency.
• Interactive Filtering: Filter data based on education level for customized analysis.
• Visualizations:
  • Distribution plots for income, recency, purchases, etc.
  • Scatter plots for identifying trends and relationships.
  • Bar charts for customer spending insights.
• Summary Statistics: View descriptive statistics for numerical columns.

🛠️ Setup & Installation

1. Clone the Repository

   git clone https://github.com/jojocoder28/marketing_campaign_analysis.git
   cd marketing_campaign_analysis

2. Install Dependencies

   pip install -r requirements.txt

3. Run the Streamlit App

   streamlit run app.py

📂 Project Structure

📁 marketing-dashboard
│-- app.py                   # Main entry point for the multipage app
│-- Response_Prediction.py   # Customer response prediction logic (modularized)
│-- dashboard.py             # Dashboard for marketing campaign analysis (modularized)
│-- marketing_campaign_data.csv # Sample dataset
│-- requirements.txt         # Required Python packages
│-- README.md                # Project documentation

📊 Dataset Information

The dataset used contains customer information, including:

• Demographics: Age, Education, Marital Status, Income
• Purchase Behavior: Spending on different product categories
• Campaign Response: Whether a customer accepted past campaigns

🏆 Contributions

Feel free to contribute to this project by submitting issues, suggesting improvements, or creating pull requests.

📜 License

This project is licensed under the MIT License.

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🚀 Happy Analyzing! 🎯