🧠 Customer Segmentation with K-Means Clustering

This platform leverages K-Means Clustering to segment customers based on their characteristics and behaviors. These insights enable businesses to understand different customer groups and build data-driven, targeted marketing strategies.

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🚀 Features

• Data Upload: Import your own customer data (CSV) or use sample data
• Feature Selection: Choose features like Annual Income and Spending Score
• Interactive Clustering: Segment customers using K-Means clustering
• Data Visualization: Explore clusters with interactive Plotly visualizations
• AI-Generated Insights: Get actionable marketing suggestions using Gemini AI
• Download Results: Export segmented data for further use

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🔍 Methodology

1. Data Preparation
   Upload your own dataset or use a built-in sample dataset.

2. Feature Selection
   Select two features (e.g., Annual Income, Spending Score) for clustering.

3. K-Means Clustering
   Segment your customers into groups based on feature similarity.

4. Visualization
   Interactive charts help you visually understand your customer segments.

5. AI Analysis
   Get automated marketing insights for each segment using Google's Gemini AI.

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🧑‍💻 How to Use

1. Upload Data
   Upload a CSV file with customer data or generate a sample dataset.

2. Configure Settings
   Select two features for clustering and adjust the number of clusters.

3. Explore Results
   Analyze clusters using visual tools and summary statistics.

4. Generate Insights
   Click to generate AI-powered marketing recommendations.

5. Download Results
   Export your segmented dataset as a CSV.

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📊 Interpreting Results

• Elbow Method: Suggests the optimal number of clusters.
• Cluster Plot: Shows customer groupings in 2D feature space.
• Cluster Statistics: Summary metrics for each segment.
• Comparison Tools: Compare characteristics between segments.

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💼 Business Applications

• 🎯 Targeted Marketing: Create personalized campaigns for each segment.
• 🧪 Product Development: Design offerings tailored to group needs.
• 💸 Pricing Strategy: Adjust pricing strategies by segment.
• 🤝 Customer Retention: Identify and retain at-risk customers.
• 📈 Resource Allocation: Focus on high-value segments.

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⚙️ Tech Stack

• Python – Core programming language
• Streamlit – Web app framework
• Scikit-learn – Machine learning and clustering
• Plotly – Interactive data visualizations
• Google's Gemini AI – AI-generated business insights

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📦 Installation

To run locally:

pip install -r requirements.txt
streamlit run app.py