A Business Intelligence and Data Analytics solution for analyzing restaurant order channels, customer behavior, profitability, and market share across multiple delivery platforms.
The Order Channel Performance & Market Share Analytics project provides a comprehensive analysis of restaurant ordering channels to identify performance trends, customer preferences, profitability, and regional market dynamics.
The project helps decision-makers understand how different ordering platforms contribute to sales, revenue, and customer engagement through interactive visualizations and business intelligence dashboards.
Restaurants operate across multiple ordering channels such as:
- In-Store
- Uber Eats
- DoorDash
- Self-Delivery
However, businesses often struggle to identify:
- Which channel generates the highest revenue
- Most profitable ordering platform
- Customer preferences by cuisine
- Regional market share
- Performance differences between restaurant segments
This project transforms raw operational data into actionable business insights.
- Analyze order channel performance
- Measure market share across delivery platforms
- Compare profitability between ordering channels
- Analyze customer purchasing behavior
- Evaluate cuisine-wise performance
- Identify regional ordering trends
- Develop an interactive analytics dashboard
Raw Dataset
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Data Cleaning
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Feature Engineering
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Exploratory Data Analysis
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Channel Performance Analysis
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Cuisine & Segment Analysis
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Market Share Analysis
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Business KPI Evaluation
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Interactive Streamlit Dashboard
- Data Cleaning & Preprocessing
- Feature Engineering
- Exploratory Data Analysis
- Channel-wise Revenue Analysis
- Net Profit Analysis
- Cuisine Performance Evaluation
- Restaurant Segment Analysis
- Regional Market Share Analysis
- Business KPI Dashboard
- Interactive Streamlit Web Application
- 📊 Executive Dashboard
- 🍽 Channel Performance Analysis
- 📈 Revenue & Profit Dashboard
- 🌍 Regional Market Share Analysis
- 🍕 Cuisine Performance Dashboard
- 🏪 Restaurant Segment Analysis
- 📋 KPI Summary
- 📥 Data Export
OrderChannelAnalytics/
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├── datasets/
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├── DataCleaning.ipynb
├── ExploratoryDataAnalysis.ipynb
├── ChannelAnalytics.ipynb
├── CuisineSegmentAnalysis.ipynb
├── app.py
├── style.css
├── requirements.txt
└── README.md
- Python
- Pandas
- NumPy
- Plotly
- Matplotlib
- Seaborn
- Streamlit
- VS Code
- Jupyter Notebook
- GitHub
- Total Orders
- Revenue
- Net Profit
- Channel Market Share
- Average Order Value
- Customer Distribution
- Cuisine Performance
- Restaurant Segment Performance
The dashboard enables stakeholders to:
- Identify the best-performing order channels
- Compare revenue and profitability
- Analyze customer ordering preferences
- Evaluate cuisine demand across regions
- Improve channel-specific business strategies
- Support data-driven operational decisions
Clone the repository
git clone https://github.com/your-username/Order-Channel-Performance-Market-Share-Analytics.gitInstall dependencies
pip install -r requirements.txtRun the application
streamlit run app.py(Add screenshots after deployment.)
Suggested screenshots:
- Executive Dashboard
- Channel Performance Dashboard
- Cuisine Analysis
- Regional Market Share
- KPI Dashboard
- Demand Forecasting
- Customer Segmentation using Machine Learning
- Real-Time Dashboard Integration
- Predictive Sales Analytics
- Geographic Heatmaps
- Time-Series Trend Analysis
Rihu Mishra
AI & Machine Learning Student
This project was developed for educational, academic, and portfolio purposes.