This project analyzes the business operations of Quadri Mobile Communication, a local mobile shop in Dildarnagar, to address key challenges in sales strategy, pricing, and inventory management. By leveraging data analysis and visualization techniques, the project provides actionable recommendations to improve profitability and customer satisfaction.

1. Optimize Product Range: Identify popular configurations and introduce high-demand models to meet customer preferences.
2. Enhance Pricing Strategy: Develop competitive pricing while maintaining profitability.
3. Improve Inventory Management: Reduce stock-outs and overstock, and streamline inventory planning.

• Sales Data: Historical sales records, including revenue, units sold, and pricing.
• Inventory Data: Stock levels, turnover rates, and restocking schedules.
• Expense Data: Fixed and variable costs, including rent, salaries, and utilities.

• Python: For data analysis and creating custom visualizations.
• Excel: For data cleaning and initial exploration.
• Matplotlib & Seaborn: For creating detailed charts and graphs.

1. Top 10 Selling Models by Revenue and Volume
2. Sales Volume and Revenue Distribution by Brand
3. Inventory Turnover Rates
4. Sales Trends by Month and Weekdays
5. Product Preferences (Price Range, Colors, RAM/ROM Configurations)

• Premium models drive revenue, while budget models dominate volume.
• High-demand products frequently face stock-outs, leading to missed sales opportunities.
• Seasonal trends (e.g., November peaks) highlight the importance of timely inventory planning.
• Customers prefer budget-friendly models with 4GB RAM/64GB ROM configurations and blue-colored devices.

1. Implement demand-driven inventory management to optimize stock levels.
2. Focus on budget segment models while maintaining a balanced product range.
3. Prepare for seasonal peaks with advanced stocking and festive promotions.
4. Adopt a Point of Sale (PoS) system to monitor sales, inventory, and finances efficiently.

data/                   # Raw and processed data files  
notebooks/              # Jupyter notebooks for data analysis  
visuals/                # Charts and graphs generated from the analysis  
reports/                # Final report and presentation   
README.md               # Project overview and details  

• Integrate real-time data using a PoS system.
• Expand analysis to include customer feedback and market trends.
• Automate inventory management recommendations.

• Mr. Azad Khan and the staff at Quadri Mobile Communication for sharing business data and insights.
• Tools and libraries: Python, Matplotlib, Seaborn, and Excel.