{"id":28315523,"url":"https://github.com/mandeep04sharma/walmart-sales-performance-analysis","last_synced_at":"2026-01-25T20:52:15.146Z","repository":{"id":287861017,"uuid":"966042332","full_name":"Mandeep04Sharma/Walmart-Sales-Performance-Analysis","owner":"Mandeep04Sharma","description":"This project analyzes historical transaction data from Walmart stores using advanced SQL queries to uncover insights related to sales performance, customer behavior, and operational efficiency. 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By leveraging SQL techniques, the project covers various aspects such as branch performance, product profitability, customer segmentation, and sales trends.\n\n# 🎥 Project Video Walkthrough\n📽️ [Video Explanation](https://drive.google.com/drive/folders/1jDsGiRVDziNf6UPvdgEeIL-I_dE9Jv_R)\n\n## Key Features:\n- **Branch Performance**: Identifying the top-performing Walmart branch by calculating monthly sales growth.\n- **Profitability Analysis**: Analyzing the most profitable product lines for each branch based on gross income and cost of goods sold.\n- **Customer Segmentation**: Classifying customers into High, Medium, and Low spenders based on their average spending.\n- **Anomaly Detection**: Identifying abnormal sales transactions based on average sales for the product line.\n- **Sales Trends**: Analyzing sales by day of the week, customer type, and payment method preferences.\n  \n## Tasks Completed:\n- Task 1: Identified the top-performing branch based on sales growth.\n- Task 2: Determined the most profitable product line for each branch.\n- Task 3: Segment customers by spending behavior.\n- Task 4: Detected anomalies in sales transactions.\n- Task 5: Analyzed the most popular payment methods by city.\n- Task 6: Analyzed monthly sales distribution by gender.\n- Task 7: Identified the best product line by customer type.\n- Task 8: Identified repeat customers within a specific time frame.\n- Task 9: Found top 5 customers by sales volume.\n- Task 10: Analyzed sales trends by day of the week.\n\n## **Technologies Used**:\n- MySQL\n- Advanced SQL queries (e.g., JOINs, GROUP BY, window functions, subqueries)\n\n## 📧 Contact\n\nFeel free to connect:\n\n- LinkedIn: https://www.linkedin.com/in/mandeep-sharma04/\n- Email: Mandeep04sharma@gmale.com\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmandeep04sharma%2Fwalmart-sales-performance-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmandeep04sharma%2Fwalmart-sales-performance-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmandeep04sharma%2Fwalmart-sales-performance-analysis/lists"}