🛍️ Sales Performance Analysis of Walmart Stores Using Advanced MySQL Techniques

This project is part of my Internshala SQL Training capstone. It demonstrates advanced SQL techniques by analyzing Walmart sales data across multiple dimensions like profitability, customer behavior, trends, and anomalies.

🔗 Project Video: Watch on Google Drive

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📌 Project Overview

We analyzed a Walmart sales dataset to gain insights using complex SQL queries. This project covered key aspects such as:

• Branch performance
• Profit optimization
• Customer segmentation
• Anomaly detection
• Payment preferences
• Sales trend analysis

All queries were written in MySQL using advanced features like:

• CTEs (WITH)
• Window functions (ROW_NUMBER, LAG)
• Conditional logic (CASE)
• Date formatting and manipulation
• Aggregate functions

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🧠 Key Business Questions Answered

✅ Task 1: Identifying the Top Branch by Sales Growth Rate

Determine which branch has shown the highest monthly average sales growth.

✅ Task 2: Finding the Most Profitable Product Line for Each Branch

Helps each branch focus on their most profitable category.

✅ Task 3: Customer Segmentation Based on Spending

Classifies customers into LOW, MEDIUM, and HIGH spenders.

✅ Task 4: Detecting Anomalies in Sales Transactions

Spots unusual sales using deviation from average product line sales.

✅ Task 5: Most Popular Payment Method by City

Identifies preferred payment methods (e.g., Card, Cash, E-wallet) per city.

✅ Task 6: Monthly Sales Distribution by Gender

Tracks how sales differ by gender over months.

✅ Task 7: Best Product Line by Customer Type

Shows product preference based on customer category (e.g., member vs. normal).

✅ Task 8: Identifying Repeat Customers

Analyzes repeat purchases within a 30-day window.

✅ Task 9: Top 5 Customers by Sales Volume

Ranks the highest-paying customers.

✅ Task 10: Analyzing Sales Trends by Day of the Week

Identifies peak and low-performing days.

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📊 Insights & Recommendations

• 📌 Boost high-profit product lines per branch with targeted campaigns.
• 🎯 Personalize loyalty programs for high and medium spenders.
• 🧍‍♂️ Re-engage male customers in months like February (low activity).
• 🛍️ Plan staff & stock around high sales days like Saturday and Tuesday.
• 💸 Improve low-traffic days (like Monday) with special offers.

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📁 Files Included

File	Description
SQL_PROJECT_PRESENTATION.pptx	PowerPoint presentation of the project
queries/	Folder containing .sql files for all tasks
visuals/	(Optional) Screenshots or visual representations of output
data/	(Optional) Sample dataset or dummy version (if shareable)

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🧰 Tools Used

• SQL: MySQL Workbench
• Visualization: PowerPoint, Excel (for graphs)
• Platform: Internshala Training SQL Capstone Project

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📬 Contact

If you have any questions or feedback, feel free to reach out:

• 📧 thirumalanaidu.ds2026@gmail.com
• 8074244660

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📌 Note

This project is purely educational and not affiliated with Walmart Inc.