This project analyzes Walmart sales data using SQL to uncover insights about sales patterns, top-selling products, and customer behaviour and operational efficiencies.
Goals of the analysis:
- Explore sales trends over time
- Identify top-performing products and stores
- Examine regional and category-based performance
- Generate actionable insights for business decisions
The project includes:
- 00_DataCleaning.sql – Prepares and cleans the Walmart sales dataset for analysis.
- 01_Query1.sql → 10_Query10.sql – Ten SQL queries analyzing:
- Total sales by store
- Top-selling products
- Sales trends over time
- Category and regional performance
- Weekday vs weekend sales patterns
- Male/Female performance.
- Walmart_Sales_Analysis.pptx – Summarizes key insights and visualizations from the analysis.
- Branch A is the top performer as per monthly sales growth rate .
- Food & Beverage is the most profitable product line in
branch B followed by Health & lifestyle in branch C and Health & beauty in Branch A. - Customers are segmented in High ,Medium , Low spenders. : High Spenders having maximum average spending .
- Repeat customers are a strong indicator of loyalty.
- The top 5 customers contribute disproportionately to total sales.
- Sales peak on Saturday and Tuesday showing higher weekend traffic. : Lowest sales on Monday consistent with retail patterns.
-
Replicate winning strategies from higher growth branches to other branches too .
-
Optimize inventory per branch demand.
-
Launch loyalty and re-engagement programs.
-
Partner with payment providers at a city level.
-
Design Gender specific campaigns.
-
Plan staffing and promotions according to the days pattern.
This analysis helps Walmart or business analysts understand sales performance, make data-driven decisions, and identify areas for improvement or growth.