Amazon Sales Analytics Dashboard

Overview

This project analyzes Amazon sales data in Power BI to understand revenue trends, regional performance, product category contribution, and profitability patterns. The dashboard is designed to help stakeholders identify business opportunities, monitor key metrics, and spot areas that need attention.

Business Problem

Amazon generates sales across multiple product categories, customer segments, regions, and sales channels. Management needs a clear view of sales performance and profitability to identify growth opportunities, improve business decisions, and address low-margin or loss-making areas.

Project Objective

• Analyze sales performance over time.
• Compare sales and profit across categories, regions, and states.
• Identify seasonal trends and regional performance gaps.
• Highlight profit drivers and loss-making product lines.
• Provide actionable insights for better decision-making.

Dataset Overview

The dataset includes sales transactions with dimensions such as:

• Order date
• Category and sub-category
• Region and state
• Segment
• Sales channel
• Profit, discount, quantity, and shipment details

Dashboard Features

• KPI cards for Total Sales, Total Quantity, Total Profit, and Total Shipments
• Sales by Category
• Sales by Year and Month
• Sales and Profit by Region
• Average Discount Percentage by Sub-Category
• Sales and Profit by Category and Segment
• Profit by State using map visualization
• Category-level profit analysis

Key Insights

• Sales increased steadily from 2014 to 2017.
• The fourth quarter generated the highest sales, showing strong seasonality.
• Technology contributed the highest sales among all categories.
• The West region generated the strongest sales and profit performance.
• The Central region showed lower revenue efficiency compared with sales volume.
• Furniture generated high sales but weaker profit margins.
• Tables emerged as a loss-making sub-category with negative profit.

Business Recommendations

• Increase inventory and marketing activity before Q4 demand peaks.
• Focus on high-performing Technology products.
• Investigate low profitability in the Central region.
• Review pricing and discount strategies in Furniture.
• Reduce or rework loss-making product lines such as Tables.

Tools Used

• Power BI
• Power Query
• DAX
• Excel

Resume Summary

Built an interactive Power BI dashboard analyzing Amazon sales data across categories, regions, and time periods. Developed KPI cards, trend analysis, regional profitability views, and category-level insights to identify growth opportunities and loss-making areas.

Repository Structure

Amazon-Sales-Analytics/
├── README.md
├── Amazon Sales Dashboard.pbix
├── screenshots/
└── dataset/

Screenshot

How to Use

1. Open the .pbix file in Power BI Desktop.
2. Refresh the data if required.
3. Use the slicers and visuals to explore trends by category, region, and time.