Amazon Sales Analytics Dashboard & Business Report

📌 Project Overview This project analyzes Amazon sales transactions over a two-month period to evaluate sales performance, customer behavior, and operational efficiency. The goal is to uncover revenue drivers, identify risks such as pending and cancelled orders, and provide actionable business recommendations supported by data. The project combines descriptive analytics, business insight generation, and dashboard storytelling to simulate a real-world e-commerce analytics case.

📅 Dataset Information Time Period: 2 February – 2 April 2025 Total Transactions: 250 Total Sales Value: $243,845 Total Units Sold: 714 Unique Customers: 10 Order Statuses: Completed, Pending, Cancelled Product Categories: Electronics, Home Appliances, Clothing, Footwear, Books

🎯 Business Questions Addressed How much revenue is actually realized vs. pending or cancelled? Which products and categories drive the highest sales and risk? Are sales concentrated in specific products or customers? What operational issues are impacting revenue completion? Where should inventory, logistics, and marketing efforts be prioritized?

🛠️ Tools & Technologies Data Analysis: Excel / SQL (data cleaning & aggregation) Visualization: Tableau (interactive dashboard) Reporting: Business analytics & statistical profiling

📊 Dashboard Overview The interactive dashboard provides: Key KPIs (Total Sales, Orders, Customers) Sales trends over time Sales breakdown by category and product Order status distribution (Completed / Pending / Cancelled) Geographic distribution of customers

📷 Dashboard Preview:

🔍 Key Insights Sales Performance Total Sales: $243,845 Completed Revenue: $88,530 (36.31%) Pending Sales: 37.03% Cancelled Sales: 26.67%

➡️ Nearly 64% of total revenue is not yet realized, representing significant revenue risk.

Product & Category Insights Top Products by Sales: Refrigerators ($78,000), Laptops ($58,400) Highest Revenue Risk: Refrigerators have the highest cancelled ($24,000) and pending ($31,200) sales Top Category: Electronics dominate sales, completed revenue, and quantities Lowest Performing Category: Books

Quantity Insights Highest Units Sold: Smartphones (106), Smartwatches (97) Lowest Units Sold: Washing Machines (45), T-Shirts (53)

Customer Insights Only 10 customers generated all 250 orders, indicating extreme customer concentration

Most frequent buyers: Emma Clark (32 orders) Jane Smith (30 orders)

Highest cancellations: Jane Smith (13) David Lee (11)

➡️ This creates revenue volatility and customer dependency risk.

⚠️ Key Risks Identified High volume of pending orders impacting cash flow High cancellation rates for bulky appliances Operational and logistics challenges for high-value items Heavy reliance on a small customer base

💡 Business Recommendations Improve Order Fulfillment: Reduce pending orders from 37% to below 20% by prioritizing high-demand electronics Optimize Inventory Planning: Increase stock for Smartphones, Laptops, Smartwatches, and Refrigerators Enhance Logistics: Partner with specialized delivery providers for large appliances Convert Pending Orders: Use automated reminders and transparent delivery timelines Reduce Customer Concentration: Introduce loyalty programs and acquire new customers Replicate Peak Sales Days: Leverage insights from early-February sales spikes

📈 Project Outcomes

This project demonstrates: End-to-end analytical thinking Business-driven insight generation Strong dashboard storytelling Practical, data-backed recommendations It simulates a real e-commerce analytics scenario commonly encountered in business analyst and data analyst roles.

👩‍💻 Author Noura Mersal 📍 Berlin, Germany