main_readme.md

🏪 GlobalRetail Inc. - Sales Analytics Capstone Project

Comprehensive analysis of 536K+ sales transactions generating $60.12M in revenue

📊 Project Overview

This capstone project provides deep insights into GlobalRetail Inc.'s sales performance through comprehensive data analysis of 536,350 transactions across multiple countries and product categories. The analysis reveals critical business insights including customer behavior patterns, product performance metrics, and geographic market dynamics.

🎯 Key Achievements

• $60.12M Net Revenue Analysis
• 97.85% Customer Retention Rate Discovery
• 13 Strategic Business Questions Answered
• Interactive Power BI Dashboards Created
• 10 Data-Driven Recommendations Delivered

🔍 Business Questions Analyzed

1. ✅ Total sales revenue and quantity analysis
2. ✅ Top 10 revenue-generating products identification
3. ✅ Product return rate analysis
4. ✅ Top customer segmentation by spend
5. ✅ Average revenue per customer calculation
6. ✅ Customer retention pattern analysis
7. ✅ Sales distribution by geographic market
8. ✅ Country-wise transaction value analysis
9. ✅ Geographic return rate comparison
10. ✅ Premium product performance evaluation
11. ✅ Suspicious transaction pattern detection
12. ✅ Time-series sales trend analysis
13. ✅ Seasonal performance identification

📈 Key Findings Summary

💰 Financial Performance

• Net Revenue: $60.12M from 5.3M units sold
• Return Rate: 4.8% ($2.66M in returns)
• Avg Revenue per Customer: $12.69K

🌍 Geographic Insights

• UK Market Dominance: 82.9% of total sales ($49.84M)
• Highest ATV: Netherlands ($22.14K per transaction)
• Expansion Opportunities: Netherlands, Australia, Germany

👥 Customer Intelligence

• Total Customers: 4,739 unique customers
• Retention Rate: 97.85% (4,637 repeat buyers)
• Top Customer: $2.11M in purchases

📦 Product Performance

• Top Product: Popcorn Holder ($583K revenue)
• High Return Product: Paper Craft Little Birdie (80,995 units)
• Premium Opportunity: Vintage Kitchen Cabinets ($660+ unit price)

🛠️ Technology Stack

• Database Management: PostgreSQL with PgAdmin 4
• Data Preparation & Analysis: PostgreSQL (Advanced SQL)
• Data Visualization: Microsoft Power BI
• Data Processing: PostgreSQL ETL processes
• Documentation: Markdown, PDF reports

📁 Repository Structure

├── 🗄️ postgresql/           # PostgreSQL schemas, queries, and ETL scripts
├── 📊 dashboards/          # Power BI files and screenshots
├── 📈 reports/             # Comprehensive analysis reports
├── 🗃️ data/               # Dataset files (anonymized)
├── 📸 assets/             # Images, logos, and visual assets
└── 📝 scripts/            # Data processing and analysis scripts

🚀 How to Explore This Project

1. View the Dashboards

Navigate to /dashboards to see interactive Power BI visualizations

2. Read the Full Report

Check /reports/insights_report.pdf for comprehensive business insights

3. Explore the PostgreSQL Analysis

Browse /postgresql for all database schemas, analytical queries, and ETL scripts

4. Understand the Methodology

Review methodology documentation in individual folder README files

📊 Dashboard Previews

Sales & Product Performance Dashboard

Customer Analytics Dashboard

Geographic Insights Dashboard

🎯 Strategic Recommendations

1. Geographic Diversification: Reduce UK dependency, expand to high-ATV markets
2. Premium Product Enhancement: Capitalize on luxury item opportunities
3. Return Rate Optimization: Address quality issues in high-return products
4. Customer Retention Programs: Leverage exceptional retention rate further
5. Seasonal Inventory Management: Optimize for peak performance months

📊 Business Impact

This analysis provides actionable insights that could potentially:

• Increase Revenue: 15-20% through market expansion
• Reduce Returns: 2% improvement in return rates
• Enhance Customer Value: Targeted premium product marketing
• Optimize Operations: Better inventory management and seasonal planning

🔧 Setup Instructions

Prerequisites

• PostgreSQL (version 12+)
• PgAdmin 4 for database management
• Power BI Desktop (latest version)
• Basic knowledge of PostgreSQL and Power BI

Running the Analysis

1. Clone this repository
2. Set up PostgreSQL database using schema files in /postgresql/schema
3. Execute ETL scripts from /postgresql/etl_scripts
4. Run analytical queries from /postgresql/queries
5. Open Power BI files from /dashboards
6. Review methodology in respective README files

👨‍💻 About the Analyst

Stephen Kiri | WelUp Digital Academy
Data Analytics Capstone Project

Passionate about transforming raw data into actionable business insights through advanced analytics and compelling visualizations.

🤝 Connect & Collaborate

• LinkedIn: linkedin.com/in/stephen-kiri-9b8aa1136
• Email: stephen.kiri.analyst@gmail.com
• Portfolio: [Your Portfolio Website]

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This project demonstrates end-to-end data analysis capabilities including PostgreSQL database management, advanced SQL analytics, ETL processes, Power BI visualization design, and strategic business recommendation development.