E-commerce Sales & Customer Insights (Self-Initiated Project)

Type: Personal / Portfolio Project
Tools: SQL (PostgreSQL)
Data: Synthetic (AI-generated)

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📊 Project Overview

This project simulates an e-commerce sales database and demonstrates core SQL skills used in real-world analytics work.
It focuses on extracting insights about customer behavior, revenue trends, and segmentation using SQL queries.

All data is synthetic and created for educational and portfolio purposes only.

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💼 Business Questions Answered

• What are the monthly revenue trends by product category?
• Which cities generate the most revenue?
• Who are our most valuable customers (via RFM segmentation)?
• How many customers are repeat vs. one-time buyers?

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🛠️ SQL Scripts Included

Script	Description
monthly_revenue_by_category.sql	Aggregates monthly sales by product category
top_cities_by_revenue.sql	Identifies top 10 cities by total revenue
rfm_segmentation.sql	Segments customers using Recency, Frequency, and Monetary metrics
repeat_vs_onetime_customers.sql	Compares counts of one-time vs. repeat customers

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📂 How to Use

1. Load the CSV files (customers.csv, products.csv, orders.csv) into a PostgreSQL database.
2. Run each .sql script to generate insights.
3. Use the query outputs to build reports or dashboards.

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📌 Notes

• All data is synthetic, created with AI assistance.
• This is a self-initiated project created to meet portfolio requirements and showcase SQL proficiency.
• No real company or clients are associated with this project.

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📝 License

This project is licensed under the MIT License.