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SQL-business-performance-analysis

SQL-based business performance analysis project focused on sales, customer, and product KPIs using data analytics and business intelligence techniques.

Project Overview

This project analyzes business performance using SQL by focusing on three major business areas:

  • Sales Performance
  • Customer Behaviour
  • Product Performance

The analysis was performed to identify trends, evaluate KPIs, and generate actionable business insights.


Tools Used

  • SQL
  • PostgreSQL
  • Power BI
  • Excel

Project Structure

sql/
│
├── sales_kpis.sql
├── customer_kpis.sql
└── product_kpis.sql

Sales KPI Analysis

The sales analysis focused on evaluating revenue performance and business growth.

KPIs Calculated

  • Total Sales
  • Sales Growth %
  • Average Order Value (AOV)
  • Running Total Revenue
  • Monthly Sales Trends
  • Revenue Contribution %

Key Insights

  • Revenue showed steady growth over time.
  • Certain periods generated significantly higher sales.
  • A small number of categories contributed most revenue.

Customer KPI Analysis

The customer analysis focused on spending behaviour and customer value.

KPIs Calculated

  • Total Customers
  • Customer Lifespan
  • Customer Recency
  • Average Monthly Spend
  • Purchase Frequency
  • Customer Segmentation

Customer Segments

  • VIP Customers
  • Regular Customers
  • New Customers

Key Insights

  • VIP customers generated the highest revenue.
  • Repeat customers showed stronger purchasing behaviour.
  • Customer retention improved long-term sales performance.

Product KPI Analysis

The product analysis evaluated product performance and category contribution.

KPIs Calculated

  • Product Revenue
  • Total Quantity Sold
  • Product Performance Ranking
  • Revenue by Category
  • Average Product Cost

Product Segments

  • High-Performers
  • Mid-Range
  • Low-Performers

Key Insights

  • High-performing products generated most business revenue.
  • Some categories consistently outperformed others.
  • Product demand varied across time periods.

Visualizations

The SQL analysis was visualized using dashboards and charts including:

  • Revenue Trend Charts
  • Customer Segment Analysis
  • Product Performance Dashboards
  • Category Revenue Analysis
  • Running Revenue Trends

Conclusion

This project demonstrates how SQL can be used to analyze business performance, calculate KPIs, identify trends, and generate business insights for decision-making.

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SQL-based business performance analysis project focused on sales, customer, and product KPIs using data analytics and business intelligence techniques.

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