Customer Sales Intelligence and Profitability AnalysisCustomer Sales Intelligence and Profitability Analysis
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Customer Sales Intelligence & Profitability Analysis
Project Description
I analyzed 10,000 orders and 1,498 customers to identify the customers, products, and segments driving sales and profitability.
Key Insights:
📈 High-value customers contributed approximately 59.6% of total sales
⚠️ 267 At-Risk customers had previously generated approximately 129.82M in sales, highlighting a strong win-back opportunity
💰 High sales did not always mean high profitability
📊 Compared product-level sales, profit, and profit margins to identify more profitable opportunities
🎯 Used customer segmentation and RFM analysis to identify valuable and at-risk customers
What I delivered:
• Data cleaning and exploratory analysis using Python
• Data storage and analysis using PostgreSQL & SQL
• Customer segmentation and profitability analysis
• A 4-page interactive Power BI dashboard
• Business recommendations based on customer and product performance
Tools: Python • PostgreSQL • SQL • Power BI • Excel
Workflow: Raw Data → Python → PostgreSQL → SQL Analysis → Customer Segmentation → Power BI → Business Insights
Outcome: The analysis transformed raw sales data into actionable insights for customer retention, win-back campaigns, product profitability, and revenue growth.
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