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Data analysis project on Nike sales data to uncover business trends, profitability drivers, and strategic insights.

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Ashok-1103/Nike-Sales-Data-Analysis

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👟 Nike Sales Data Analysis

📌 Project Overview

This project analyzes Nike sales data to uncover key business trends, profitability drivers, and actionable insights across product categories, regions, customer segments, and sales channels.

The focus is on transforming messy, real-world sales data into a clean, reliable dataset and generating insights that support strategic decision-making.


🎯 Objective

  • Analyze 2,500 Nike sales records
  • Identify revenue and profit trends
  • Evaluate product, region, and channel performance
  • Provide actionable business recommendations

🔄 Analysis Workflow

  1. Data Loading & Quality Assessment
  2. Data Cleaning & Validation
  3. Exploratory Data Analysis (EDA)
  4. Data Visualization
  5. Insight Generation & Business Recommendations

🧹 Data Quality Challenges

Initial dataset issues:

  • Missing Order Dates: 24.6%
  • Missing Units Sold: 49.4%
  • Missing MRP: 50.2%
  • Negative Units Sold
  • Discounts greater than 100%

➡️ Highlighted the importance of data cleaning before analysis.


🛠️ Data Cleaning Steps

  • Filled missing numerical values
  • Converted negative units sold to positive
  • Capped discounts at 100%
  • Standardized region names
  • Unified multiple date formats
  • Removed invalid records

✅ Final clean dataset: 1,884 transactions


📊 Key Business Metrics

  • Total Revenue: ₹546,786.16
  • Total Profit: ₹2,563,539.17
  • Total Units Sold: 1,765
  • Average Order Value: ₹290.23
  • Date Range: July 2023 – July 2025

📈 Key Insights

🧑‍🤝‍🧑 Sales by Gender Category

  • Men's category generates the highest revenue
  • Kids category delivers the highest profit
  • Indicates better margins in Kids’ products

🏷️ Product Line Performance

  • Top Revenue Generators: Basketball, Training, Soccer
  • Lifestyle is the most profitable despite lower revenue → high efficiency

🌍 Regional Analysis

  • Top Revenue Region: Kolkata
  • Top Profit Region: Bangalore
  • Bangalore shows high transaction volume but lower AOV

🛒 Channel Performance

  • Online generates more revenue
  • Retail is slightly more profitable
  • Transaction count is nearly identical

💸 Discount & Profitability

  • Most profitable discount range: 40–50%
  • Men’s Running shows negative profit margin (red flag 🚩)

📅 Seasonal Trends

  • Revenue peaks in Q4 (Nov–Dec)
  • Post-holiday slump in January
  • Summer lull in July

🧠 Business Recommendations

  • Optimize discount strategy for profitability
  • Investigate losses in Men’s Running category
  • Scale high-margin product lines (Lifestyle, Kids Basketball)
  • Replicate Bangalore’s success model in other regions
  • Improve data collection standards

📄 Report

📌 Full presentation-style report available in the report/ folder.


👤 Author

Ashok M


📜 License

MIT License

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Data analysis project on Nike sales data to uncover business trends, profitability drivers, and strategic insights.

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