🚴‍♂️ Bike Sales Dashboard

📌 Project Overview

This project analyzes bike purchase behavior using customer demographic and lifestyle data. The goal is to build an interactive Excel dashboard to visualize key insights, identify trends, and support data-driven decision-making.

📂 Project Files

• Excel Project Dataset.xlsx → Original dataset containing 1,026 records of customer details.

• Bike_SaLes_dashboard.xlsx → Final project workbook with:

  • bike_buyers → Cleaned dataset (1,000 records)
  • Pivot Table → Aggregated data for analysis
  • Dashboard → Interactive visualization of insights
  • Working Sheet → Intermediate calculations and transformations

📊 Key Features of the Dashboard

• Demographic breakdown of bike buyers (Age, Gender, Marital Status)
• Income vs. Bike Purchase analysis
• Commute distance and regional trends
• Car ownership and family size impact on purchases
• Interactive filters for dynamic insights

🛠 Tools & Techniques

• Microsoft Excel

  • Data cleaning and transformation
  • Pivot tables for aggregation
  • Charts & slicers for interactive dashboarding

🚀 How to Use

1. Open Bike_SaLes_dashboard.xlsx in Excel.
2. Navigate to the Dashboard sheet.
3. Use the slicers and filters to explore different customer segments and insights.

📈 Insights (Examples)

• Middle-aged professionals with higher income are more likely to purchase bikes.
• Customers with shorter commute distances show higher interest in bike purchases.
• Regions show varying bike adoption trends, with noticeable differences between Europe and Pacific areas.

💡 Contributions and suggestions are welcome! Fork this repo, explore the data, and enhance the dashboard.