Bike Sales Visualization with Google Sheets

Overview

This project analyzes bike sales data from Kaggle, focusing on customer demographics, commuting habits, and purchasing behaviors. The analysis was conducted using Google Sheets, involving data cleaning, pivot tables, and visualizations to create an interactive dashboard for stakeholders to explore trends and insights.

Project Details

1. Data Cleaning and Transformation

• Original data included fields like ID, Marital Status, Gender, Income, Children, Education, Occupation, Home Owner, Cars, Commute Distance, Region, and Age.
• Transformed data by creating an additional Age Brackets column, grouping customers into age categories (e.g., "Young", "Middle Age", "Older Adults").
• Adjusted data fields for readability and analysis (e.g., Gender as "Male" or "Female", Income as formatted numbers).

2. Visualization 1: Average Income Per Purchase

• Used a pivot table to calculate the Average Income for customers who purchased bikes.
• This graph helps stakeholders identify income trends among bike purchasers.

3. Visualization 2: Customer Age Brackets

• Grouped customers by Age Brackets and visualized bike purchase behavior by age category.
• This provides insights into which age groups are more likely to purchase bikes, guiding marketing strategies.

4. Visualization 3: Customer Commute Distance

• Visualized customer bike purchases based on their commute distances (e.g., 0-1 miles, 2-5 miles).
• Helps identify which customers are more likely to purchase bikes based on commuting habits.

5. Dashboard Creation

• Combined all three visualizations into an interactive dashboard.
• Applied filters for Marital Status, Region, and Education to allow deeper exploration of trends.

Tools Used

• Google Sheets: For data cleaning, organizing, and visualization using pivot tables and charts.

Visualizations Included

• Average Income per Purchase: Showcasing the income trends for bike purchasers.
• Customer Age Brackets: Displaying purchasing behavior by age categories.
• Customer Commute Distance: Highlighting how commuting distance influences bike purchases.

How to Use

1. Google Sheets Link: Open the Google Sheets file to interact with the pivot tables and graphs.
2. Apply Filters: Use filters for marital status, region, and education to explore the data further.
3. Explore the Dashboard: The dashboard allows stakeholders to analyze trends across demographics and commuting habits.

Future Improvements

• Add additional filtering options, such as occupation and car ownership.
• Expand the dataset with more demographic details or sales figures.