Data Analytics Project

BikeDekho Purchase Trend Analysis

A complete data analytics project analyzing gender-wise bike purchase behavior using real-world dataset patterns, dashboards, and automated reporting.

📘 Project Overview

This project focuses on understanding consumer behavior on BikeDekho using gender-segmented purchase data. The objective was to analyze purchase trends, conversion rates, income and age impact, and generate actionable business insights using visual dashboards and a final PDF report.

🛠 Tech Stack

Python (Pandas, Matplotlib)
Data cleaning & analysis

Excel
Raw data & dashboards

ReportLab
Automated PDF report

📊 Data Analysis Workflow

Data Understanding

Total Purchased
Not Purchased
Conversion Rate
Average Income
Average Age

Data Cleaning

Removed noisy headers
Converted numeric fields
Filtered valid gender categories

📈 Dashboard Visualizations

🔍 Key Insights

Women show slightly higher purchase conversion rate (48.5%) than men.
Income differences do not significantly impact buying decisions.
Average age across genders is nearly identical (~44 years).
Men have higher purchase volume mainly due to sample size.

📄 Deliverables

✔ Cleaned dataset
✔ Visual dashboards
✔ Insight summary
✔ Automated PDF report
✔ GitHub-ready documentation