Bike Rental Data Analysis Project
Objective:
Analyzed bike rental data to differentiate between annual members and casual riders, optimizing marketing strategies.
Tools Used:
- SQL for data querying and analysis.
- Python for data manipulation and statistical analysis.
- Tableau for data visualization.
Key Actions:
- Conducted detailed analysis using SQL and Python to uncover usage patterns and customer behavior differences.
- Utilized Tableau to create visualizations that highlighted insights on peak usage times and popular rental locations for annual members and casual riders.
- Recommended targeted marketing campaigns based on preferences and behavior patterns to increase annual membership conversions.
Results:
- Identified that annual members account for 70% of total rentals, with casual riders contributing 30%.
- Developed data-driven campaigns that led to a 15% increase in annual membership conversions.
- Presented findings and recommendations to stakeholders, earning praise for actionable insights aligning marketing efforts with customer preferences.
Conclusion: This project demonstrates proficiency in data analysis, visualization, and strategic recommendation skills, contributing to informed decision-making and business growth.