Cyclistic Bike-Share Analysis

This project analyzes how annual members and casual riders use Cyclistic, a fictional bike-share company created for the Google Data Analytics Professional Certificate case study. Using real-world Chicago bike-share trip data, I analyzed 84,776 rides to identify differences in ride volume, duration, day and time of use, weekday versus weekend patterns, and starting stations. The analysis found that members accounted for 72.13% of rides, while casual riders took substantially longer trips and showed a stronger relative preference for weekend riding.

The findings suggest opportunities for Cyclistic to use behavior-based marketing to convert casual riders into annual members. Recommended strategies include targeting casual riders during weekends, focusing on riders who take longer or repeated trips, and using high-activity times and locations for targeted promotions. The project demonstrates practical skills in data cleaning, spreadsheet analysis, pivot tables, visualization, and translating data findings into business recommendations.

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