Turning Casual Cyclists into Loyal Members: My Cyclistic Capstone Case Study
This month, I wrapped up my Google Analytics Certificate capstone project by diving into Chicago’s Cyclistic bike-share data. As a storyteller, I wanted to understand how casual riders and annual members use the service—and how Cyclistic could convert more of those one-time cyclists into year-round subscribers.
The Big Question
How do annual members and casual riders use Cyclistic bikes differently—and what can we do with those insights?
Key Findings
Shorter Commutes vs. Long Leisure Rides
Members average about 13 minutes per trip, suggesting point-to-point, commute-style usage.
Casual riders average 1 hour & 25 minutes, indicating more leisure exploration.
Peak Times Differ
Members spike at 7–9 AM and 4–6 PM
Casual riders peak 12–4 PM.
Hotspot Stations
Between 12 PM–6 PM, casual riders cluster at tourist-friendly stations.
Members concentrate around business districts (e.g., Clinton & Madison, Clinton & Washington).
Day-of-Week Patterns
Tuesdays and Thursdays are busiest overall—ideal for mid-week membership promotions.
Casual ridership surges on Saturdays, while members still ride heavily on Sundays.
Strategic Recommendations
Midday “Discover Chicago” Pass
Promote a 4-hour bundle or half-day pass at popular leisure stations (Canal & Adams, Michigan & Washington) to convert casual riders exploring the city.
Rush-Hour Commuter Bundles
Offer a discounted “5-day commuter” pass for members at business-district stations (Clinton & Madison, Clinton & Washington).
Station-Targeted Messaging
Deploy digital signage or in-app notifications at top stations during key time windows (7–9 AM for members; 12–4 PM for casuals) to highlight annual-membership perks (e.g., unlimited rides, reduced per-ride cost).
Weekday Trial Offers
Run a “Two-Week Free Trial” email campaign on Tuesdays and Thursdays—when ridership is already high—to nudge casual riders into the membership funnel.
Dive Deeper: View the Full Presentation
I’ve packed all my charts, data tables, and step-by-step analysis into a Google Slides deck. Click the link above or below to explore every visualization and insight:
Thanks for reading! If you’re curious about data-driven storytelling, let me know!