The primary goal of this analysis is to identify and describe how casual riders and annual members (subscribers) use the fictional company Cyclistic’s, bike rental service differently. By uncovering these patterns, we aim to provide data-driven insights to help the marketing team transition casual riders into loyal annual members.
The data for this analysis was provided by Divvy Bikes, consisting of user trip data for the year 2019. The dataset includes information on trip duration, start and end times, station names, user types, and demographic information such as gender and birth year.
To ensure a high degree of accuracy and reliability in the findings, the following cleaning steps were performed:
Removal of Incomplete Records: Rows containing “NA” for gender and/or birthyear were removed. This accounted for approximately 6% of the total data.
Time Extractions: A new column was created to extract the Month of each trip to allow for seasonal analysis.
After processing the 2019 data, several clear trends emerged:
User Volume: There are significantly more Subscribers than there are Casual users of the service.
Trip Duration: The data shows that Subscribers utilize the service for much longer periods of time than do Casual users.
Gender Demographics: Men represent the majority of users across both Subscriber and Casual categories (~73%-77%).
Age Insights: The average age of all users is 45. Interestingly, women tend to be slightly younger on average (43 years old).
Seasonal Demand: There were significantly more rides completed in March compared to January or February, suggesting a correlation with the onset of Spring.
Ridership Volume: Subscribers vs. Casual
How the two user groups compare in total numbers.
Usage by Gender and User Type.
Visualizing the spike in March ridership.
Top Three Recommendations:
Leverage the “March Spike”: Launch a “Spring into Cycling” marketing campaign in late February. Since data shows a significant increase in March, this is the optimal time to offer conversion incentives (like a discount on the first month of a subscription) to casual riders.
Targeted Demographics: Since the average age is 45 and women skew younger, create marketing content that resonates with these specific age brackets. Highlighting female riders in advertisements may also help close the gender gap observed in the data.
Focus on Duration Value: Since Subscribers ride for longer periods, marketing should emphasize the comfort and cost-effectiveness of annual memberships for long-distance commutes or extended weekend exercise.