1. Bike Share
How Casual Riders Differ from Members
Presented by Jennifer Pinti
December 30, 2021
2. Data Discovery Deep Dive
Goal
● Reach out to bike share users who are not members.
● These users already have utilized the service, and we need to see
what would target them to switch to become annual members
● From the findings, marketing campaigns can be implemented most
effectively
What patterns did we find between casual riders and annual members?
3. Ride Duration
● There is a significant difference in
ride duration from casual riders vs.
members.
● Casual riders actually spend an
average of 3x more time on their
bike share rides!
● The member uses their ride for
around 16.7 minutes.
● Casual spends 50 minutes.
*data provided by Motivate International to Google Data Analyst
program
4. Number of Rides
● An average of 5e+05 (or 4 million)
rides are from members
○ mid week being when the
service is used the most
● An average of 2e+05 (or 1.5 million)
in casual rides
○ More rides on weekends
● Even with the difference in use on
days of the week, members still use
the ride share around 2.5x more
frequently.
*source: company data Q2-4 2019 & Q1 2020
5. Conclusion
● the casual rider uses the
ride share longer
● May be to get the most out
of a one time payment
● the member uses
the ride share more
frequently
● No need to hold
onto the bike
Reaching out to casual riders would be worthwhile but more data would be of value
The Relation of Ride Duration and Frequency
Casual riders may use the service and more frequently & in shorter duration as members
6. ● Conduct a poll to find user intent
● Look at behaviors (data of behavior) of other bike
shares
● Build a marketing campaign to casual riders based
on the results
Plan of Action
Notas del editor
The chart is in seconds: 1000 seconds is around 16 minutes, and 3000 seconds is around 50 minutes.
Just as there is a significant difference in ride duration of casual riders vs. members, the findings show different behaviors in the number of rides.
Since we see that the casual rider uses the ride share longer, and the member uses the ride share more frequently, we conclude that the casual rider is looking to get the most out of each ride, as they pay every time they use it, instead of being able to use the service freely.
Knowing if the intent of the ridersare the same, solidifies our findings. If we move forward with what we know of the existing data, we can still reach the casual riders, knowing that they use the service differently (longer & less frequent, more on weekends), and simply focus on value. If we can gather data to find user intent, we can target the campaigns specifically and potentially have a higher return.
