I have completed this project to complete the final step of the google analytics program which is a capston project. This case study is about a fictional company called Cyclistic which has a potential to increase profitability by converting casual users to members. As a data analyst, my role was to dive more into the behaviors of the casual riders to understand if there are any potential opportunities for the company. The dataset used in this case study are licensed by Motivate International Inc (https://ride.divvybikes.com/data-license-agreement).

1. Capstone Case study
How does a Bike-Share Navigate speedy success
Completed by: Plato Khisa

2. Background of the company: Cyclistic
• Bike-share company based in Chicago
• The company follows similar type of business model as Uber but with
some differences:
• The obvious difference is that they offer ride-share in forms of bikes
• The bikes are operated by the user and responsible for parking it in the
docking station
• They offer reclining bikes, hand tricycles and cargo bikes
• Most users use it for leisure, with only one-third of the total users are using
the bikes for commuting to work

3. A basic overview of different type of users
• Mainly two types of users:
• Casual riders: Customers who purchase
it for a single day use
• Cyclistic Members: Customers who
purchase annual memberships
• 5.71M of trips were made in the one
year period between Dec 2021 to
Dec 2022.
• Around 3.37 million (59%) trips were
made by Cyclistic Members

4. The key business Questions
• Is there any room for more making Cyclistic more profitable?
• The financial analysts believe so. They believe that the company can be more
profitable by converting the casual riders into Cyclistic Members
• Their estimate may be feasible because the casual riders rode for 25 million
more minutes than the Cyclistic Members in the one year period between
Dec 2021 to Dec 2022
• In order to do that, the company must come up with a successful Marketing
Campaign to convert the casual users to Cyclistic members.
• It is important to know how the different types of users behave or use the
Cyclistic platform so that a successful marketing strategy can be implemented.

5. Main objectives of the project
• The main goal is to convert Casual users to Cyclistic members.
However, firstly we need to understand whether the casual
members would bring more profit to the company.
• If we can confirm that the converting casual riders would actually
bring more profits to the company, then we will dig more into the
behaviors of the casual users and try to answer the following
questions:
• How similar or dissimilar are casual riders from the Cyclistic members
• What can we know from the trip data to make an effective marketing
campaign?

6. Data, methodology and cleaning
• Cyclistic is a fictional company and the case study is designed by a team from google
for the students
• Source: the dataset is made by Motivate International Inc. The dataset consists of 12
CSV files where each file contains the trip data of each month from Dec 2021 to Dec
2022.
• For the convenience of the analysis, each CSV files were merged into a single CSV file
• Then the merged CSV file was loaded to POWERBI platform where the data was
cleaned using POWER Query Editor
• The main cleaning steps included: removing columns, dissecting the start timestamp
into two different columns: Day of the week and Month, calculating ride time by doing
mathematical operations with start_timestamp and end_timestamp
• After the completion of the data cleaning, the visualizations were made using Power BI
tools

7. How are the casual users and Cyclistic
members are different
• Even though Cyclistic members
make more trips but the ride time
of casual users are significantly
more than the Cyclistic members in
the given time period (Dec 2021-
Dec 2022)

8. How are the casual users and Cyclistic
members are different
The average ride time of
the casual users is almost
2.5 times than the
Cyclistic members

9. Insights from the ride times of both users and
it’s implication on Marketing Strategy
• Our data shows that the casual users have more ride times than the
Cyclistic members
• Since the data is not adequate to find more insights about the casual
users, we can assume that most of the casual users are not returning
customers or frequent users
• The marketing strategy should focus on giving rewards to those casual
users so that they purchase a long-time subscription from Cyclistic

10. More insights about casual and Cyclistic
members
The casual riders are
more proactive on the
weekends, whereas the
Cyclistic members are
proactive throughout
the week

11. More insights about casual and Cyclistic
members
There is an upward
trend in the ride time
of the casual users
from the month of
April and lasts until July
but the traffic of casual
users remains more
than the members until
the end of October

12. More insights about casual and Cyclistic
members
Electric bike is the
most popular category
from the casual users
which is followed by
classic bike

13. More implication for the marketing team
• Casual users use the platform more on the weekends and their usage hike
from the month of April-October. The marketing team can use this
knowledge to offer two different types of membership deals to the casual
customers, which are:
• 6 month subscription from May-October with a price which is a bit
higher than the annual subscription but less than casual users. This is to
ensure that the annual subscription remains as the most lucrative offer
from the company.
• Sub-annual/ monthly subscription plans for weekend users: In this type,
customers can subscribe for sub-annual periods but can only use the
bikes during the weekends.

14. Top places/stations to organize a marketing
campaign

15. Implication for digital marketing
• Right now digital marketing is one of the most efficient techniques to
reach customers. But the given data has no relevant information to
find more insights about target customers.
• For an effective marketing strategy the company should try to collect
the customer data more eloquently, which means that the company
must have information about the age, gender and occupation of the
consumers to meet the minimum criteria.

16. Conclusion
• There is a scope to make more profits by converting casual users who
make the most of the ride time for the company into members
• The casual users usually ride on weekends, but their ride times hike
seasonally from May- October
• The company can come up with sub-annual subscription offers during
the seasonal period so that it is more rewarding for the casual riders
to use the platform as a member than a casual user.
• For the digital marketing, the company should collect more
information about the customer so that they can target their
customers appropriately.