Background
Cyclistic Bike-Sharing is a case-study for the Google Data Analytics Professional Certificate capstone project.
Cyclistic is a bike-sharing company located in Chicago and has been operating since 2016. The company has a large cycling network with total 692 stations across the city and 5,824 bicycles equipped with lock and geotracking tool. There are 2 types of memberships available for users: casual rider and annual member.
Scenario
The analyst team wants to understand how casual riders and annual members use Cyclistic bikes differently. From the insight, the team will design a new marketing strategy to convert casual riders into annual members.
Datasets
This project utilized one year of Cyclistic bike-sharing data spanning from November 2021 to October 2022. The datasets are available for access at the following link: Cyclistic Datasets.
Tools
This project utilized three primary tools:
R: For loading, cleaning, transformation, and analysis.
Microsoft Excel: for exporting results from R and generating summary tables.
Microsoft Power BI: For data visualization and report creation. While Tableau was introduced in this course for visualization, Power BI was preferred based on my personal experience. I believe both tools offer comparable capabilities for this project's visualization and reporting needs.
R Code
Because the size of each dataset is quite large - more than 100 MB for each monthly dataset, so I analyzed each dataset separately in each R-file. At the end, there are 12 R-files contain analysis for each month. But, I only upload 1 R-file because the code in files are same except for dataset file name.
Libraries
This analysis primarily utilized two R libraries:
tidyverse : For general data manipulation, transformation, and visualization.
lubridate : For manipulation of date and time variables.
R File
Link to R file: 2011_11.R
Reports
Total Rides and Average Ride Time based on Membership
Total Rides based on Membership and Bike Type
Amount of Bike Type based on Membership
Bike Type Percentage for 1 Year based on Membership
Favorite Start/End Stations based on Membership
Average Ride Time (in minutes) and Favorite Start/End Time based on Membership
Insight
In general, number of member-users was larger than casual-users, except in summer months. As shown in the table and chart above, in July 2022, number of casual-users was only slightly lower than number of member-users.
Number of casual-users reached its peak during summer months: June, July (maximum) and August.
There were 2 types of bike for member-users: classic and electric; while casual users had 3 options: classic, electric, and docked.
Average ride-time for casual-users was longer than member-users. Casual-users rode their bike for 23 to 33 minutes, while member-users only for 11 to 13 minutes.
For casual-users, their favorite start and end station was Streeter Dr and Grand Ave; while for member-users, it varied based on months.
Both casual-users and member-users has similar favorite for start and end hour i.e. at 17 p.m. Since their average ride-time was less than 1 hour, so most of the users rode their bike starting at 17.00 p.m and finished before 18.00 p.m.
Action - Marketing Strategy
Based on analysis above, we can see that casual-users reached maximum number at summer time, from June, July and August; they started and ended their rides at Streeter Dr and Grand Ave Station; between 17.00 p.m to 18.00 p.m.
Therefore Cyclistic Company should make event to promote the benefit of membership to these casual-users on either June, July (best month), or August, in Streeter Dr and Grand Ave Station, at 17.00 p.m. to 18.00 p.m.
Further Analysis
20 Most Popular Start Station