Google Data Analytics Capstone Project:
Cyclistic Bike-Share Analysis
Introduction
In 2016, Cyclistic launched a successful bike-share offering. Since then, the program has grown to a fleet of 5,824 bicycles that are tracked and locked into a network of 692 stations across Chicago. The bikes can be unlocked from one station and returned to any other station in the system at any time.
Cyclistic offers two pricing plans: single-ride passes and full-day passes, and annual memberships. Customers who purchase single-ride or full-day passes are referred to as casual riders. Customers who purchase annual memberships are Cyclistic members.
Lily Moreno, the marketing manager has assigned me the task of analyzing Cyclistic historical bike trip data to identify trends to identify how annual members and casual riders use Cyclistic bikes differently. The data analysis will follow the following steps: Ask, Prepare, Process, Analyze, Share and Act.
Ask
The following business question will also be answered to help the future marketing program:
How do annual members and casual riders use Cyclistic bikes differently?
Prepare
The data was made available by Motivate International Inc under this License. The dataset follows the ROCCC analysis as described below:
Reliable: yes
Original: yes, the original data can be located
Comprehensive: yes, all important information was provided
Current: yes, the dataset is updated monthly
Cited: yes
The dataset can be found here
Process
I downloaded the dataset and stored it in my system. I used Excel power query to clean and analyze the data. I analyzed the data from April 2020 — Mar 2021 as follows:
1. Created custom column “ride_length” = [ended at] — [started at]
2. Extracted a new column “month” from “started_at” to enable me to analyze which month of the year rides were taken.
3. Extracted a new column “day_of_week” from “started_at” to enable me to analyze which day of the week rides were taken.
4. Missing rows were deleted.
5. I put the months and days of the week in the right order.
6. Removed duplicates
Analyze
The dataset was analyzed as follows:
Number of ride types
There were 3 types of bikes available: Docked bikes, Electric bikes, and Classic bikes. Further analysis of the bike types revealed that docked bikes were mostly used during the period under review with over 2.5M bikes being used. This was followed by electric bikes recording over 400k bikes.
Ride behavior of members and casual riders
Cyclistic bike company offers 2 types of membership: members and casual. Analysis showed that members took more trips than casual members. But further analysis revealed that casuals rode for a longer duration than members during the period under review.
Number of rides per day
Analysis of the number of rides per day revealed that Saturdays were the busiest day of the week having casual riders recording a higher number of rides than members. This was followed closely by Sundays with both riders recording almost similar number of rides. This could be attributed to the fact that they are weekends when most people are not at work and have ample time to ride their bikes. During the weekdays, members recorded a higher number of rides compared to casual riders.
Number of rides across months
Analysis of the number of rides across the different months revealed that Cyclistic company recorded a steady rise in the number of rides from June. This peaked in August and steeply declined in December with members taking more trips than casuals. The peak could be attributed to the summer season when most people are on vacation and have more time to ride bikes. The steep decline in December could be attributed to the Winter season when most people remain indoors because of the cold.
Ride Analysis
The average length per ride is: 00:28:41 (mins)
The max length per ride is: 18:40:02 (hrs)
Share
Below is a dashboard displaying how casual riders use Cyclistic differently from members.
Act
Recommendations
1. Offer incentives/promos to casual members since they use the bikes for longer periods to convert them to members. Maximize the traffic during weekends to run these promos.
2. Offer extra services such as free repairs, change of tires, extra gear, and warm clothing at each station to encourage more people to ride during the winter season.
Recommendations for further analysis
- Analyze the top ten busiest start stations. This will guide the organization in making decisions regarding where to focus their campaigns and promos to convert casual riders to members.
- Information regarding the age, gender, and lifestyle of riders should be made available. this will enable the organization better assess their clients and guide them in organizing promos, and campaigns best suited for the riders.
