Cyclistic Bike Share Case Study
Cyclistic Bike Share Case Study
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In this project, I analyzed data for the marketing team to Identify the main differences between two types of customers the casual and annual riders, and use digital media to influence them.
In this project, I analyzed data for the marketing team to Identify the main differences between two types of customers the casual and annual riders, and use digital media to influence them.
Introducion
Introducion
Scenario
I am a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago (Fictional company). The director of marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore, my team wants to understand how casual riders and annual members use Cyclistic bikes differently. From these insights, my team will design a new marketing strategy to convert casual riders into annual members.
About the company
In 2016, Cyclistic launched a successful bike-share offering. Since then, the program has grown to a fleet of 5,824 bicycles that are geo 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.
Moreno (Marketing manager) has set a clear goal:
Design marketing strategies aimed at converting casual riders into annual members.
In order to do that we in the marketing analyst team need to better understand how annual members and casual riders differ, why casual riders would buy a membership, and how digital media could affect their marketing tactics. Moreno and her team are interested in analyzing the Cyclistic historical bike trip data to identify trends
My process In Analysis
My process In Analysis
In order to answer the key business questions, I will follow the steps of the data analysis process: ask, prepare, process, analyze, share, and act
In order to answer the key business questions, I will follow the steps of the data analysis process: ask, prepare, process, analyze, share, and act
About The data
About The data
This dataset is the first-party data collected from its organization and located in 12 CSV files; every file represents a month from the 2022 year, organized into 13 columns. There is no biased or credibility in this data because this is first-party data. This data is ROCC (Reliable, original, comprehensive, current, and cited)
ASK
ASK
Three questions will guide the future marketing program:
How do annual members and casual riders use Cyclistic bikes differently?
Why would casual riders buy Cyclistic annual memberships?
How can Cyclistic use digital media to influence casual riders to become members?
Business Task
Business Task
Identifying the main differences between casual and annual riders and using digital media to influence them
Prepare and clean data
Prepare and clean data
In This stage, I prepared the data for analysis by doing these steps
In This stage, I prepared the data for analysis by doing these steps
Calculating the ride length and the day of the week by using spreadsheets
Merging 12 CSV files into one file to make a full-year analysis by using python
Dropping Nulls value
transforming the data type of end date and start date to date type
I dropped the ride_length and make a new one in minutes in integer type
I dropped the start station name id and the end station name Id
Removing negative and zero values of ride length
Create a monthly column by extracting it from the start date
I checked the duplicated rows
Make sure the columns are consistent
Saving cleaned data into a new CSV file ( to use it for visualization)
That is the analysis using Python on GitHub
Analysis and Insights
The number of each member and casual riders
Casual riders represent about 40% and members represent about 60 %
The Average ride_length of member and casual rider
The average ride length of casuals is 24.2 minutes, whereas the average ride length of members is 12.6 minutes. The casual riders spend more time than member riders.
Most days riders use the bikes
The most day the member use bikes are Thursday, Wednesday, then Tuesday
The most day, casual riders use bikes on Saturday, then Sunday (on the weekend)
The Average Rider Length Per Month
The casual riders spend their time in March, then in May. But the annual subscribers (members) spend their time in June, July, and May
The Average Rider Length Per Day
The casual riders spend their time on Sunday and on Saturday, then on Monday. But the annual subscribers (members) spend the most time on Saturday and Sunday
Most months has a high use of bikes
The activity of annual subscribers' bike users is high from May to October (and the most active month is August)
The activity of casual bike users is high from May to September (and the most active month is July) they active in the summer
The most popular type of bikes the two riders use on their journey
The casual riders use the docked type where the member does not
The type used by the casual and members is the classic bike then, the electric bike
Recommendations
Recommendations
I suggest making a summer subscription to attract casual users.
Where the casual members' ride length is more than the annual subscriber, the casual riders use the bike on weekends and in summer. We can customize a new subscription for casual users.
Whereas the casual subscribers used the docked type cycle, We can make an offer when they use the docked type in an annual subscription.
Using Digital media to clarify the benefits of subscribing to the membership for riders who have a long ride length
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