How Does a Bike-Share Navigate Speedy Success?

Background Info: https://github.com/xJQx/Cyclistic-Riders-Analysis/blob/main/Background%20Info.pdf

Dataset: https://divvy-tripdata.s3.amazonaws.com/index.html

R Documentation: https://xjqx.github.io/Cyclistic-Riders-Analysis/

Slide Deck: https://github.com/xJQx/Cyclistic-Riders-Analysis/blob/main/Slide%20Deck.pdf

Scenario:

I am a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. 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. But first, Cyclistic executives must approve my recommendations, so they must be backed up with compelling data insights and professional data visualizations.

Business Task:

• How do annual members and casual riders use Cyclistic bikes differently?
• Analyse how annual members and causal riders use Cyclistic bikes differently and provide data-driven recommendations for a new marketing strategy to convert causal riders to members

Key Stakeholders:

• Lily Monero: Director of Marketing and my manager
• Cyclistic Marketing analytics team: Team of data analysts
• Cyclists executive team: Stakeholder approving recommendations

Documentation of Data Analysis Process:

R Documentation:

• R Documentation*
  
• R Code
  
• R Markdown Code

Excel Pivot Table and Chart:

• Excel Pivot Table
  
• Excel Pivot Table Image
  
• Excel Pivot Chart Image

Conclusion of Analysis:

Casual Riders:

• Casual riders use the bikes for relaxation and as a bonding exercise with family and friends.

  • Casual riders has significantly higher average ride duration of than members throughout the week.
  • Casual riders use the bikes more often on the weekends (Saturday and Sunday).

• Casual riders use the bikes as a form of exercise in order to meet their New Year's resolution.

  • Casual riders use the bikes significantly longer in the first few months of the year.

Members:

• Members use the bikes as a form of transportation regularly to travel to work/school.
  • Members use the bikes more compared to casual riders all together.
  • Members use the bikes more frequently on weekdays (Monday to Sunday).
  • Members are consistent in their riding duration throughout the year.

Visualization:

Comparing Average Number of Rides & Average Ride Duration between Casual Riders and Members:

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Average Ride Duration & Number of Rides by Type and Weekday:

Number of Rides Trend for Casual Riders vs Members:

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Average Ride Duration by Type and Month:

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Number of Rides Throughout the Month:

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Recommendations:

1. Advertise during New Year's period to convince casual riders to convert to members.
2. Encourage casual riders to sign up for membership to use bikes as alternative mode of transportation, for health and environment.
3. Introduce an exclusive members' community with members' only bonding and relaxation events/activities.

Future Improvements:

• Collect survey data for analysis to better understand the decision-making mindset of casual riders vs members.
• A larger data set can be used for analyzing longer term trends and behaviors of riders.
• The start and end stations can be analyzed to see if there are any particular areas that have more members and find the reasons for such occurrences.