In 2016, Cyclistic, a fictional bike-sharing company, launched a successful bike-share program in Chicago. Cyclistic's flexible pricing plans include single-ride passes, full-day passes, and annual memberships. Customers who purchase single-ride or full-day passes are referred to as casual riders, while those with annual memberships are known as Cyclistic members.
The primary objective of this Excel project is to analyze how annual members and casual riders use Cyclistic bikes differently. This analysis will help design targeted marketing strategies aimed at converting casual riders into annual members.
The dataset used in this analysis contains trip data from June 2023, provided directly by Cyclistic. The data has been cleaned and prepared in Excel to ensure data quality and consistency.
This Excel project aims to provide comprehensive insights into the usage patterns of Cyclistic bikes by different types of riders. By analyzing the trip data using Excel, we can uncover key differences in how annual members and casual riders utilize the bike-share service.
The analysis includes:
- Data cleaning and preparation using Excel.
- Examination of ride duration and frequency.
- Comparison of usage patterns between casual riders and annual members.
- Identification of peak usage times and popular routes.
- Recommendations for targeted marketing strategies to convert casual riders into annual members.
The following visualizations are included in this project:
- Overall Bike Rides: Calculates the percentage of casual riders and members for the month of June.
- Total Rides Across a Week: Shows the distribution of total rides throughout the week.
- Average Ride Length Across a Week: Analyzes the average duration of rides on each day of the week.
- Preferred Bike Type: Identifies the most commonly used bike types by riders.
- Total Rides vs. Bike Type: Compares the total number of rides for different bike types.
- Average Ride Length vs. Bike Type: Examines the average ride length for each bike type.
These visualizations provide a detailed understanding of rider behavior and preferences, which can inform strategic decision-making for Cyclistic.
The findings from this analysis will help Cyclistic design effective marketing strategies to increase annual memberships. By understanding the behaviors and preferences of casual riders, Cyclistic can tailor its offerings to better meet the needs of potential annual members.
Contributions to this project are welcome! If you have any ideas, suggestions, or improvements, please feel free to submit a pull request. Make sure to provide a detailed description of your changes.
The dataset used in this project has been made available by Motivate International Inc. under their Data License Agreement. Please refer to the license for terms and conditions regarding the use of the data.