Google Capstone Project

This is a detailed article explaining the steps I took and the conclusions I came to for this capstone project.

Scenario

    For this project, I'm a junior data analyst for a fictional company called "Cyclistic", a bike-share company in Chicago. I've been given the task of figuring out how annual members and casual riders use Cyclistic bikes differently and design a new marketing strategy to convert casual riders into annual members.

Ask

In this step, I asked myself the question “How do annual members and casual riders use Cyclistic bikes differently?” It’s believed that annual members are more profitable than casual riders. My task was to analyze the data to find the difference between casual riders and members and then provide recommendations to convert casual riders into annual riders.

Prepare

To prepare I downloaded the data for this case study. I downloaded the trip data from Q2-Q4 of 2019 and Q1 of 2020 from here.

Process

For this step, I combined and uploaded the data into one excel workbook. This is where I cleaned the data removing any duplicates and NULL data. I created a column called “ride_length” where I found the ride length for each ride. Next, I created a column called “day_of_week” so I could find out what day each ride fell on.

Analyze

 In this step, I created a pivot table to help summarize the data and calculate the average ride_length for users by day of the week and calculate the number of rides for users by day of the week. I then merged the data into a full-year view using R Studio.

Share

Lastly, I went to R studio where I created visuals to represent the data.

    

In the picture below you can see the results of where I compared the average ride length of casual riders and member riders. What I found was casual riders on average have a longer ride length than member riders.

    

    Below, you can see where I compared the count of all rides of casual riders and member riders. While casual riders have a longer ride length member riders take more rides than casual riders. Especially, in the month of July when members more than doubled the number of rides taken compared to casual riders.

 
Lastly, I compared the count of all rides for both casual and member riders throughout the week. What I found was the busiest day of the week for casual riders and member riders was Tuesday. 

Insights summary

• Casual riders on average have a longer ride length than member riders.
• While casual riders have a longer ride length member riders take more rides than casual riders. Especially, in the month of July when members more than doubled the number of rides taken compared to casual riders.
• The busiest day of the week for casual riders and member riders is Tuesday. 

Business Recommendations

    Based on my research I've come up with three recommendations to convert casual riders into annual members.

• Provide a 30-day trial membership for casual members where at the end they are given the option to become an annual member at a discounted price.
• Offer discounted memberships during periods where Cyclistic bikes show more use. For example, during the summer months of June, July, and August.
• Highlight membership benefits and offer discounts to current members who share their experience with Cyclitic bikes and get new users to sign up for membership through referral links.

What I've learned

Below are some of the things I've learned from completing this project.

• How to use Microsoft Excel to prepare data for analysis.
• How to use RStudio to clean data using tidyverse and make insights with data.
• Creating visuals in Tableau to find insights and make business recommendations.