Introduction
This is the part of the last assignment of the Google Data Analytics Profesional Certificate from Coursera.This document includes the steps followed as required by the Google DA Capstone Project for the Cyclist Bike-Share case.
You are a junior data analyst working on 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, your team wants to understand how casual riders and annual members use Cyclistic bikes differently. From these insights, your team will design a new marketing strategy to convert casual riders into annual members. But first, Cyclistic executives must approve your recommendations, so they must be backed up with compelling data insights and professional data visualizations. Characters and teams
● Cyclistic: A bike-share program that features more than 5,800 bicycles and 600 docking stations. Cyclistic sets itself apart by also offering reclining bikes, hand tricycles, and cargo bikes, making bike-share more inclusive to people with disabilities and riders who can’t use a standard two-wheeled bike. The majority of riders opt for traditional bikes; about 8% of riders use the assistive options. Cyclistic users are more likely to ride for leisure, but about 30% use the bikes to commute to work each day.
â—Ź Lily Moreno: The director of marketing and your manager. Moreno is responsible for the development of campaigns and initiatives to promote the bike-share program. These may include email, social media, and other channels.
● Cyclistic marketing analytics team: A team of data analysts who are responsible for collecting, analyzing, and reporting data that helps guide Cyclistic marketing strategy. You joined this team six months ago and have been busy learning about Cyclistic’s mission and business goals—as well as how you, as a junior data analyst, can help Cyclistic achieve.
â—Ź Cyclistic executive team: The notoriously detail-oriented executive team will decide whether to approve the recommended marketing program.
Cyclistic is a bike-share program that features more than 24800 bicycles a692 700 docking stations across Chicago. The bikes can be unlocked from one station and returned to any other station in the system anytime.
Cyclistic’s marketing strategy relied on building general awareness and appealing to broad customer segments. One approach that helped make these things possible was the flexiblity of its pricing plans: single-ride passes, full-day passes, and annual membership. Customers who purchase single-ride or full-day passes are referred to as casual riders. Customers who purchase annual membership are Cyclistic members.
The director of marketing believes the company’s future success depends on maximizing the number of annual membership. Therefore, as a Data Analyst, our job is to find and analyze any pattern or trend in Cyclistic historical bike trip data to understand how casual riders and annual members use Cyclistic bikes differently. From these insights, we can create a new marketing strategy to convert casual riders to annual members.
Three questions will guide the future marketing program:
1.How do annual members and casual riders use Cyclistic bikes differently?
2.Why would casual riders buy Cyclistic annual memberships?
3.How can Cyclistic use digital media to influence casual riders to become members?
Deliverables for the project
1.A clear statement of the business task
2.A description of all data sources usedDocumentation of any cleaning or manipulation of data
3.A summary of the analysis
4.Supporting visualizations and key findings
5.Recommendations based on the analysis nalysis
Guiding questions
â—Ź What is the problem you are trying to solve?
â—Ź How can your insights drive business decisions?
Deliverable for the ASK phase
Clear statement of the business task: Determine how casual users and members behave to tailor a strategy to make the casual users get a membership.
The dataset I use was acquired from Divvy Tripdata. For this capstone project, I use data from January 2024 to October 2024 (10 months). I use R for combining and cleaning the dataset that contains a lot of rows (more than 5 million) which Spreadsheet cannot handle. The data has been made available by Motivate International Inc. under this License.The data can be found Here.
Guiding questions -
Where is your data located? How is the data organized?
Are there issues with bias or credibility in this data?
Does the data ROCCC? [Reliable, Original, Comprenhensive, Current and Cited]
How are you addressing licensing, privacy, security, and accessibility?
How did you verify the data’s integrity? How does it help you answer your question? Are there any problems with the data? data?
Key tasks
1.Download data and store it appropriately.
2.Identify how it’s organized.
3.Sort and filter the data.
4.Determine the credibility of the data.
This is an exploratory data analysis project done with R in Kaggle. The project requires us to do the following:
â—Ź Data Cleaning: Assessing Data Quality, Cleaning Data, Combining and Organizing Data, Creating New Variables
â—Ź Data Analysis and Visualization: Divvy Trip Trends analysis and visualization and creating charts and graphs Tebleua
â—Ź Recommendations for Future Analysis
Thank you !
Google Data Analytics Capstone: Complete a Case Study
The full project is posted on Kaggle
Tableau Dashboard - created a dashboard in Tableau summarizing the data. Tableua Dashboard
