Skip to content

AnupPainuly/Case_Study_Bike_Sharing

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 

Repository files navigation

Cyclistic Bike Sharing Capstone Project

Scenario

In 2016, Cyclistic launched a successful bike-share offering. Since then, the program has grown to a fleet of 5,824 bicycles that are geotracked 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 anytime. Until now, Cyclistic’s marketing strategy relied on building general awareness and appealing to broad consumer segments. One approach that helped make these things possible was the flexibility of its pricing plans: single-ride passes, full-day passes, and annual memberships. Customers who purchase single-ride or full-day passes are referred to as casual riders. Customers who purchase annual memberships are Cyclistic members. Cyclistic’s finance analysts have concluded that annual members are much more profitable than casual riders. Although the pricing flexibility helps Cyclistic attract more customers, Moreno believes that maximizing the number of annual members will be key to future growth. Rather than creating a marketing campaign that targets all-new customers, Moreno believes there is a very good chance to convert casual riders into members. She notes that casual riders are already aware of the Cyclistic program and have chosen Cyclistic for their mobility needs.

Business Task

Anlayse the usage the trends of all the members using the service for conversion of membership Program.

Conclusions

The total trip duration for casual riders and annual members are affected by the season. The temperature is very low during the winter season, fewer people are willing to go out and people who need to travel daily for work will choose to take other public transport, this had caused the total trip duration are the lowest among another season. Over the years, we see a significant divergence of total trip duration from May to September for two groups of users. This has shown their usage pattern significantly due to their preference and it is more clear when we look into total trip duration on every single hour within the day.

**Relevant links and citations

Please refer Here for viewing the insights in Tableau and Here for Programing (R) code.

The data has been made available by Motivate International Inc. under this license.