The project is about fictional company, Cyclistic. In 2016, Cyclistic launched a successful bike-share oering. Since then, the program has grown to a feet of 5,824 bicycles that are geotracked and locked into a network of 692 stations across Chicago. Until now, Cyclistic’s marketing strategy relied on building general awareness and appealing tobroad consumer segments.
The company wants to design marketing strategies aimed at converting casual riders into annual members and for this it needs to find out how do annual members and casual riders use Cyclistic bikes dierently.
This project uses R for Data Cleaning, Data Transformation and Data Visualisation
- The data contains 2059037 observations about Causal riders and 3660568 observations about member riders.
- The average ride length for casual riders is 28.25 mins and for member riders it is 12.53 mins which implies on average casual riders are travelling for longer distance
- Docked Bike is the least preferred ride type and is entirely used by casual members.
- Casual members prefer Electric bike over Classic Bike while member use both equally.
- June, July and August are the months with most no. of trips.
- Winter months of January, February and December witnessed the least no. of rides during the year for both the member types.
To encourage more people to become a member, the Cyclists can adopt some of the following strategies:
- Launch a point based reward system based on distance traveled for members.
- Casual riders use the services more on weekend for recreational and leisure activities so marketing schemes should be launched around areas like cafes, parks, community centres and theatres and offer group discounts.
- Increasing marketing activities in the top popular stations along with promotional offers.
- Devise a promotional scheme for winter months to help pickup low ridership during these months.
- Offering Discounted campaigns during weekdays to encourage more casual riders to use the service during the week