Cyclistic Bike Share project

Overview

In this case project I'll be working with a fictional company called Cyclistic as a Junior Data Analyst. Cyclistic is a bike sharing company in Chicago. They offer a bike share program that features more than 5800 bikes 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 them to commute to work each day.

Objective

The business task here is to understand how casual riders and annual members use Cyclistic bikes differently which will be used to design a new marketing strategy to convert casual riders into annual members.

Relevant Stakeholders

In this project, I'll be working with a few stakeholders:

• Lily Moreno: She is my manager and the director of marketing. She is responsible for the development of campaigns and initiative to promote the bike share program.
• Cyclistic Executive team: They will be responsible on deciding whether to approve the recommended marketing program.
• Cyclistic marketing analytics team: They are a team of data analysts who are responsible for collecting, analyzing, and reporting data that helps guide Cyclistic marketing strategy.

Technologies used

R was the main technology used for the project. Before working with the datasets, I had to load some libraries that would be used in the analysis. The libraries are Tidyverse for data analysis, readr for loading the datasets, ggplot2 for visualization and lubridate package for working with dates.

Datasets

The datasets where all sourced from kaggle

conclusion

• Casual riders make more use of docked bike than bike share members who makes more use of classic bikes.
• Highest activity during summer - Casual and member riders are seen to be more active between July and September
• From the analysis above, casual riders are seen to be very active during the weekends (Saturday and Sunday) indicating that they probably use this service for leisure.It can also be inferred that members activities, to a noticeable extent are fairly distributed across the week without sudden pikes indicating that they might be using the bike share service as a means of transportation to work on a daily basis although we'll need more data to support this proposition.
• Casual and member riders were obbserved using the service more in the evening period.
• members usertype frequency is just a third of casual usertypes frequency.

Recommendatiom

• Discounts should be given on weekends to casual riders when they use the bike share service most.

• Ads could also be created outlining the benefits of resorting to using bikes to commute to work on a daily basis - like how it is a form of exercise and helps maintain good health and also how it contributes to maintaining a green environment.

• Since more of the casual riders make more use of docked bikes, plans on getting more docked bikes in place should be considered.