An Analysis of Divvy Bikeshare Data
An Analysis of Divvy Bikeshare Data
Examining unique behaviors of Divvy bikeshare riders. Discovering correlations and patterns. Turning that into actionable insight.
Examining unique behaviors of Divvy bikeshare riders. Discovering correlations and patterns. Turning that into actionable insight.
Utilizing R studio and R markdown, I cleaned, manipulated, and analyzed twelve months of Divvy bikeshare data to discover unique behaviors among their riders. The ultimate goal was to make recommendations on how to convert casual riders to purchase annual memberships.
My analysis covers January 2021 - December 2021 and focuses on distinguishing behaviors between riders that hold a membership and casual riders. The data was analyzed by a number of factors including, time of day, day of week, and ride length.
Using the insights derived from the analysis , I made recommendations for how to target casual riders and incentivize them into purchasing annual memberships.
