This project analyzed a dataset of the CitiBike brand bike-sharing service in New York City, in order to support a business proposal for a potential new bike-sharing company.
The results of the analysis are shown below with graphics for each of five assessments of the bike-sharing service. The dataset was isolated to the August 2019 time periods for all CitiBike activities in the New York City Manhattan region.
The following public link contains the resultant graphics of each assesment. (https://public.tableau.com/app/profile/damon7164)
A majority of bikes are checked out for less than an hour at a time, with most rides lasting approximately 5-15 minutes.
A majority of bikes are checked out by male riders, around 70%.
Rides increase during weekday commuting hours (6am-9am and 4pm-8pm), and are heavy from 10-5 PM during weekends. Wednesdays are typically lower use after 9AM for the remainder of the day.
Male subscribers represent the greatest rider demographic each day of the week. Female riders have a similar pattern with reduced volume.
Male and female riders share similar trends when checking out bikes based on day/time.
The following high-level results of the assessment with suggestions are listed below.
- The majroity of rides are 5 to 20 minutes in length.
- Female rides are longer in length (8-30 minutes) and this suggests a higher per rider revenue.
- A majority of riders are male and that most of the riders are annual subscribers
- Peak ridership trends during the AM and PM weekday communiting periods.
- Wednesday ridership is lower all day, especialy after 9AM.
Based on these assessments and findings, the the following suggestions should be considered key decision support points:
- There is a large number or rides under 5 minutes which should be investigated further and adjustments determined.
- Increasing female rides which trend longer in ride time, could help increase revenue with more longer bookings.
- Offer incentives on subscritions to increase the overall rate and widen the gender coverage.
Recommended Additional Visualizations:
- Compare the number of trips bewteen different months to understand how ridership changes seasonally.
- Detailed trip locations assessments to show gaps in availability and to balance usage.