Differences in Bike Usage

Assignment

This is a case study project for the Google Data Analytics Certification Course on Coursera. For this project, I was assigned the role of junior data analyst for Cyclistic, a fictional bike-sharing company. My job was to figure out how casual riders (customers) and annual members (subscribers) use the company's bike-sharing services differently. The goal was to use the insights from this project to decide how to increase the number of subscribers, who are more profitable than customers.

At the start, I received fictional data split across the four quarters of 2019 supplied to me by the certification course. Using Microsoft Excel and SQL, I was able to create complete datasets that had consistent data types, enabling me to pinpoint differences regarding how customers and subscribers use Cyclistic’s bikes differently. I explored differences based on location, trip duration, and the total number of trips. From there, I gained insights on what factors may affect the decision to subscribe to a bike-sharing service.

Findings

Across all four quarters, the most popular start and end locations for each user type remained consistent. Customers favor outdoor parks and entertainment centers. Subscribers are drawn primarily to business-related locations. This may indicate that customers use the bikes for leisure, and subscribers use them for daily activities such as work commutes.

Customers' most popular start stations

Streeter Dr & Grand Ave

Lake Shore Dr

Monroe St Shedd Aquarium


Customers' most popular end stations

Streeter Dr & Grand Ave

Lake Shore Dr & Monroe St

Millennium Park

Subscribers' most popular start stations

Canal St & Adams St

Clinton St & Washington Blvd

Clinton St & Madison St


Subscribers' most popular end stations

Clinton St & Washington Blvd

Canal St & Adams St

Clinton St & Madison St

Customers have significantly longer rides than subscribers by approximately 53 minutes on average. Longer durations indicate a significant event on Tuesday that interests customers. If it’s a recurring event, that may be an opportunity to convert some of these customers to subscribers.

Despite riding for shorter timeframes, subscribers take 78% of total trips. They make 3.6x more trips than customers, which suggests that Cyclistic’s bikes are a predominant mode of transportation for subscribers. Customers’ less frequent use suggests that they view the bikes as something to use for an outdoor trip or a special occasion.

Recommendations

Using these insights as guidance, I developed three recommendations for Cyclistic's marketing plan to increase subscribers.

  1. Offer a tiered subscription option to customers where they can pay a discounted price for less frequent use.

  2. Promote subscriptions on Tuesdays and at popular leisure destinations, bringing this option to the top of customers' minds when they consider travel options regarding bikes.

  3. Market bikes as a work commute alternative to driving or public transportation.

View the presentation slides here.

Data Sources Cited

DIVVY, & Lyft Bikes and Scooters, LLC. (2019). Divvy 2019 Q1 [Public data set]. 

Divvy_Trips_2019_Q1.zip.

DIVVY, & Lyft Bikes and Scooters, LLC. (2019). Divvy 2019 Q2 [Public data set]. 

Divvy_Trips_2019_Q2.zip.

DIVVY, & Lyft Bikes and Scooters, LLC. (2019). Divvy 2019 Q3 [Public data set]. 

Divvy_Trips_2019_Q3.zip.

DIVVY, & Lyft Bikes and Scooters, LLC. (2019). Divvy 2019 Q4 [Public data set]. 

Divvy_Trips_2019_Q4.zip.

License to use cited data provided by Motivate International, Inc.

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