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Pedal to Our Casual Base

Analyzing Cyclistic Casual vs. Member User Trends

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Scope of this Report & Business Task

This report provides a comprehensive comparative analysis, offering valuable insights into the distinct usage patterns of members versus casual riders. The primary objective is to empower our marketing team with data-driven insights to identify casual riders who are most likely to convert to annual memberships, and develop a targeted campaign to drive growth in this highly profitable user segment.

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Overview

  • Overview of our Dataset & Key Metrics
  • The Picture the Data Paints
  • In-Depth Comparison: Our Casual Riders vs. Members
  • Summary of Insights
  • Strategic Recommendations

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Overview of the Dataset and Key Metrics

  • This analysis draws on data from over 140,000 Cyclistic bike rides taken by members and casual users across the Chicago service area in January 2024.
  • Sourced from Cyclistic’s Amazon AWS repository, the data is stored in monthly and quarterly CSV files.
  • Customer data is limited to membership status, while ride data includes bike type (Classic or E-bike), start and end stations, GPS coordinates, and timestamps.

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Data Metrics

  • Ride Volume (Daily and Hourly)
  • Mean Ride Duration
  • Ride-Type Preference
  • Station Preference
  • Geographic Distribution
  • Weekly Distribution
  • Hourly Distribution

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  • Users ride more on weekdays than weekends
  • Users prefer classic bikes over e-bikes
  • Users typically keep to roughly 7 minute rides (median length)
  • Users tend to ride our bikes during peak commuting hours

Overall Picture the Data Paints

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The data revealed that our customers take rides much more often on weekdays. Customers tended to use Classic bikes more than E-bikes generally, but E-bikes accounted for an increasing proportion of total rides as the weekends approached.

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This data aggregation Illustrated how our customers overwhelmingly took rides during commuting hours around 8AM and 5PM.

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Ride duration through much of the week was stable, but with a notable dip on Fridays and a significant increase in duration on saturdays. E-bike rides were generally shorter than Classic Bike rides.

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Two large humps in the data showcase how ride duration spiked at commute hours. The unexpected spikes observed at 2 AM and 4 AM were possibly due to the collection of abandoned rides around these hours, and the New Year's Eve celebrations on January 1st.

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Customer activity was concentrated to a small subset of our stations. Out of a total of 996 stations, the top 20% accounted for over 70% of all rides.

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What This Tells Us

  • In summary we can see that users are by and large using the service as a commuting transportation solution
  • Customers take many more rides during weekdays, and tend to use the classic bike type.
  • Towards weekends, ride volume drops considerably, but there is an increase in leisure rides; Ride duration lengthens and E-bikes make up a larger proportion of total rides.
  • A minority of top stations a disproportionately large percentage of the time, indicating certain geographical hotspots where bikes are desired methods of transport.

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In-Depth Comparison: Our Casual Riders Vs. Members

Basic Characteristics, Weekly Patterns, Daily Patterns

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Basic Characteristics

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Casual users took significantly fewer rides than members, with member rides representing over 83% of the dataset. However, it is important to note that this dataset does not provide insight into the proportion of customers who are members versus casual users.

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Members prefer Classic Bikes nearly as much as Casual users prefer E-Bikes.

Member and Casual Preference:

E-Bikes Vs. Classic Bikes

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Casual riders took longer rides while Members took shorter rides. E-bike Rides are consistently shorter than Classic rides.

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Overall Station Preference

The top 10 stations for casual users and members comprised nearly 10% of total ride volume for the set. The top four stations for both segments had a much larger number of rides than the other stations.

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Weekly Patterns

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Proportionally, ride volume throughout the week between both segments closely mirrored each other. The most rides for both segments were on Wednesdays and Thursdays, with the fewest on Saturdays and Sundays.

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We can see Members greatly prefer Classic Bikes on weekdays but are a lot more likely to ride an E-bike over the weekend. Casual riders by comparison generally favored E-bikes with equal vigor each day of the week.

Ride Volume over the Week by Ride Type, Casual Vs. Member

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Both casuals and members took longer rides on weekends, with the longest ride times on Saturdays and the shortest on Wednesdays and Thursdays.

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Daily Patterns

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Member rides spike sharply during commuting hours. Casual rides also spike at these hours but this is less pronounced, and an arch in daily activity is more apparent in their graph.

Ride Volume by Time of Day, Member Vs. Casual

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Casual users are consistently taking longer rides through all hours of the day, except for during morning commute hours.

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Ride-Type Preference By Time of Day, Member Vs. Casual

Casual users always preferred E-bikes more throughout the day, while members actually preferred E-bikes over Classic bikes during late night and early morning hours.

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IN SUMMARY

The data shows that Members are typically using the service for utilitarian purposes as a means of commute.

Casual seem to be split as using the service for leisure rides and those who use it as a temporary transportation solution.

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TOP 3 RECOMMENDATIONS

  • Identify the top stations with consistently high usage of classic bikes during peak commute hours by casual users. This may suggest that these users could benefit more from a membership.
  • Create a targeted marketing campaign to promote memberships at these high-traffic stations.
  • Consider surveying casual users at these locations to better understand why they choose to use the service on a casual basis and what might encourage them to become members.