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(CASE STUDY)

Presented by: Zafer Ozdemir

06/07/2022

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CASE STUDY SENARIO

Scenario You are a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. The director of marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore, your team wants to understand how casual riders and annual members use Cyclistic bikes differently. From these insights, your team will design a new marketing strategy to convert casual riders into annual members. But first, Cyclistic executives must approve your recommendations, so they must be backed up with compelling data insights and professional data visualizations.

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STAKEHOLDERS

  • Lily Moreno: The director of marketing and your manager
  • Cyclistic marketing analytics team: A team of data analysts who are responsible for collecting, analyzing, and reporting data that helps guide Cyclistic marketing strategy
  • Cyclistic executive team: The notoriously detail-oriented executive team will decide whether to approve the recommended marketing program.

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BUSINESS

TASK

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How do annual members and casual riders use Cyclistic bikes differently?

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Average ride for Member_casual

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Average ride for casual is 32 minutes.

Average ride for member is 13 minutes.

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Max ride for Member_casual

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932 hours for casual users as well as for member

user is an outlier

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​

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The time spent by the member users are statics and

uniformly distributed

Casual users are the highest on saturday and sunday

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​

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  • More users are riding in weekdays by member users.
  • More users are riding in weekends by casual users.

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  • Casual users have peak on summer time.
  • Member users have high too on summer include september and october.

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KEY

FINDINGS

  • Our casual customers take the most rides on the weekends. Conversely, our members take the most rides during the week.
  • On average, our members take shorter rides than our casual customers.
  • Both members and casual customers ride more frequently in the summer months and the least frequently in the late winter and early spring.

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RECOMMENDATIONS

  • Advertise how a membership can save money for those customers who tend to take longer rides
  • Target casual customers who rent a bike for leisure on their weekends
  • Create a large summer campaign when more people are likely to rent a bike

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