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Recommended a driver’s lifetime value by developing predictive models and statistical analysis

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Lyft-Data-Challenge

Selected as 1 of 16 teams out of 302 teams to compete in the final round at Lyft HQ in San Francisco

Notes:

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Challenge FAQ

Prompt:

After exploring and analyzing the data, please:

  1. Recommend a Driver's Lifetime Value (i.e., the value of a driver to Lyft over the entire projected lifetime of a driver).
  2. Please answer the following questions:
    a. What are the main factors that affect a driver's lifetime value?
    b. What is the average projected lifetime of a driver? That is, once a driver is onboarded, how long do they typically continue driving with Lyft?
    c. Do all drivers act alike? Are there specific segments of drivers that generate more value for Lyft than the average driver?
    d. What actionable recommendations are there for the business?
  3. Prepare and submit a writeup of your findings for consumption by a cross-functional audience.

Challenge due September 15th, 2019!!

Contributers

  • Jacob Lebowitz
  • Tiger Gamble

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Recommended a driver’s lifetime value by developing predictive models and statistical analysis

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