Calculating Driver LTV from sample dataset
It is the value of a driver over the entire projected lifetime of that driver.
Calculating the lifetime value (LTV) of a typical Uber driver involves estimating the total revenue generated by the driver over the time they were active on the platform, minus the costs associated with acquiring and retaining that driver.
The raw data includes three datasets:
a) driver_ids.csv; contains the driver sign-up date
b) ride_ids.csv; contains trip details for every ride during the sample period
c) ride_timestamp_part_x.csv; this dataset is divided into three files and contains the timestamps at each stage of a ride, from a driver accepting the ride until the customer is dropped off.
To calculate the Total Revenue per Driver per Ride, we'll make a few assumptions:
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Base Fare: $2.00
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Cost per Mile: $1.15
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Cost per Minute: $0.22
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Service Fee: $1.75
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Minimum Fare: $5.00
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Maximum Fare: $400.00
In this repository I took three different approaches to estimate Driver LTV.
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