I’ve been driving for Uber for over a month and also started started driving for Lyft almost two weeks ago.This past week I drove one full week of Uber and Lyft in Chicago (some rides took me out to the suburbs as well) pretty evenly and decided to compare my earnings. I didn’t do it in any specific way, I just drove around with both apps on while I waited to get a ride, and  when I got a ride, I would simply shut off the other app. I am driving while I wait to start a temp job next month.

The idea for breaking down the numbers happened when I looked at my weekly summaries from both companies today. I ended up driving 15 hours with Lyft and 16 with Uber by coincidence. I did not think I would find such interesting differences, I really thought Uber would be paying me a lot more than Lyft.


Initially, I sat down and compared the numbers that matter to drivers: mileage, hours, tips/surge, fees, and final payout. I specifically wanted to see how my earnings compare to each mile I put on my car and to each hour I am online.

Below you can see the breakdown of my driving income this week for each company.

  • The biggest differences can be seen in the miles I drove, the number of trips, and the fee collected by each company
  • The fee collected by Uber is more than twice the amount collected by Lyft
  • Lyft’s tip is twice the amount of the surge, (also, Uber takes 20% of the surge, while Lyft lets you keep all of the tips)
HOURS 16 15
MILES 99.4 158.5
TRIPS 20 29
FEE $42.11 $85.75
TIP/SURGE $32.00 $16.71
Cust PAID total $242.88 $276.16
TOTAL PAID to Driver $200.77 $190.41



Then, I broke the numbers down to see how much money I was making for each hour, mile, and trip I drove as an average. Judging from just this week, it seems that the hourly wage is pretty close for both, but Lyft is paying me more for each mile I put on my car.

Avg hourly wage $12.55 $12.69
Avg trip fare $10.04 $6.57
$ per mile driven $2.02 $1.20


After my initial analysis, I realized that these numbers don’t matter much to most consumers. Most consumers want to save money and get to places safely and quickly. Some consumers, however, do actually place value on the way a company distributes its wealth. So for those people I looked at the fees each company charges. First as a percentage of the total they charged consumers and my total driver pay, then as an average per trip.

Below you can see my findings and how much the fees differ between companies.

  • Uber is taking about 31% of what customers pay, While Lyft is only taking about 17%.
  • And when you compare the fees to how much a driver actually receives as pay, Uber’s fees stand at 45% and Lyft’s fees are about 21%
  • Lyft’s average fee per trip was $2.11, while Uber was $2.96
Fee as percentage of:
– Total Customer Paid 17.34% 31.05%
– Total paid to driver 20.97% 45.03%
Avg fee per trip $2.11 $2.96

Why do all of this? Well, the thing about this whole ride-share business, that can easily be forgotten when you tap your finger on your phone to request a ride, is that at the end of the day it doesn’t work if you don’t have drivers. And drivers have no need to be loyal to one company… They are in it for the dinero.

Which would you pick based on my numbers?


*Please note that these number are all real and I have my statements to back them up. Also, for those of you familiar with the rideshare business; I did not receive any incentives, guarantees, or bonuses from either company for this week’s pay.


After looking over the data for this particular week, I would be more inclined to drive for Lyft than for Uber, because they take less and pay me more per mile driven. Also, if I had driven all 31 hours with Lyft, I would have received an extra 10% – which would easily make my hourly wage with Lyft more than Uber.

I would also be more inclined to use Lyft when I need a ride.  Lyft charges less fees per ride and gives drivers a bigger chunk of the money collected.

I am going to try to drive for both this week as well (same method as last week) to see if there are any major differences and to have a bigger data set.