What Delivery Gig Pay Looks Like in a Mid-Size City

I drove for three delivery apps over four months in my mid-size city — population a little under 300,000, so not a dense urban market but not rural either — and logged every shift: hours online, orders completed, total pay including tips, and miles driven according to my car's trip odometer. I did this because every number I'd seen online for delivery pay was either from a huge metro area or didn't account for gas and mileage at all, and I wanted a number that applied to where I actually live.

The short version: the apps' own per-order pay estimates were consistently higher than what I actually cleared after gas, and significantly higher after accounting for the wear on the car, which most people — myself included, for the first month — don't factor in at all.

Here's the breakdown, broken into "before expenses" (what hit my bank account) and "after expenses" (after gas and a standard per-mile wear estimate, which I used the current IRS standard mileage rate to calculate, since that's a reasonable stand-in for wear and depreciation even though I'm not claiming a tax deduction with it here).

The pay table: three apps, four months

The gap between "before expenses" and "after expenses" ranged from about 27% to 30% across all three apps — meaning roughly a quarter to a third of the pay number shown in the app isn't actually yours once a mile-driven cost is applied.

Running multiple apps at once

I ran DashFleet and CourierPing simultaneously for about half the test period — accepting whichever order came in first — which bumped my effective hourly rate by roughly 12% compared to single-app shifts during the same time blocks, mostly by cutting down on dead time between orders. The trade-off is logistics: toggling between two apps' availability and tracking which app you're "on" for tax and mileage purposes gets genuinely annoying, and I wouldn't recommend it to someone just starting out.

What the apps don't tell you upfront

None of the three apps show an hourly rate anywhere in their interface — they all show per-order estimated pay, which makes it hard to tell in the moment whether a slow night is actually slow or just feels that way. I started using a simple timer to log online-time vs. order-time specifically because the apps don't surface this, and it's the only reason I have real hourly numbers at all rather than a gut feeling.

Is it worth it in a market this size

At $12–16/hour after expenses during normal hours, and $20+/hour during the best peak-bonus windows, this isn't a replacement for a full-time job in my market, but it's a reasonable flexible supplement if you already have a reliable car and can work the specific high-demand windows (weekend dinner rushes, weekday lunch) rather than spreading hours evenly across the week. Spreading your hours evenly, which is what I did by accident in month one before I started tracking peak windows, is the single easiest way to underperform these numbers.

One more factor specific to a mid-size market: trip length. In my city, orders tended to be spread farther apart than the dense-urban numbers I'd read about online, which meant more time and mileage between drop-offs and fewer dense multi-order "batches" than drivers in bigger cities described. If you're in a similarly spread-out market, I'd expect your numbers to land closer to mine than to the larger-city figures often cited in broader coverage of this kind of work.

The car question nobody asks early enough

I didn't seriously think about mileage wear until a mechanic pointed out my brake pads were wearing faster than expected for my total annual mileage — delivery driving is disproportionately stop-and-go, which is harder on brakes and tires than highway miles. If you're considering this, I'd budget for brake and tire replacement on a shorter interval than your car's manual suggests, and build that into your real hourly math from day one rather than finding out at 40,000 miles like I did.

Insurance and taxes, briefly

My personal auto insurance policy excludes commercial delivery use, which I confirmed with my insurer before starting this test — most standard personal policies do. Two of the three apps offer limited supplemental coverage while you're actively on a delivery, but none covered the gap between deliveries while you're online and available. I added a rideshare/delivery endorsement to my existing policy for about $9/month, which I've folded into the "after expenses" numbers above as a fixed cost divided across my logged hours. On taxes, all three apps issue a 1099 if you cross their reporting threshold, and the standard mileage deduction at tax time is separate from — and generally more generous than — the per-mile wear estimate I used above for the hourly-rate math in this post.

How much the season matters

My four months of tracking spanned a slower summer stretch and the start of a busier fall season, and the difference was larger than I expected going in: my best month averaged about 18% higher pay-per-hour than my slowest month, almost entirely driven by more frequent peak-time bonuses rather than more orders overall. If you're trying to decide when to start, the run-up to a holiday season in a market like mine seems to meaningfully outperform a random week in midsummer — worth knowing before you judge your first few shifts against the numbers in this post.

If I were starting over, I'd track my numbers from day one rather than waiting a month in, and I'd pick two apps to run together immediately instead of testing them one at a time — both changes would have gotten me to a real, trustworthy hourly figure faster, and faster numbers would have let me adjust which time blocks I worked much sooner.

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