The Tangible Cost of Dead Miles
There is a category of mile that gig platforms will never acknowledge. It doesn’t appear on any order summary, generates no income, and leaves no trace except on your odometer and your fuel gauge. It is, in the most literal sense, dead — and it is quietly eating your margins.
I ran the numbers properly. Not estimates — actual logged data from every shift, every charge session, every expense. What I found was that two platforms with nearly identical average daily gross income are not remotely the same proposition once you look beneath the surface.
The first thing the data exposed was the mileage problem. Income per mile is the metric that actually matters for a driver, because miles are the unit of vehicle wear, fuel cost, and ultimately the finite lifespan of the asset you depend on. On food delivery, income per mile is compressed — not just because deliveries are short and dense, but because a significant portion of your mileage is dead mileage. Repositioning miles. Circling miles. Drive-to-a-better-zone miles. None of that appears on any order receipt. All of it appears on your odometer.
Switch to a block-based model and the structure changes entirely. You accept a fixed window for a guaranteed amount. The income is known before you leave the house. The route is loaded, the parcels are counted, and you execute. There is no waiting. There is no circling. The miles you drive are working miles.
Within that model, block type still matters. Not all blocks are equal. Amazon Flex offers two primary block types — Fresh, covering Amazon Fresh and grocery deliveries, and Logistics, covering standard parcel delivery. The income-per-mile spread between them is significant. Fresh blocks run roughly £1.20 to £1.80 per mile. Logistics blocks run £2.20 to £3.30. The gap exists for structural reasons: Fresh blocks carry a smaller parcel count, a heavier time penalty at the pickup location, and tighter delivery windows imposed by the refrigeration requirement. More constraints, less density, lower yield per mile. Logistics blocks load heavier, route more efficiently, and the mileage does more work. Understanding which block type to prioritise is its own edge, and the data makes it unambiguous.
But the income side is only half the picture. When I stopped food delivery, my insurance costs dropped over forty percent. The policy that covered food delivery was, by necessity, a commercial policy. The moment that requirement disappeared, so did a substantial fixed monthly expense. Charging costs fell by roughly sixty percent — not because I drive less, but because the daily top-up ritual ended. Food delivery demanded a full charge before every shift. Block delivery, with its more predictable mileage, allows a charging cadence of every two to three days. Thirty to forty minutes a day reclaimed, and the electricity bill cut by more than half.
When you adjust for expenses rather than comparing gross figures, the platforms that looked neck and neck on daily income diverge sharply. Lower gross, lower costs, better net. That is not a marginal difference. Over time it compounds into a categorically different financial position.
The lesson is not really about which app to work. It is about what you choose to measure and whether your data is honest enough to tell you something you didn’t already assume. I track all of this through GigFin, a small open-source tool I built specifically for gig workers who want their numbers to mean something — odometer readings, charge sessions, platform income, expenses, all of it in one place. Most gig workers are optimising for the number that feels like income. The number that actually matters is what remains after the vehicle, the insurance, and the time have all taken their share.
