What 4 makers on MakerMap learned about it, in their own words: their best posts on X, filed under Pricing & revenue.
Building pricing where founders only pay for the customers we actually save. Sounds simple.
Then the edge cases show up. What if the saved customer disputes the charge next week?
What if the payment reverses? So every save gets a receipt, and if it reverses, the fee goes back.
I'm running a pricing experiment I've never tried before: early-bird batches instead of one fixed price.
ZipIt started at $9 lifetime. Once a batch sells, price steps up. $15, then $19, then $25.
Right now it's sitting at $25 with 15 spots left before it jumps to $49.
Nervous about it. Part of me wants to just pick one number and be done.
But watching people pay less because they showed up earlier feels like the right incentive, and it's forcing me to actually ship instead of sitting on a "perfect" price forever.
Next test: does the urgency fade once it hits $49,
or does it get more interesting?
If you add 20% to your costs, you’re NOT making 20%. 💸
$10,000 job + 20% markup = $12,000 bid
Profit: $2,000 ÷ $12,000 = 16.7% margin
…and that still has to cover the truck, insurance and phone bill.
Measure any lot from satellite ⬇️ ⬇️
👉
New on Dorman Review 📌
Your AI startup can grow 10x and still go broke.
Charge $0.10. Spend $0.03. Keep $0.07.
Add retries. Spend $0.09. Keep $0.01.
Usage up. Business down.
The pricing model behind every AI product, explained simply ⬇️