Drop in your orders export. For each candidate minimum this shows the shipping revenue you would give up — measured from what you actually collected — and the break-even it would have to clear. It does not tell you the number to pick, because the thing that decides it is not in your file.
Try the sample now, or open this page on a computer with your CSV export.
Don't have a CSV to hand right now? See it run on sample data first →
No shipping column, no report. The cost side is measured from carriage you actually collected. It is never estimated, and neither is the near-miss band.
If your file was produced under a free-shipping rule you already run, every row is refused — not only the rows above your line, because the orders that would have landed just under it are sitting above it instead.
What comes back is a break-even, not a forecast. The channel these lines actually work through — carts that get abandoned less often — is not in an orders export at all, so nothing here is a verdict on the threshold itself.
| Threshold | Orders already over it | Shipping given up / 30 days | Near-miss orders | Typical top-up | Break-even top-up rate | or extra orders |
|---|
No recommended row, and nothing here is highlighted. The rows are in threshold order, not preference order. What decides which line is right for you is whether your customers top up rather than abandon, and an orders export contains only the carts that converted — so that evidence is not in this file and this page will not pretend it is.
The two hurdle columns are alternatives, not a total: some of the gap can be closed by near-miss orders topping up and the rest by extra orders, in any mix. A top-up alone result is a finding about that one channel and says nothing about whether the threshold is a good idea — the channel this page cannot see, extra orders from a better checkout, is the one that usually carries a free-shipping line. Whether either happens is a judgement about your customers, and this file contains no evidence about it.
This page is about carriage you choose to absorb. Reorder Copilot takes the same orders export, plus your stock levels and supplier lead time, and returns how much to order this week — and refuses the SKUs it cannot size rather than guessing at them.
For a candidate threshold T, with your margin m:
The usual advice is to set the threshold 15–30% above your average order value. That is wrong twice over, and both failures are the reason this page is shaped the way it is.
A free-shipping rule leaves an exact fingerprint that has nothing to do with guesswork: orders above the line stop paying carriage. So the check looks for the order value that best splits your file into "almost always paid shipping" below and "almost never paid shipping" above. If it finds one, this page will not rank thresholds, because every figure it could produce would be a reading of your current policy.
The obvious alternative — looking for a spike in the order-value histogram just above a round number — was built, measured against a store with a known $50 rule and a store with none, and thrown away. It ranked $85 as the strongest "threshold" in both files and never found the real $50 one. Order values pile up at sums of your own product prices, so a catalogue with an $89 item and a $56 item makes lumps that look exactly like a threshold. A detector that fires on a shop with no rule at all is worse than no detector: it would grey out a real answer.
A near-miss order only earns its keep if the margin on what it adds beats the carriage it was already paying you: top-up × margin > carriage charged. That is a low bar for a shop with fat margins and cheap postage and an impossible one for a shop with the reverse, and the exact figure for your shop is printed next to the sliders above rather than approximated here.
How often it bites was measured rather than asserted, by sweeping order value, carriage, margin and band width — 256 combinations. Some threshold has a positive top-up gain in 75% of them, and the stronger claim that top-ups alone could cover the entire cost holds in 57%. So this is a real effect and not a universal one; a shop with a small average order, thin margins and expensive postage sits on the wrong side of it, and that is the shop that sees top-up alone: never on every row.
None of that says a threshold is a bad idea for such a shop. It says the basket-size story is not what would pay for it, and the other story — a checkout people abandon less often — is the one this page is structurally blind to, because an orders export contains only the carts that converted.
Treat this as a way of finding out what you would be betting, not as a recommendation. Nothing on this page knows your customers.
More on why it is built this way: every free-shipping threshold calculator invents one number, and ours did too — the sweep behind the measured band, and the algebraic correction that turned out to make the prediction worse.
This page is about money you would give away on purpose. The same export also holds the money that left without anyone deciding — the days a SKU went quiet because it had run out.
Stockout Cost — same file →