Five tools · four free

Small tools for people who run shops

Each one answers a single question from a file you already have. No account, no email, no trial.

Turn your internet off and try them. This page is blocked from making any requests. Your file stays in your browser.

Stockout Cost

Finds the days each SKU went unusually quiet against its own weekday pattern, and prices them.

NEEDS date · SKU · quantity
Open the calculator →

Inventory Turnover

Days of cover for every SKU, and the number it cannot compute from these files rather than a ratio that looks like it.

NEEDS orders · SKU · units on hand
Open the calculator →

Reorder Point free to use and to read

The formula written out in full, with the three cases where it is confidently wrong.

NO FILE NEEDED
Work out your reorder point →

Free Shipping Threshold

Shows the shipping revenue you would give up, and the break-even it would have to clear.

NEEDS order value · shipping charged
Work out your threshold →

List Diet

Splits your contact count into what is provably unreachable and what needs your judgement.

NEEDS an email column
Open List Diet →
The one that costs money

Reorder Copilot

Does the reorder arithmetic for your whole catalogue every week and writes the purchase order. The formula and the calculator on that page stay free. This is for the week you stop doing it by hand.

Price
$49once

not per month. There is no server behind it, so charging monthly would be charging for nothing

It runs over your whole catalogue every week, with the same exclusions the free tools use, so no order quantity for a discontinued line, none for a SKU with less history than its lead time.

Read the formula first, then decide →

Refuses

These under-report on purpose

All of them would be easy to make more impressive. The stockout calculator could put a number on every slow-moving SKU instead of excluding them; List Diet could mark "never opened" as safe to delete and show you a much larger saving; the free-shipping page could print "set it to $75" and a revenue forecast to go with it.

All of them would be wrong, and the cost of being wrong lands on you, in a purchase order for stock you did not need, a suppression list that quietly removes customers who were buying but never opening, or a shipping rule set from a forecast nobody could have made. So where the data genuinely cannot answer a question, these say so instead of guessing, and the totals come out lower than a less careful tool would show you.

If you find a number that looks wrong, please tell me what your data looked like. I would rather fix it than have someone act on it.

The measurements behind that

Two write-ups of what went wrong while building these, with the numbers. Both are reproducible from the measurement scripts they name.

All notes →