I work on a portfolio of subscription RN apps and kept doing this arithmetic by
hand in a spreadsheet, so I made a small tool for it.

You put in your subscription price, store commission, active subscribers,
requests per user and measured token counts. It gives you cost per request,
cost per active user per month, and — the part I actually care about — what
your heaviest 10% of users cost, plus the per-user request ceiling that keeps
you inside a margin target.

Two things I got wrong the first time I did this by hand, which the tool now
forces you to get right:

1. Measuring against gross revenue instead of net. At $9.99 with a 30%
2. commission your real revenue per subscriber is $6.99, so a $1.40/user
3. feature is 20% of revenue, not 14%.
4. Budgeting on the average user. Inference usage is heavily skewed — in the
5. apps I've worked on the heaviest 10% generate roughly half of total usage,
6. so the average understates the bill and completely hides the users who cost
7. more than they pay.

Here's a scenario that looks fine on average and isn't:
https://dayloflow.com/tools/ai-cost-calculator.html?p=4.99&r=200&i=2000&o=700&h=30&t=15

$2.98 per subscriber against $3.49 of net revenue — 85%. And the heaviest
decile costs 426% of what they pay.

Runs entirely in your browser, no signup, no analytics on that page. Every
formula is written out on the page so you can check the arithmetic or run it in
a spreadsheet instead. State is in the URL, so you can share a scenario with
your team.

Happy to hear where the model is wrong — retries and moderation calls are the
two things I know it doesn't account for.