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The Deliverability Cost Calculator.

Two numbers you already have — monthly sends and delivery rate — and one you should: what a delivered message is worth. Out comes the invisible line of your P&L: how many messages simply never arrive, what that costs a month, and what fixing delivery to 95%+ would recover.

Try a shape:

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Never arrive, per month

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Delivered, per month

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Recoverable at a 95% rate

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All math runs in your browser — nothing is sent anywhere.

How to read this

This is a formula, not a benchmark: your sends, your delivery rate, your message value — your answer. The reason to run it at all is that deliverability is the quietest metric in the stack. It degrades one polite percentage point at a time, nobody owns it, and every percentage point is a slice of revenue that never gets the chance to exist.

The «Uber Eats shape» preset uses the public numbers from a real case: two million messages a month running at ~84% — one in six simply gone. The value inputs stay yours; that case's answer was measured in raw delivery logs, and the defect turned out to be the platform, not the list.

One honest caveat: this tool measures delivery rate — what the receiving server accepted. Inbox placement (inbox vs spam) sits on top of it and needs seed tests. If delivery is already low, placement is your second problem.

Questions this tool gets asked

What is a good email deliverability rate?
95%+ delivered is the working bar for a healthy program; the strongest senders run 98%+. Anything under ~90% is no longer a hygiene issue — it is a structural defect somewhere in the platform, authentication, or list, and it compounds monthly.
Delivery rate vs deliverability vs inbox placement — what does this tool measure?
Delivery rate is the share of sends accepted by the receiving server — the number in your platform's logs, and the one this calculator uses. Inbox placement (inbox vs spam folder) sits on top of it and needs seed-list tests to measure. If your delivery rate is already low, placement is the second problem, not the first.
Why did my deliverability drop?
Three usual suspects, in the order teams check them — and the reverse order of how often they're guilty: list hygiene, sender reputation, and platform configuration. Platform-level defects are the least checked and the most expensive: at Uber Eats scale, one config defect held global delivery at ~84% while every dashboard blamed reputation.
How do I fix a low delivery rate?
Measure from raw delivery logs (not the campaign dashboard), verify SPF/DKIM/DMARC, then trace the failure pattern: if it doesn't follow list age or segment, stop cleaning the list and audit the platform. Fix the root cause once — subject-line work on top of a broken platform is cosmetics.
How much does poor deliverability cost?
This calculator's formula: monthly sends × (target rate − current rate) × value per delivered message. The point is not precision — it's that the number is rarely small, and it repeats every month until the defect is found.

The case behind the preset: 84% → 95%+ at Uber Eats scale → Why opens won't warn you — Read behavior, not opens →

Want the real number, from your real logs?

Deliverability is where I start every audit — measured in raw delivery logs, not dashboard vanity. The Teardown finds your top leaks in five working days, async, no calls.

Start with the €600 Teardown or book a 30-min fit call