Bounce rate calculator
Enter what you sent and what came back. You get the rate and the band it falls in, measured against the thresholds mailbox providers respond to.
Hard and soft together, as your platform reports them.
Why 2% and 5% are the numbers
Neither figure is arbitrary, and neither is a rule a provider publishes as a rule. They are the levels at which behavior changes. Under 2%, a list looks maintained: addresses were checked or collected recently, and the few failures are ordinary churn.
Past 5%, you are telling every receiving provider that you mailed a list you had not cleaned. Sending repeatedly to addresses that do not exist is one of the clearest signals of a purchased or neglected list, and it is weighted accordingly.
The middle band is where most senders live. A list at 3% is not in trouble today, and it is losing about that much of its value per campaign. Address decay runs at roughly a fifth to a quarter of a B2B list each year as people change jobs, which is why a list left alone for eighteen months arrives at 5% on its own.
Your ESP has its own limits, usually stricter than the providers. Several suspend accounts above 5% on a single campaign, and some act at 3%. That is worth reading before you import anything large.
| Rate | What it says about the list | What to do |
|---|---|---|
| Under 2% | Maintained and recent | Nothing. Keep verifying before large sends |
| 2% to 5% | Drifting with age | Clean it, and check where the oldest addresses came from |
| Over 5% | Not verified before sending | Stop the campaign. Verify, then resume slowly |
| Over 10% | Purchased, scraped, or years old | Do not send this list. It will cost you the domain |
Lowering the rate without deleting the list
Start with the oldest addresses, because that is where the failures concentrate. An address collected four years ago is far more likely to be gone than one from last month, and segmenting by signup date usually finds the problem faster than verifying everything.
Then look at how the worst segment was collected. Typed at an event, imported from an old CRM, and typed into a form by the person themselves produce very different failure rates. The collection method is the cause; the bounce rate is the symptom.
Verification before the send catches what is already dead. It will not tell you which valid mailbox nobody reads, and there is no check that can. Engagement data answers that, and only your own sending produces it.
Questions people ask
My bounce rate jumped on one campaign. Why?
Usually a new source entered the list. Check whether the bounces cluster around a single import date or a single form. A block by one provider can also look like a bounce spike while nothing about the list changed.
Should I remove soft bounces?
Not on the first failure. A full mailbox or a busy server is temporary and the address is real. Most platforms suppress automatically after several consecutive soft bounces, which is the right moment.
Does a low bounce rate mean good deliverability?
No. Bounces are the mail that was refused outright. Mail accepted and filed in the spam folder counts as delivered, and that is invisible in this number.
How often should a list be verified?
Before any large send, and on a schedule for anything that sits unused. Quarterly suits most B2B lists, given how much of one goes stale in a year.
The rate is the symptom
Verification finds the addresses that will bounce before you send to them, and labels the ones nobody can settle instead of guessing.