Email Open Rate Calculator — Reported and MPP-Adjusted

Background.

Email open rate is unique opens divided by emails delivered. Two independent platforms define it identically: Mailchimp calls it "a percentage that tells you how many successfully delivered emails were opened by recipients," with successful deliveries being "the number of recipients who didn't hard or soft bounce"; HubSpot calls it the "percentage of recipients who opened the email out of the number who received it." So the arithmetic is settled. What is not settled is whether the numerator means anything.

Open tracking works by embedding a tiny remote image and counting requests for it. HubSpot states the mechanism plainly: "An email open is counted when the images in the email load, or when a recipient clicks on a link in the email." That worked tolerably until Apple shipped Mail Privacy Protection in September 2021. Apple's own privacy documentation describes what it does: Mail "downloads remote content in the background by default — regardless of whether you engage with the email," and routes those requests "through two separate relays operated by different entities." A protected recipient therefore registers an open without reading anything, and does so at a time and from an IP address that tell you nothing. Mailchimp says the consequence in one sentence: "Bot activity such as Apple's Mail Privacy Protection (MPP) can falsely inflate open and click metrics."

This calculator does not pretend that away and it does not guess your way out of it either. It bakes in no assumption about how common machine opens are, because no authority publishes a defensible universal figure and your share depends entirely on how much of your list is on Apple Mail. You supply the machine-open count from your own platform's bot-filtering report, and the page then gives you three readings of the same send. The reported rate is what your dashboard shows, machines included — an upper bound. The lower bound removes machine opens from the numerator while leaving every recipient in the denominator; it is guaranteed too low, because protected recipients who genuinely did open have been discarded along with the machines. The observable-audience rate removes those recipients from both sides, assuming one machine open per protected recipient, and is the closest thing to a figure comparable with your pre-2021 numbers.

On the worked example — 120,000 sent, 3,600 bounced, 116,400 delivered, 52,800 unique opens of which 29,040 were machines — those three readings are 45.36%, 20.41% and 27.20%. A dashboard reporting 45% is describing a send where roughly a quarter of observable recipients opened. The reported figure is not a small overstatement; it is nearly 1.7 times the honest estimate. Note the ordering, which is forced by the arithmetic rather than chosen: the lower bound always sits below the observable-audience rate, and the observable-audience rate can never exceed the reported rate. They coincide only when every delivered email was opened, or when there were no machine opens at all.

One more reconciliation the page handles quietly. Some tools divide by emails sent rather than emails delivered. The two differ by exactly the delivery rate: open rate on sent = open rate on delivered × delivery rate, because (U ÷ D) × (D ÷ Sent) cancels to U ÷ Sent. In the worked example the delivered-based 45.3608247423% and the delivery rate of 97% give exactly 44%, and both figures are shown so a discrepancy with another tool can be diagnosed rather than argued about. The practical conclusion of all of this: open rate stopped being a performance metric in September 2021 and became a deliverability diagnostic. Judge campaigns on clicks and conversions; use this page to understand what the open number is actually made of.

What is email open rate calculator?

Open rate is the share of delivered emails that registered at least one open. The numerator is unique opens — recipients who opened at least once, not total opens, which counts repeat views by the same person. The denominator is delivered, defined as emails sent minus hard and soft bounces. Both major platforms consulted here define it that way, so the page uses delivered throughout and reports the sent-based variant separately for reconciliation. An open is recorded when a remote tracking image loads, or when a link in the message is clicked; the click fallback exists because recipients who block images would otherwise never register. That mechanism has two failure modes pointing in opposite directions. It undercounts anyone who reads the message in a plain-text or image-blocking client without clicking. Since September 2021 it also massively overcounts anyone using Apple Mail with Mail Privacy Protection enabled, because Apple pre-fetches remote content for every message regardless of whether the recipient ever opens it. Neither failure is a bug in the calculation — the arithmetic is one division — and neither can be fixed by choosing a different formula. What can be done is what this page does: state which opens are machine opens, and show the rate with and without them. There is no standards body for email metrics and no audited definition; the platforms' own documentation is the authority, and where two platforms agree, as they do here, that agreement is the strongest evidence available.

How to use this calculator.

1. 01Pull four numbers for the same send: emails sent, bounces, unique opens, and machine or bot-filtered opens.
2. 02Use UNIQUE opens, not total opens. If your unique-open figure exceeds the emails delivered, you are looking at total opens and the calculator will reject it.
3. 03Get the machine-open count from your platform's own bot-filtering or Apple-MPP report. If your platform does not break it out, enter 0 and read the reported figure as an upper bound — the page will not invent a number for you.
4. 04Pick the headline you need. Reported is what to quote when comparing with your own dashboard; observable audience is what to quote when comparing with anything from before September 2021.
5. 05Read the share-of-opens-that-were-machines output first. It tells you how much of the headline to believe before you look at the headline.
6. 06Check the bounce rate. If open rate fell and bounce rate rose in the same period, the story is deliverability, not creative.
7. 07If another tool disagrees with your open rate, compare against the 'if you divide by sent' output — that convention difference explains a gap of exactly the bounce rate's worth.
8. 08Do not compare open rates across periods that straddle a change in your Apple Mail share, a change in your platform's bot filtering, or a change in denominator convention. Any of the three moves the number without anything about your audience changing.

The formula.

Delivered is sent minus bounces, and every rate on this page divides by it. The reported open rate is unique opens ÷ delivered × 100: at the worked example's figures, 52,800 ÷ 116,400 = 45.3608247423%. The two adjustments differ only in what they do with the denominator. Removing machine opens from the numerator alone gives (52,800 − 29,040) ÷ 116,400 = 20.412371134%, which is a strict lower bound because protected recipients who genuinely opened were removed from the top while remaining at the bottom. Removing those recipients from the denominator as well gives 23,760 ÷ 87,360 = 27.1978021978%, an estimate of the open rate among the audience whose behaviour is still observable. Two orderings fall out of the algebra rather than being asserted. The lower bound is always below the observable-audience rate, because the same numerator is divided by a larger denominator. And the observable-audience rate can never exceed the reported rate: the difference between them works out to M × (D − U), which is zero or positive because delivered is never smaller than unique opens — so the two coincide exactly when every delivered email was opened, or when there were no machine opens. The delivery rate does double duty. It is a deliverability metric in its own right, and it is the exact conversion factor between the two denominator conventions: open rate on sent = open rate on delivered × delivery rate, because (U ÷ D) × (D ÷ Sent) cancels to U ÷ Sent. Here that chain runs (52,800 ÷ 116,400) × (116,400 ÷ 120,000) = 52,800 ÷ 120,000 = 44%. Multiplying the two ROUNDED outputs instead — 45.3608247423 × 0.97 — gives 43.999999998, which is why the sent-based figure is computed from the raw counts and not from the other output. On rounding stage: every intermediate value is carried at full arbitrary-precision decimal width, and rounding happens once, at the return boundary, to ten decimal places. No rate on this page is derived from another rate that has already been rounded — the sent-based figure is computed from the raw counts, not from the delivered-based figure times a rounded delivery rate. Three degenerate cases are handled explicitly rather than allowed to divide by zero: bounces equal to the whole send is rejected, machine opens equal to every delivered email is rejected because no observable audience would remain, and a send with zero opens returns a machine share of 0% rather than 0 ÷ 0.

A worked example.

Frequently asked questions.

References& sources.

1. [1]Apple — "Mail Privacy Protection & Privacy" (Apple Legal, privacy data documentation). Verbatim: Mail "downloads remote content in the background by default — regardless of whether you engage with the email"; Protect Mail Activity "routes all remote content downloaded by Mail through two separate relays operated by different entities. The first knows your IP address, but not any third-party Mail content you receive. The second knows the remote Mail content you receive, but not your IP address." This is the primary authority for why a reported open rate overstates human engagement. Free, first-party. Retrieved 2026-07-29.
2. [2]Mailchimp Help — "About Open and Click Rates". Verbatim: "The open rate is a percentage that tells you how many successfully delivered emails were opened by recipients"; "The click rate is a percentage that tells you how many delivered emails registered at least 1 click"; and, on the distortion, "Bot activity such as Apple's Mail Privacy Protection (MPP) can falsely inflate open and click metrics." Official product documentation from a major measurement provider; free. Retrieved 2026-07-29.
3. [3]Mailchimp Help — "About Email Reports" (campaign statistics glossary). Verbatim: "Successful deliveries: The number of recipients who didn't hard or soft bounce on this email"; "Opened: The number of recipients who opened this email any number of times"; "Total opens: The total number of times the email was opened by recipients. This count includes multiple opens from individual recipients"; "Open rate: The percentage of successfully delivered emails that registered as an open." Establishes the delivered denominator and the unique-versus-total-opens distinction used on this page. Retrieved 2026-07-29.
4. [4]HubSpot Knowledge Base — "Analyze your marketing email campaign performance". The second, independent authority used to check the denominator: open rate is the "percentage of recipients who opened the email out of the number who received it", click rate is measured against the same base, and click-through rate is measured against openers. Also confirms the tracking mechanism: "An email open is counted when the images in the email load, or when a recipient clicks on a link in the email." It agrees with Mailchimp on the denominator; the only difference is wording (recipients versus delivered emails), which coincide for a single send. Retrieved 2026-07-29.