Open Rate

Open rate is the percentage of delivered emails that recipients opened — opens divided by emails successfully delivered, expressed as a percentage. If you deliver 10,000 emails and 2,000 are opened, the open rate is twenty percent. It has long been one of the first numbers email marketers look at, because it sits at the very top of email engagement: before anyone clicks a link or buys anything, they have to open the message. As a result, open rate has traditionally been read as a signal of two things — how compelling the subject line and sender name were at earning the open, and how engaged and healthy the list is overall. A rising open rate on a subject-line test suggests the new line drew more people in; a chronically low open rate hints at a tired list or deliverability trouble.

Mechanically, an open has historically been counted using a tiny invisible tracking pixel embedded in the email. When the recipient's email client loads images, it requests that pixel from the sender's server, and that request is recorded as an open. This is worth understanding because it explains both how open rate works and why it became unreliable: the metric depends on images loading, which means it was never perfectly accurate (people who block images but read the email do not register an open), and it left the door open to being thrown off entirely when a major email provider changed how images load. Open rate, in other words, is an inferred metric, not a directly observed one, and that inference is only as good as the assumption that an image load equals a human reading.

The honest state of open rate today is that Apple Mail Privacy Protection (MPP), introduced in 2021, broke it as a precise measure. To protect users, Apple Mail began pre-loading email images — including tracking pixels — automatically through a proxy, whether or not the recipient actually opened the message. Because Apple Mail is one of the most widely used email clients, this means a large share of "opens" are now machine-generated by Apple's servers rather than real human opens. The effect is to inflate reported open rates and detach them from genuine engagement. An open rate that includes MPP-affected recipients counts opens that may never have happened, so the headline number is systematically too high and no longer a clean read of how many people really opened.

This does not make open rate worthless, but it does change how you must treat it. As an absolute measure of engagement, it is now unreliable and should be read with heavy skepticism, especially across audiences with many Apple Mail users. As a relative measure, it retains some limited use — comparing two subject lines sent to the same audience at the same time can still hint at which drew more opens, since the MPP inflation affects both roughly equally. But the broader lesson is to stop leaning on open rate as a primary success metric and shift weight toward signals MPP does not distort, like clicks, conversions, replies, and unsubscribes. Open rate went from a trusted top-of-funnel gauge to a number that must be heavily caveated, and pretending otherwise leads to false confidence.

Using open rate well now means demoting it. Treat it as a soft, caveated indicator rather than a headline metric, and never report it as if it were a clean measure of engagement, because a meaningful share of counted opens are Apple's servers pre-loading images, not people reading. Where you do use it, use it relatively and carefully — a subject-line A/B test on one audience at one time can still suggest which line earned more opens, since the inflation hits both variants similarly — but resist drawing absolute conclusions from the raw percentage. Most of all, move your attention and your goals down the funnel to metrics that survived the change: click-through rate, conversions, replies, revenue per email, and unsubscribe rate all reflect real recipient behavior that MPP does not manufacture.

The failures are mostly failures of pretending nothing changed. Reporting open rate as a clean success metric invites false confidence built on machine-generated opens. Comparing open rates across audiences with very different shares of Apple Mail users is comparing apples to inflated apples. Optimizing hard for open rate — chasing the number with clickbait subject lines — can even hurt, training a list to feel misled. And ignoring the metrics MPP did not touch leaves you blind to what actually happened after the open. The discipline is to acknowledge that open rate is now distorted, use it only relatively and with caveats, and judge email success primarily on downstream behavior — clicks, conversions, replies, and unsubscribes — that reflects real people rather than pre-loaded pixels.

Open rate — the share of delivered emails opened — gauged subject lines and engagement, but Apple Mail Privacy Protection in 2021 began pre-loading images and inflating it, so it now demands heavy caveats.

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