Your tracker says the email was opened. Should you believe it?
The honest answer: it depends on the open. Some opens are a prospect reading your proposal at their desk. Others are Apple's servers pre-loading images, or a security scanner checking your links for malware. Treating all of them as equally true is how people end up chasing ghosts. This guide is about the right amount of trust, at each level.
What does confidence mean for an email open?
It means treating an open as a probability instead of a fact. The useful question isn't "did they open it," it's "how likely is it that a real person opened it."
That's a shift in thinking, but it matches how the signal actually works. An open is recorded when a tracking image loads, and lots of things load images: people, privacy features, scanners, proxies. So every open arrives with some amount of doubt attached. Good tracking measures that doubt and shows it to you. Bad tracking hides it behind a confident-looking number. There's more on what the base metric can and can't tell you in our glossary entry on email open rate.
Why can't trackers just count opens?
Because most of what they'd count isn't people. Apple Mail Privacy Protection pre-fetches tracking pixels on Apple's servers for every reader who switches it on, read or not, and Apple Mail accounted for 62 percent of the opens Litmus measured in July 2026.
Then come the scanners. Corporate security tools like Mimecast, Proofpoint, or Microsoft Defender open and click links at delivery to check for malware, and at large companies Omnivery found 80 to 95 percent of clicks came from them. One scanner can fire many opens within seconds. Gmail adds a third wrinkle: its proxy opens are usually real, but one read can arrive as several fetches. Add it up and a raw open rate can overstate real reads by a wide margin.
How does open grading work?
Every open gets a grade: verified (the person replied on the thread), most likely human, possibly human, or a machine kind such as an Apple Mail prefetch, a link preview or a security scanner. The grade comes from request timing, network origin, and client signature, and each open shows the reason in plain words, like "opened in Gmail" or "Microsoft Defender security scan".
Timing asks: did this open land at a human moment, or two seconds after send? Origin asks: does this request come from where a reader would be? Signature asks: does the client look like a mail app a person uses, or like a known scanner? No single signal decides alone. It's the combination that separates a Tuesday-morning read from a delivery-time malware check. Only verified and most likely human opens make your stats, because a wrong count is worse than no count. The full logic is public on our methodology page, with the grade details on the confidence scoring page.
How accurate is the grading?
A weekly job checks each grading rule against replies, clicks and user corrections. A rule without enough feedback to judge reports nothing at all rather than an estimate.
And you can audit it yourself. The Diagnose view lets you click any open and see why it counted or got filtered, in plain words. If a grade ever looks wrong to you, the evidence is right there to check. That's the standard worth holding any tracker to: not "trust us," but "here's why."
What should you do with each grade?
Act on the top, wait on the middle, ignore the bottom. Verified and most likely human opens are follow-up material. Possibly human means hold until a second signal shows up, like a repeat open or a click. Apple Mail, link previews and scanners are machine noise.
This maps cleanly onto real decisions. A counted open at a human hour: send the follow-up while you're on their mind. A possibly human open: do nothing yet, one more signal usually arrives within a day if the interest is real. A scanner: pretend it never happened, because for your purposes it didn't.
Does this change how you follow up?
Yes, in one big way: you stop spending energy on ghosts. Every hour spent chasing scanner opens is an hour not spent on the prospect who read your email three times this week.
If your current tool hands you one undifferentiated count, our comparison hub shows how the major trackers handle machine noise. Or test it directly: Outsolvi is $7 a month billed yearly, $12 monthly, with a 14-day free trial, no credit card, and a 7-day money-back guarantee. Two weeks of graded opens next to your old raw counts will tell you exactly how much of your open data was ever real.