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Why your email open rate is wrong, and by how much

That 70 percent open rate on your dashboard probably counts a lot of machines. Where the inflation comes from, and how to see through it.

N
Nate Summers
Co-Founder, Outsolvi
Published August 2, 20265 min read752 words
Quick Answer752 words · 5 min read

Your email open rate is inflated because machines load tracking pixels too. Apple Mail Privacy Protection pre-fetches pixels for everyone who switches it on, and Apple Mail accounted for 62 percent of the opens Litmus measured in July 2026. Corporate security scanners open and click links to test them. How far a raw open rate overstates real reads depends on your list; in consumer email, Omnivery measured roughly half of all opens as machines.

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Table of contents6 sections
  1. Where does the inflation come from?
  2. How much does it change the math?
  3. Which lists get hit hardest?
  4. Why don't trackers fix this?
  5. What does a trustworthy open rate look like?
  6. What should you do this week?
Topics:email trackingOutlook email trackingGmail email trackingAI email insightsfollow-up automationawareness

Key takeaways

  • →A raw open rate can overstate real reads by a wide margin. How wide depends on your list, and nobody publishes a reliable B2B average.
  • →Apple Mail Privacy Protection is the biggest source: it pre-fetches pixels on Apple's servers, and Apple Mail accounted for 62 percent of the opens Litmus measured in July 2026.
  • →Corporate scanners (Mimecast, Proofpoint, Microsoft Defender) open and click links to test them. At large companies, 80 to 95 percent of clicks are scanners (Omnivery, 2026).
  • →Gmail's proxy opens need the full signal picture. Blind counting inflates your rate, blind discarding hides real readers.
  • →A confidence-scored open rate, graded Tier 1 to Tier 5 with a 25 percent floor, is the version of the metric you can actually act on.

Here's an uncomfortable fact: the open rate on your dashboard is wrong. Often not by a little: machines load tracking pixels too, and on a list full of iPhone readers and enterprise inboxes, a big share of your "opens" is software.

That's not a rounding error. That's a different story about your outreach.

Where does the inflation come from?

Three places, and none of them are your prospects.

Apple Mail Privacy Protection is the biggest one. Apple pre-fetches tracking pixels on its own servers, so every Apple Mail reader who switches it on registers as an opener whether they read your email or not. Apple Mail accounted for 62 percent of the opens Litmus measured in July 2026. On a list that skews toward Apple users, this single mechanism can flip most of your open data from signal to noise.

Corporate security scanners are the second. Mimecast, Proofpoint, and Microsoft Defender open every link and image in incoming email to check for malware. At large companies behind these gateways, Omnivery found 80 to 95 percent of clicks came from these scanners, not people. Email you send them gets opened and clicked by software, often within seconds of delivery.

Gmail's image proxy is the messy third. Gmail serves images through its own proxy, so the request your tracker sees didn't come straight from the reader. Some proxy opens are real humans reading. Some aren't. Telling them apart takes the full signal picture, not blind counting and not blind discarding.

How much does it change the math?

A lot. Say you send 100 cold emails and your tracker reports 70 opens.

If half your list is on Apple Mail with MPP on, those 50 recipients register opens automatically. If a fifth of your list sits behind a scanner, those 20 register too, instantly. That's 70 opens before anyone has read a word. Some of those people probably did read, but a raw count can't tell you which ones, so the 70 tells you very little.

Now think about what you did with the inflated number. You followed up with "openers" who never saw your email. You wrote off subject lines that were actually fine. You told your team the top of the funnel was healthy when it wasn't. Wrong data doesn't just sit there. It steers.

Which lists get hit hardest?

Lists heavy on Apple Mail users and corporate domains. That describes most B2B lists.

Selling to consumers on personal iPhones? Nearly every recipient has Apple's pre-fetch working against your data. Selling to mid-size and enterprise companies? A big slice of those inboxes sit behind Mimecast, Proofpoint, or Defender, and every send gets machine-opened on arrival.

The frustrating part is that the inflation isn't even. One campaign might land on a scanner-heavy segment and report sky-high opens. The next hits a segment with fewer machines and looks like a flop. Neither number reflects your subject lines or your list quality. You end up "learning" lessons from noise.

Why don't trackers fix this?

Mostly because counting pixel loads is easy and grading them is hard. A tracker that reports every load gets to show you a big flattering number. A tracker that filters has to explain why your open rate just dropped by half, and that's a harder sales pitch, even when it's the honest one.

Our take is simple: no score beats a wrong score. If a tool can't tell you which opens were human, the big number it shows you isn't a feature.

What does a trustworthy open rate look like?

It's a graded one. Outsolvi scores every open from Tier 1 (high-confidence human) down to Tier 5 (bot or scanner), using request timing, network origin, and client signature. Anything below a 25 percent confidence floor is excluded from your counts. The full rules are public on the methodology page, and the confidence scoring feature page shows how the tiers surface in the app.

Every classification rule's precision is recomputed weekly from real user corrections. And when you want to check a specific open, the Diagnose view shows you exactly why it counted or got filtered. Click the number, see the evidence.

What should you do this week?

Pull up last month's open rate and ask one question: does this number include machines? If your tracker can't answer, you have your answer.

Then compare. The comparison hub breaks down how the major trackers handle this. Or run the test directly: Outsolvi is $7 a month billed yearly, with a 14-day free trial and no credit card needed. Two weeks of real sends will show you the gap between your reported opens and your real ones. Fair warning: the real number is smaller. It's also the only one worth acting on.

Stop trusting raw open counts.

Outsolvi grades every open, so you know who read your email and which opens were an Apple Mail preview or a security scanner. 14-day free trial, no credit card.

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Frequently asked questions

Direct answers to the questions readers of this article most often ask.

How inflated is my open rate?+

It depends on how many of your recipients use Apple Mail with Mail Privacy Protection on, and how many sit behind corporate security scanners. Nobody publishes a reliable B2B average. The best measured figure is for consumer email, where Omnivery found roughly half of all opens were machines every year since 2023.

Is a high open rate ever bad news?+

It can be a warning sign. If your open rate looks too good, like 70 or 80 percent on cold outreach, the most likely explanation is that your tracker is counting Apple pre-fetches and security scanners as people.

Why not just ignore opens and track replies only?+

Replies are a great signal but a rare one. Filtered, confidence-scored opens tell you who's paying attention before they reply, which is when follow-up timing matters most. The answer is a better open number, not no open number.

How do I know which of my opens were real?+

Use a tracker that grades each open and shows its work. Outsolvi scores every open from Tier 1 (high-confidence human) to Tier 5 (bot or scanner), and the Diagnose view lets you click any open and see why it counted or was filtered.

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Nate SummersCo-Founder, Outsolvi

Writing about email tracking, follow-up timing, and AI signals for sales teams who hit send on real pipelines. Outsolvi is built natively for Outlook and Gmail, with AI follow-up insights from $7/mo billed yearly.

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