Why Email Open Rate Is an Unreliable Metric Now (and What to Track Instead)

Why Email Open Rate Is an Unreliable Metric Now (and What to Track Instead)

Email open rate is no longer a reliable measure of genuine engagement because Apple's Mail Privacy Protection (MPP), enabled by default across Mail app users since 2021, pre-loads every tracking pixel in an incoming email automatically - registering an open the instant the message arrives at Apple's servers, whether a human ever sees it or not. On a list with a meaningful share of Apple Mail users, this inflates open rate independent of whether anyone actually engaged.

Key takeaways

1. Apple Mail Privacy Protection pre-fetches every tracking pixel automatically on delivery, registering a false open before a human ever opens the message.
2. The inflation is proportional to Apple Mail share on the list - a list skewed toward iPhone/Mac users sees a larger, more misleading open-rate lift than a list dominated by other clients.
3. Open rate is not gone as a metric, it is just no longer directly comparable across lists, over time, or against pre-2021 historical benchmarks without accounting for MPP skew.
4. Click-through rate and click-to-open rate remain reliable, since MPP triggers an automatic pixel fetch but cannot fabricate a genuine link click.
5. Downstream conversion metrics (site visits, purchases, signups from email traffic) are unaffected by MPP and should carry more weight in evaluating a campaign than open rate alone.

Teams that still report open rate as the headline email metric are frequently measuring Apple's prefetching behavior more than their own audience's actual engagement - and a rising open rate over time can just as easily mean more subscribers switched to Apple Mail as it can mean better subject lines.

Mail Privacy Protection (MPP): an Apple Mail feature, on by default since iOS 15 and macOS Monterey, that routes all incoming mail images through Apple's proxy servers and pre-loads them regardless of whether the user opens the email.

Click-to-open rate (CTOR): the percentage of opens that resulted in a click, calculated only from confirmed opens - a metric that is somewhat protected from MPP inflation since it is a ratio between two engagement signals rather than a raw open count.

Why the inflation isn't uniform across lists

The operational pain this creates for teams comparing performance across segments or time periods: MPP's effect scales directly with the share of the list using Apple Mail, so open rate is not just inflated - it is inflated by a different, list-specific amount, making cross-list or cross-time comparison unreliable unless that Apple Mail share is tracked and adjusted for.

A B2B list skewing toward Windows/Outlook users will show a smaller MPP-driven lift than a B2C list skewing toward iPhone users, even if the two lists have genuinely identical human engagement. This means a marketer benchmarking two campaigns' open rates against each other, without knowing each list's device mix, is comparing two different measurement artifacts rather than two comparable engagement numbers. The same underlying problem - two systems producing numbers that were never meant to reconcile - shows up when GA4's own modeled conversions get compared directly against an ad platform's reported conversions: the fix in both cases is tracking each source's own trend over time, not chasing an exact cross-source match.

Prooflytics

Turn scattered analytics into one clear picture

Every source in one brief. The whole picture. Your decision.

Start free trialSee pricing

14 days free · no credit card

What still works, and what to report instead

The ICP problem this creates for a marketer who has to report on email performance to a manager or client: an open rate that no longer means what it used to still gets asked for, and simply removing it from the report without explanation reads as evasive, not disciplined.

Click-through rate is not affected by MPP's automatic pixel prefetch, because clicking a link requires an actual human action that Apple's proxy servers cannot simulate - a genuinely engaged subscriber still has to tap or click for a click event to register. Click-to-open rate is a useful secondary check specifically because it is a ratio of two engagement-adjacent numbers rather than a raw count, which partially (not fully) dampens the MPP skew embedded in the open-rate denominator. Downstream metrics - site sessions from email traffic, conversions attributed to an email send, revenue per email sent - are the most reliable of all, since they require the recipient to take an action entirely outside Apple's mail infrastructure. The same principle of trusting the downstream conversion over a proxy metric applies to CTR-optimized creative that quietly inflates cost per acquisition - a metric that looks good in isolation can still be the wrong one to optimize toward.

The practical reporting shift: keep open rate visible for historical continuity, but present it alongside click-through rate and downstream conversions as the primary decision metrics, and note the Apple Mail share of the list so a reader can judge how much of any open-rate movement is measurement artifact versus real engagement change. The same shift away from a single misleading top-line metric applies to send frequency decisions - a list fatigue signal hidden inside a rising unsubscribe rate is a similar case of one number needing a second, more durable metric alongside it before it can be trusted on its own.

Google does not publish one complete official list of what restarts the Smart Bidding learning phase, which is exactly why teams keep triggering it by accident -- What Actually Resets the Smart Bidding Learning Phase covers the most consistently reported triggers and what usually does not reset it.

Using instrumentation discipline when the budget for measurement itself is flat

The ICP problem this creates for teams whose email program isn't growing in budget or headcount: measurement problems like this one tend to get deprioritized exactly when there's no budget increase to justify fixing them, even though the fix here costs nothing but attention.

By a rule from Prooflytics' own product knowledge base on marketing measurement discipline: when a channel's budget stays flat, the team should disproportionately prioritize instrumentation and measurement quality on that channel rather than assuming a stable budget means the current measurement setup is good enough - teams with flat budgets that focus on tracking and measurement quality tend to get more defensible analytics on their existing spend, precisely because no one else is competing for that attention when there's no growth story to chase. Applied to email specifically: fixing how open rate gets reported, and shifting the headline metric to click-through and downstream conversion, is exactly the kind of flat-budget measurement improvement that costs nothing to implement and directly improves decision quality on spend that's already committed.

Prooflytics tracks Email as a channel-grouped source in the daily briefing today - session and conversion volume from UTM-tagged email traffic, the same downstream signal GA4 itself uses - though it does not yet ingest click or open events directly from the email platform itself, so platform-level click and open data still has to come from the ESP's own reporting.

Bottom line

• Apple Mail Privacy Protection pre-fetches tracking pixels automatically, inflating open rate by an amount proportional to each list's Apple Mail share - not a fixed, universal percentage.
• Stop comparing open rate directly across lists or time periods without accounting for Apple Mail share; the comparison is otherwise measuring device mix, not engagement.
• Report click-through rate and downstream conversions as the primary decision metrics; keep open rate for historical continuity and rough deliverability signal only.
• Treat this as exactly the kind of low-cost measurement fix worth prioritizing on a flat email budget - it costs nothing and directly improves decision quality on spend already committed.
• Book a walkthrough to see how Prooflytics tracks Email as a channel-grouped source in the daily briefing alongside every other channel.