How accurate is email client market share data when Apple Mail intentionally opens messages?
Matthew Whittaker
Co-founder & CTO, Suped
Published 4 May 2025
Updated 16 Aug 2025
5 min read
When we talk about email marketing and deliverability, email client market share data often comes up as a crucial metric. It's understandable why we rely on these numbers, as they help us understand our audience and optimize campaigns. However, recent changes, particularly with Apple Mail Privacy Protection (MPP), have significantly muddied the waters.
The core issue is that Apple Mail now intentionally pre-opens emails, regardless of whether a user actually views them. This action automatically triggers the tracking pixel that many email service providers use to measure opens. Consequently, the reported open rates, and by extension, email client market share figures, can be highly inflated and misleading, making it harder to gauge true engagement.
Understanding Apple Mail Privacy Protection
Mail Privacy Protection, introduced by Apple, is designed to give users more control over their privacy. It works by routing all incoming mail through a proxy server and pre-loading all content, including tracking pixels, before the user even opens the email. This means that an open is registered, whether or not the recipient actually interacts with the message.
This feature impacts not only email open tracking but also other data points that rely on image loading, such as device type and geographic location, because the IP address is masked by the proxy. Consequently, email marketers lose a significant amount of traditional insight into subscriber behavior.
This leads to a scenario where emails sent to Gmail accounts, for example, but read using the Apple Mail client, will show an open, even if the Gmail server itself might not have registered a direct open. This creates a disconnect between the mailbox provider's filters and the client's reported activity.
The distortion of email client market share data
Traditional email client market share data is largely based on the loading of tracking pixels embedded in emails. When these pixels load, they send data back to the email service provider, indicating which client was used. With Apple Mail’s MPP, this process happens automatically, regardless of user interaction. This artificially inflates Apple Mail's reported share.
For instance, a report might show Apple Mail accounting for over 50% of email opens, as noted by sources like Litmus data. This figure, however, represents machine-generated opens (or proxy opens) rather than genuine user engagement with the email content. It makes it nearly impossible to identify who is truly engaged.
This issue is compounded by other email clients that also employ pre-fetching or proxy services, such as some Yahoo Mail versions or even Gmail's image caching. This means that what we see as an open may actually be a machine, not a human, engaging with our content. It’s hard to tell if this was a real open from any of those proxies.
Metric
Pre-MPP Interpretation
Post-MPP Interpretation
Open rate
Direct indicator of user engagement
Inflated by machine opens, unreliable for engagement
Email client market share
Accurate representation of client usage
Skewed, over-representing Apple Mail usage
Device type
Reliable for understanding audience devices
Less reliable due to proxy masking IP addresses
The primary problem is that email client market share data, typically gathered through open tracking pixels, now largely reflects how machines interact with your content, not necessarily how users actively engage with their email client. This means that if someone uses Yahoo Mail on an Apple iOS device with MPP turned on, you might see requests from both Apple and Yahoo proxies, without knowing which application the user actually opened or if they opened it at all. This makes it impossible to definitively confirm a real open or the actual client used.
The wider implications for email analytics
The implications of MPP extend beyond just market share data. Email marketers have long relied on open rates to segment audiences, measure campaign success, and even inform IP warmup strategies. With inflated open rates, these traditional approaches become less reliable.
For example, if you're using open rates to gauge subscriber engagement, you might mistakenly think a segment of your audience is highly engaged when, in reality, their emails are just being pre-fetched by Apple's proxy. This can lead to misinformed decisions about content strategy, send frequency, and list hygiene.
Best practices for accurate email analytics
Focus on clicks: Clicks are a clearer indicator of active engagement, as they require explicit user action. They are unaffected by proxy pre-fetching.
Track conversions: Ultimately, the goal of email marketing is often conversion, whether it's a purchase, sign-up, or download. This metric is the most accurate measure of ROI.
Utilize other engagement signals: Monitor replies, forwards, and unsubscribes to get a holistic view of subscriber interaction.
Regularly clean your lists: Remove inactive subscribers based on actual engagement, not just inflated opens, to maintain a healthy sender reputation. This can also help with avoiding spam traps.
Adapting to the new reality
Given the changes with Apple Mail and other privacy-focused initiatives, it's essential to adapt our approach to email analytics. We need to shift our focus from vanity metrics like inflated open rates to more meaningful indicators of subscriber engagement.
This means focusing on metrics that truly reflect user interest and intent. While open rates might still be tracked for directional insights or comparison against pre-MPP benchmarks, they should no longer be the sole, or even primary, measure of email performance. By embracing a broader view of engagement, we can ensure our email strategies remain effective and data-driven.
Traditional focus
Open rate: Primary metric for campaign success.
Client market share: Highly reliant on pixel-based tracking.
Segmentation: Often based on open behavior.
Modern focus
Click-through rate: Key metric for content effectiveness.
Shift your focus to metrics like click-through rates and conversions, as these truly reflect user engagement and are unaffected by pre-fetching.
Regularly segment your audience based on genuine interactions, not just inflated open rates, to refine your targeting and messaging strategies.
Test your emails across various clients and devices to ensure consistent rendering and functionality, regardless of privacy protections.
Leverage server-side data where possible to gain deeper insights into deliverability and engagement beyond client-side tracking.
Common pitfalls
Over-relying on reported open rates for campaign performance, leading to an inaccurate understanding of subscriber engagement.
Misinterpreting email client market share data due to pre-fetching, which can skew audience segmentation and targeting efforts.
Failing to adapt list hygiene practices to account for inflated opens, potentially leading to lower overall deliverability rates.
Not understanding that machine opens don't confirm actual user interaction or deliverability to the inbox.
Expert tips
Clicks are the new opens, focus on them.
Pre-fetching by proxies doesn't mean actual opens.
Email client market share is harder to measure.
Sender reputation isn't directly impacted by proxy opens, but engagement matters.
Expert view
Expert from Email Geeks says to take email client market share numbers with a grain of salt because measuring them using image downloads is pretty inaccurate.
2023-06-07 - Email Geeks
Expert view
Expert from Email Geeks says that now Apple is intentionally opening messages, opens are counted when content is requested from the host.
2023-06-07 - Email Geeks
Navigating the new email analytics landscape
The landscape of email analytics has undeniably changed. While traditional email client market share data and open rates provided a snapshot of engagement, Apple Mail's Mail Privacy Protection has introduced significant inaccuracies. It's crucial for marketers to understand these changes and pivot their strategies towards more reliable engagement metrics.
Apple, is designed to give users more control over their privacy. It works by routing all incoming mail through a proxy server and pre-loading all content, including tracking pixels, before the user even opens the email. This means that an open is registered, whether or not the recipient actually interacts with the message.
Gmail accounts, for example, but read using the 
Yahoo Mail versions or even 
Gmail's image caching. This means that what we see as an open may actually be a machine, not a human, engaging with our content. It’s hard to tell if this was a real open from any of those proxies.
