How does Apple Mail Privacy Protection (MPP) affect the tracking of email opens and clicks, and how are machine opens categorized?
Michael Ko
Co-founder & CEO, Suped
Published 5 Aug 2025
Updated 16 Aug 2025
7 min read
When Apple introduced Mail Privacy Protection (MPP) with iOS 15 in September 2021, it significantly altered the landscape of email tracking. This feature was designed to give users more control over their data, specifically by preventing senders from learning information about their email activity. For many of us in email marketing and deliverability, it meant a fundamental shift in how we interpret engagement metrics, particularly open rates.
Before MPP, tracking pixels embedded in emails would load only when a recipient opened the message, providing a reliable signal of engagement. With MPP, Apple's proxy servers now pre-load all images and content, including these tracking pixels, regardless of whether the user actually views the email. This change creates a challenge for marketers who rely on traditional open rate metrics to gauge campaign performance.
The immediate consequence was a noticeable inflation of open rates for users leveraging the Apple Mail app across their devices. This inflated data makes it harder to truly understand genuine recipient engagement. We now have to contend with a new category of machine opens, which are automatically triggered by Apple's servers rather than human interaction.
How MPP affects open tracking
MPP works by routing email content through a proxy server. When an email arrives in an Apple Mail inbox, the proxy server downloads all remote content, including the tracking pixel, before the user even has a chance to open the email. This pre-fetching action is what triggers the false open. It's a privacy measure designed to hide the user's IP address and location, preventing senders from gaining insights into when or if an email is opened.
This means that the open event you see in your email service provider (ESP) or analytics platform for an Apple Mail user might not correspond to a human opening the email. It's simply the Apple proxy fetching the content. While this can confirm the email inbox delivery, it distorts traditional engagement metrics and makes it challenging to accurately assess true open rates. Many ESPs have adjusted their reporting to try and filter or categorize these, but it remains a complex issue.
The impact extends beyond just raw open numbers. Features like perfect send time optimization, which rely on precise open timing, are also affected. This makes it crucial to explore alternative methods to estimate real open rates and understand campaign effectiveness.
Before Apple Mail Privacy Protection (MPP)
Open Tracking: Reliably tracked when a user opened an email, triggered by the loading of a tiny, invisible pixel.
Metrics: Open rates were considered a core engagement metric, reflecting actual recipient interest.
Data Richness: Senders could often infer device type, location (from IP address), and precise open times.
After Apple Mail Privacy Protection (MPP)
Open Tracking: Opens are pre-fetched by Apple's proxy, making it appear as if all emails are opened, even if they aren't viewed.
Metrics: Open rates are inflated and no longer a reliable indicator of human engagement. Focus shifts to other metrics.
Data Anonymity: User IP addresses are hidden, and precise open times are obscured, limiting demographic and behavioral insights.
Categorizing machine opens
Machine opens, particularly those generated by Apple MPP, are often indistinguishable from genuine human opens using traditional tracking methods. This is because the signal received by your ESP is simply an image request from an Apple server, not directly from the user's device. As a result, many email marketing platforms categorize these MPP-triggered events as standard opens, contributing to the inflated rates.
The challenge lies in attributing these machine opens to a specific device type, such as desktop or mobile. The HTTP referer information, which usually provides clues about the user's environment, is largely sanitized by the Apple proxy. This makes it difficult for tracking mechanisms to accurately categorize whether an MPP open originated from an Apple mobile or desktop device. Any tool attempting to assign these proxy fetches to a specific device type is likely making an educated guess at best, and potentially inaccurate assumptions.
It's important to understand that not all machine opens are Apple MPP opens. Other services, such as Gmail and Yahoo, also employ proxy services that can trigger machine opens for various reasons, including spam filtering and caching. Therefore, accurately identifying artificial opens can be quite complex, requiring a nuanced approach to data analysis and segmentation.
Open Type
MPP Impact
Device Identification
Apple MPP Opens
Inflates open rates by pre-fetching email content.
Difficult to determine if from mobile or desktop device due to proxy sanitization.
Other Machine Opens (e.g., Gmail, Yahoo)
Can also trigger false opens for spam filtering or caching purposes.
Similar challenges in accurate device identification.
Human Opens
Represents genuine recipient engagement with the email content.
More reliable device identification (though still subject to other privacy features).
The impact on click tracking
While Apple MPP profoundly impacts open tracking, its effect on click tracking is generally minimal. This is a crucial distinction. When a recipient clicks a link within an email, that action typically redirects them to a web page through their web browser. This process usually bypasses the Apple proxy servers that handle image pre-loading.
Clicks are processed differently than image requests. They are active engagements initiated by the user, leading to a new web request. Because of this, MPP does not directly interfere with click tracking. You can still reliably track if a user interacted with your email content by clicking on a link. This means metrics like Click-Through Rate (CTR) and Click-to-Open Rate (CTOR) become even more valuable in a post-MPP world.
However, it's worth noting that other privacy-preserving features, such as Apple's Private Relay or various VPN services, could still obscure the user's IP address when they click a link. While the click itself is recorded, the geographical or device-specific information associated with that click might be anonymized. Understanding how MPP and other privacy features affect click tracking is essential for a comprehensive view of your email performance.
Adapting to the new reality of email metrics
Given the unreliability of open rates for a significant portion of your audience, it's imperative to adapt your email marketing strategy. The focus should shift from solely relying on opens to prioritizing other, more definitive engagement metrics. These include click-through rates, conversion rates (e.g., purchases, sign-ups), website visits originating from email, and even direct replies to your emails.
By emphasizing these actions, you gain a clearer picture of true recipient interest and campaign effectiveness. For instance, a high CTR despite a potentially inflated open rate indicates that your content is compelling enough to drive action. Moreover, leveraging better metrics for outbound campaign effectiveness helps ensure your marketing efforts are genuinely impactful, not just seemingly so.
Segmenting your audience can also provide valuable insights. While you can't always identify MPP users precisely, you can often infer their presence based on client data or by observing patterns of inflated opens without corresponding clicks. This allows you to tailor your analytics and reporting to account for the MPP effect, providing a more accurate understanding of your overall email program's health and helping you avoid potential inaccurate open tracking scenarios.
Views from the trenches
Best practices
Focus on click rates and conversions as primary indicators of engagement, rather than inflated open rates.
Segment your audience by email client or inferred MPP usage to better understand genuine engagement patterns.
Utilize engagement metrics beyond opens, such as website visits, replies, and unsubscribe rates, for a holistic view.
Common pitfalls
Over-relying on open rates as a key performance indicator (KPI) post-MPP, leading to skewed perceptions of campaign success.
Misinterpreting machine opens as genuine human engagement, which can lead to misguided optimization efforts.
Failing to adapt reporting and analytics to account for the impact of Apple MPP and other privacy features.
Expert tips
Consider a shift in strategy towards 'click-based' engagement metrics for a more accurate understanding of recipient interest.
Implement a robust segmentation strategy to analyze behavior among different user groups, including those affected by MPP.
Regularly review your data for anomalies and understand the limitations of open tracking in today's privacy-focused environment.
Expert view
Expert from Email Geeks says that the categorization of MPP machine opens as desktop or mobile depends entirely on the tracking mechanism. These are fetches from a server, not directly from a device, so any tool trying to assign a device type is likely making an incorrect assumption.
March 16, 2023 - Email Geeks
Expert view
Expert from Email Geeks says that email headers are sanitized by the Apple proxy, which means there may not be enough information to distinguish between mobile and desktop opens. It makes more sense for email services to categorize them in their own group.
March 16, 2023 - Email Geeks
Navigating email engagement in a privacy-first world
Apple Mail Privacy Protection has undeniably changed how we measure email engagement, particularly open rates. While it presents a challenge for traditional tracking methods, it also serves as an important impetus for marketers and deliverability professionals to evolve their strategies. We must move beyond a sole reliance on open rates and instead embrace a more comprehensive suite of metrics that truly reflect recipient interaction and campaign success.
By understanding the technical mechanisms behind MPP's impact on opens versus clicks, and by accurately categorizing machine-generated opens, we can develop more robust and insightful analytics frameworks. Focusing on clicks, conversions, and other downstream actions will provide a more accurate picture of your email program's performance and help you continue to optimize for genuine engagement in this privacy-first era.
