Email Service Providers (ESPs) utilize a combination of technical and behavioral analyses to distinguish between human and bot email opens and clicks, although achieving complete accuracy remains a significant challenge. Their primary methods include scrutinizing IP addresses for suspicious origins, known bot networks, or unusually rapid activity. They also analyze user-agent strings to identify automated clients and assess the speed of interaction, as bots frequently engage almost instantly upon delivery. Furthermore, ESPs look for behavioral anomalies like repetitive patterns and the non-execution of JavaScript. However, the introduction of Apple Mail Privacy Protection (MPP) has fundamentally altered open tracking, as it pre-fetches all images, making automated opens indistinguishable from genuine human interactions and rendering the open rate largely unreliable as an engagement metric. While ESPs continuously refine their proprietary algorithms to filter out bot activity, their efforts operate on a best-effort basis, acknowledging that sophisticated bots can increasingly mimic authentic user behavior.
13 marketer opinions
Distinguishing between human and bot email engagement remains an ongoing, complex challenge for Email Service Providers (ESPs). While they leverage a range of technical analyses-including scrutinizing IP addresses, user-agent strings, and the speed of interaction-the sophistication of bots continues to evolve, making 100% accuracy elusive. ESPs are in a continuous race to refine their proprietary algorithms to filter out non-human interaction, operating on a best-effort basis to provide actionable data. This dynamic landscape means marketers must interpret engagement metrics with increasing caution, often correlating them with broader business outcomes rather than relying solely on raw open or click data.
Marketer view
Marketer from Email Geeks explains that ESPs do not achieve 100% reliability in distinguishing between human and bot opens/clicks, operating on a best-effort basis to provide reasonable reporting. Non-human clicks often occur very shortly after delivery, making them somewhat plausible to "fake up" in reporting, while opens are much harder to reliably distinguish.
5 Mar 2024 - Email Geeks
Marketer view
Marketer from Email Geeks shares that a significant portion of non-unique HTTP requests for click tracking links originate from a single ASN and a small number of user-agents. He suggests that a decent starting point for distinguishing can be achieved with a few rules, but more comprehensive rules are needed to reach 95%+ coverage.
4 May 2025 - Email Geeks
2 expert opinions
The primary challenge for Email Service Providers (ESPs) in discerning human email opens from automated actions stems directly from Apple Mail Privacy Protection (MPP). This feature pre-loads all images through proxy servers, rendering automated 'opens' functionally identical to genuine recipient interactions. Consequently, ESPs find it nearly impossible to reliably differentiate between a human open and one triggered by MPP or a bot, effectively invalidating the open rate as a reliable metric for measuring true subscriber engagement.
Expert view
Expert from Word to the Wise explains that due to Apple Mail Privacy Protection (MPP), which pre-loads all images via proxy servers, automatic opens are indistinguishable from human opens at the ESP level, making it extremely difficult for ESPs to reliably differentiate between the two. This invalidates open rate as a reliable metric for engagement.
27 Jan 2025 - Word to the Wise
Expert view
Expert from Spam Resource explains that Apple Mail Privacy Protection (MPP) pre-fetches and pre-loads email images, resulting in automated 'opens' that are indistinguishable from genuine human opens. This makes it nearly impossible for ESPs to reliably discern whether an open was a true recipient interaction or an automated action by a bot or privacy feature.
6 Sep 2023 - Spam Resource
4 technical articles
Email Service Providers (ESPs) actively implement sophisticated, often proprietary, systems to distinguish between human and bot-generated email opens and clicks. While most ESPs confirm they proactively filter out automated activity to provide more accurate engagement data, specific methodologies vary. Common techniques include analyzing IP reputation, inspecting user-agent strings for known bot patterns, evaluating the speed and sequence of interactions, and leveraging client-side script execution, like JavaScript, as a critical differentiator for confirming genuine user engagement.
Technical article
Documentation from Mailchimp explains that their systems automatically filter out a significant amount of bot activity from email open and click tracking data to provide more accurate engagement metrics. While specific methods aren't detailed, it implies proprietary algorithms are used to identify and exclude non-human interactions.
6 Jul 2024 - Mailchimp
Technical article
Documentation from SendGrid states that they proactively filter out common bot activity from their click tracking data. This ensures that the reported click-through rates reflect human engagement more accurately, indicating that their system has built-in mechanisms to differentiate between automated and genuine user interactions.
2 Nov 2023 - SendGrid
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