Summary
Identifying artificial email opens and clicks, generated by spam filters, security solutions, and privacy features, is crucial for accurate email deliverability analysis. These non-human interactions, often from services like Barracuda, Proofpoint, Mimecast, and features like Apple Mail Privacy Protection (MPP) and Gmail's image proxy, distort traditional engagement metrics, particularly open rates. Marketers can detect this automated activity by observing patterns such as opens occurring immediately after sending, all links being clicked simultaneously, or opens originating from known data center IP addresses and specific security vendor user agents. Recognizing these anomalies allows email marketers to pivot their focus from inflated open rates to more reliable metrics like click-through rates and conversions, enabling more effective list management and campaign optimization.
Key findings
- Diverse Sources of Artificial Activity: Artificial opens and clicks are generated not only by traditional spam filters like Barracuda, Proofpoint, and Mimecast, which 'detonate' or pre-fetch emails in sandbox environments, but also by privacy features such as Apple Mail Privacy Protection (MPP) and Google's image proxy, which automatically load email content.
- Telltale Identification Patterns: Key signs of artificial engagement include opens occurring immediately after sending, all links being clicked within milliseconds, opens originating from data center IP ranges or specific security vendor IP addresses, and user agent strings that do not correspond to typical browsers or email clients. Anomalies in geographic data, such as opens from unusual locations, also point to non-human interaction.
- Impact on Engagement Metrics: These artificial interactions significantly inflate open rates, rendering them less reliable as a sole indicator of human engagement. High open rates coupled with unusually low click-through rates or lack of downstream activity (e.g., website visits, purchases) are strong indicators of bot or security scanner activity.
- Client-Specific Behaviors: Different email clients and services exhibit specific behaviors; for instance, Microsoft's filters may follow List-Unsubscribe links, while Google's filters do not. Apple Mail users, due to MPP, will consistently show inflated open rates, masking actual engagement.
Key considerations
- Prioritize Actionable Metrics: Shift focus from raw open rates to more reliable indicators of genuine engagement, such as click-through rates (CTR), click-to-open rates (CTOR), website visits, and conversion data. A high open rate with a low CTOR, for example, can signal significant artificial activity.
- Analyze Log Data: Examine detailed email log data, including IP addresses, user agent strings, and timestamps. Look for opens and clicks originating from known data center IP ranges, security vendor networks, or unusual geographic locations. User agent strings like 'Proofpoint URL Defense' or 'Mimecast' are strong indicators of automated scanning.
- Segment by Client: Segment your audience by email client and device type, particularly Apple Mail users, to account for the expected inflation of open rates due to Mail Privacy Protection (MPP). This allows for a more nuanced understanding of engagement across different segments.
- Adjust Engagement Scoring: Update engagement scoring models to de-emphasize the open metric, especially for contacts exhibiting signs of artificial engagement. Assign higher value to more definitive actions like clicks, form submissions, and conversions, to accurately identify truly engaged subscribers.
- Refine List Hygiene: Adapt list hygiene strategies to account for artificial opens. Instead of solely relying on opens for re-engagement or suppression, prioritize actual click activity and downstream conversions. Contacts showing only 'opens' over extended periods might be better treated as unengaged.
What email marketers say
14 marketer opinions
To accurately measure email campaign performance amidst the prevalence of artificial opens and clicks, marketers must employ sophisticated detection strategies. These non-human interactions, stemming from spam filters, security software, and privacy enhancements like Apple Mail Privacy Protection, obscure true subscriber engagement. Identifying such activity involves scrutinizing detailed email logs for patterns like rapid, sequential opens and clicks from the same IP address, opens originating from known data centers or security vendor networks, and user agent strings indicative of automated processes. By recognizing these anomalies, email marketers can pivot from relying on inflated open rates to prioritizing more meaningful metrics like click-through rates, conversions, and website visits, ensuring that engagement data reflects genuine human interest.
Key opinions
- Automated Pre-fetching Behaviors: Spam filters like Barracuda frequently generate excessive opens and clicks, sometimes even before an email is fully accepted by the recipient's server, a behavior also observed with Google and Microsoft filters, particularly for .edu and non-profit domains.
- Distinct Client-Specific Filter Actions: Microsoft's security filters are known to follow 'List-Unsubscribe' links, whereas Google's filters generally do not, adding a layer of complexity to engagement tracking across different platforms.
- Forensic Identification Patterns: Artificial engagement is characterized by specific, non-human patterns such as opens occurring within milliseconds of sending, multiple rapid clicks on all links within an email, near 100% click rates, and opens originating from known data center IP ranges, security scanner user agents, or unexpected geographic locations.
- Distorted Open Rates and CTOR Significance: The presence of artificial opens significantly inflates raw open rates, making the click-to-open rate (CTOR) a more reliable indicator of true engagement; a high open rate coupled with a very low CTOR strongly signals bot or pre-fetching activity.
Key considerations
- Beyond Raw Open Rates: Shift the primary focus from raw open rates to more reliable engagement metrics like click-through rates (CTR), click-to-open rates (CTOR), website visits, and conversion data to gauge genuine subscriber interest.
- Deep Dive into Log Data: Analyze raw log data for detailed insights, including IP addresses, user agent strings, and timestamps, to pinpoint opens and clicks from suspicious sources such as data centers, known VPNs, or security scanners.
- Refine Engagement Scoring Models: Adjust internal engagement scoring models to de-emphasize the open metric, especially for Apple Mail users or contacts exhibiting suspicious open patterns, assigning higher value to verifiable actions like clicks, form submissions, and purchases.
- Strategic List Management: Adapt list hygiene strategies by prioritizing actual click activity and downstream conversions over opens. Contacts showing only 'opens' over extended periods, without other engagement, should be considered unengaged for list health purposes.
- Leverage Advanced Analytics: Utilize advanced analytics and tools that provide granular data on opens and clicks, enabling the detection of patterns indicative of bot activity, potentially even employing machine learning models for sophisticated anomaly detection.
Marketer view
Email marketer from Email Geeks explains that she has definitely seen excessive opens and clicks generated by spam filters, believing Barracuda is hosted on Amazon/AWS servers. She also notes that Outlook's cloud EOP filter clicks on the list-unsubscribe header.
13 Sep 2024 - Email Geeks
Marketer view
Email marketer from Email Geeks confirms frequently seeing excessive opens and clicks with Barracuda, occurring before email acceptance, noting it as a tribal knowledge issue without formal documentation.
5 May 2023 - Email Geeks
What the experts say
2 expert opinions
Identifying artificial email opens and clicks, which are primarily generated by security vendors like Proofpoint and Mimecast, is essential for accurate email deliverability analysis. This non-human activity can be detected through a careful examination of user-agent strings and IP addresses. Key indicators include specific user-agent strings, such as 'Proofpoint URL Defense,' IP addresses originating from data centers rather than typical residential locations, and opens that occur almost instantly after an email is sent. Furthermore, a lack of subsequent clicks or other user activity from these 'opens,' coupled with unusual geographic origins, also signals automated engagement. By understanding these patterns, marketers can distinguish genuine engagement from bot activity.
Key opinions
- User-Agent String as Key Indicator: Security vendors such as Proofpoint and Mimecast often use unique user-agent strings, like 'Proofpoint URL Defense,' which are critical for identifying artificial email interactions.
- Data Center IP Origins: Automated opens and clicks predominantly originate from data center IP ranges or cloud provider networks, contrasting with the residential IP addresses of human subscribers.
- Immediate Open Timestamps: A strong indicator of automated activity is an email open occurring almost instantaneously after the send time, signifying pre-fetching by security filters.
- Lack of Follow-Up Engagement: Unlike genuine opens, artificial opens are rarely followed by subsequent user actions, such as clicking on links, making this lack of activity a key diagnostic sign.
- Geographic Anomalies Point to Bots: Opens and clicks from unusual or unexpected geographic locations are often a sign of automated email scanning rather than authentic subscriber engagement.
Key considerations
- Analyze User-Agent Strings: Regularly examine user-agent strings associated with opens and clicks. Specific strings like 'Proofpoint URL Defense,' 'Mimecast,' or 'Barracuda' are clear indicators of automated security scanning.
- Scrutinize IP Addresses: Investigate the IP addresses from which opens and clicks originate. Artificial activity often comes from data center IP ranges or cloud providers, rather than typical residential or corporate networks.
- Assess Open Timeliness: Pay close attention to opens that occur almost immediately after an email is sent. This rapid engagement is a hallmark of automated pre-fetching by spam filters and security tools.
- Monitor Subsequent Activity: Observe if opens are followed by actual user activity, such as clicks on links or website visits. Artificial opens typically lack any subsequent engagement from the 'user'.
- Check Geographic Origin: Look for opens originating from unusual or unexpected geographic locations that do not align with your subscriber base, as this can indicate automated scanning from data centers.
Expert view
Expert from Spam Resource explains that artificial email opens and clicks, generated by security vendors like Proofpoint or Mimecast, can be identified by examining user-agent strings and IP addresses. These vendors often use unique user-agent strings, for example 'Proofpoint URL Defense,' and originate from data center IP ranges, not typical residential IPs, when pre-fetching emails to scan for malware or phishing threats.
25 Dec 2024 - Spam Resource
Expert view
Expert from Word to the Wise shares that automated email opens, often caused by security tools, can be identified by several indicators: opens occurring almost immediately after sending, specific non-browser user-agent strings, for example 'Mimecast' or 'Barracuda,' IP addresses originating from data centers or cloud providers, unusual geographic locations, and a lack of subsequent clicks or user activity from these 'opens.'
14 Feb 2025 - Word to the Wise
What the documentation says
5 technical articles
Identifying artificial email opens and clicks is critical for understanding true audience engagement. These non-human interactions often stem from email client privacy features, such as Apple's Mail Privacy Protection and Gmail's image proxying, which pre-load content and mask user data. Additionally, corporate security solutions and spam filters from providers like Proofpoint and Validity commonly employ 'sandbox detonation,' opening emails and clicking all links in isolated environments to check for threats. Such automated actions significantly inflate open rates and distort engagement metrics. Marketers can identify this artificial activity by observing patterns like rapid, comprehensive clicks from known security vendor IP ranges or data centers, and by shifting their analytical focus from unreliable open rates to more dependable metrics like click-through rates and conversions.
Key findings
- Privacy-Driven Pre-loading: Features like Apple's Mail Privacy Protection (MPP) and Gmail's image proxy automatically pre-load email content, resulting in artificial open signals and masking actual user IP addresses and locations.
- Security Sandbox Detonation: Corporate and enterprise spam filters, including those from Validity and Proofpoint, generate artificial opens and clicks by 'detonating' emails in sandbox environments to scan for malicious content.
- Pattern Recognition for Detection: Artificial engagement can be identified by opens and clicks originating from known security vendor IP ranges or data centers, extremely rapid and comprehensive click patterns, for example, all links clicked instantly, and multiple interactions from different IPs within seconds.
- Shift in Metric Reliability: Traditional open rates are significantly inflated by these automated actions, making click-through rates (CTR) and conversions more reliable indicators of genuine subscriber engagement.
Key considerations
- Prioritize Actionable Metrics: De-emphasize raw open rates and instead focus on click-through rates, click-to-open rates, and conversion data as more accurate measures of genuine subscriber interest and campaign performance.
- Analyze Source and Speed: Scrutinize email logs for opens and clicks originating from suspicious IP addresses, such as known security vendor ranges or data centers, and look for unusually rapid or simultaneous engagement across all links.
- Account for Client-Specific Behavior: Recognize that Apple Mail users will consistently show inflated open rates due to MPP, and Gmail's image proxying can also obscure true open intent; adjust your analysis accordingly for these segments.
- Leverage Geographic and IP Data: Utilize geolocational data to identify opens appearing from unexpected locations or known data center IP addresses, which often indicate bot or security scanner activity rather than human interaction.
Technical article
Documentation from Apple Support explains that Mail Privacy Protection (MPP) introduced with iOS 15 effectively pre-loads email content, masking users' IP addresses and creating artificial open signals. To identify these, marketers should be aware that open rates will be inflated for users on Apple Mail, and should focus on click-through rates and conversions as more reliable engagement metrics.
23 May 2023 - Apple Support
Technical article
Documentation from Mailchimp Knowledge Base explains that many email clients and security software use proxy servers to pre-fetch email content, leading to false opens. They suggest focusing on click rates and conversion data as more reliable indicators of engagement. Users can also analyze geolocational data for opens that appear to come from data centers or unusual locations, indicating bot activity rather than a user.
21 Dec 2021 - Mailchimp Knowledge Base
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