Why do spam filters open emails?

Spam filters (also known as blocklists) open emails and click links as a security measure to scan for malicious content like malware, phishing attempts, and spam. This proactive scanning ensures the safety of the recipient's inbox before the email is delivered.

How can I differentiate between a bot click and a human click?

You can differentiate between bot and human clicks by looking for specific patterns in your data: Timestamps: Bots often click immediately upon or even before delivery. Click patterns: Bots frequently click every link in an email simultaneously. IP addresses: Look for clicks originating from known data centers or security vendors (e.g., Barracuda, Microsoft, Google).

Does artificial engagement hurt my sender reputation?

Generally, no. Artificial engagement from spam filters is typically a sign that security systems are functioning as intended. It doesn't directly harm your sender reputation, as these are legitimate (though automated) interactions. Your sender reputation is more impacted by factors like spam complaints, bounce rates, and email authentication practices (SPF, DKIM, DMARC).

What should I focus on if open and click rates are unreliable?

If open and click rates are unreliable due to artificial engagement, focus on downstream metrics that reflect genuine interest and conversions. These include website visits from email links, purchases, form submissions, replies to your emails, and overall lead generation or sales figures. These metrics provide a more accurate picture of your email campaign's real business impact.

How to identify artificial email opens and clicks generated by spam filters? - Technical - Email deliverability - Knowledge base

As email marketers and deliverability professionals, we rely heavily on metrics like open and click rates to gauge campaign performance and audience engagement. However, a growing challenge is the presence of artificial engagement, primarily generated by sophisticated spam filters and security tools. These automated interactions can significantly inflate your reported numbers, making it difficult to understand true subscriber behavior.

Identifying these false positives is crucial for accurate data analysis and informed decision-making. If you've ever seen an email report with an unusually high open rate (sometimes over 90%) or clicks occurring before the email was even delivered to the recipient, you're likely encountering artificial engagement. I'll walk you through how to spot these patterns and what steps you can take to get a clearer picture of your email performance.

How spam filters operate

Email security gateways and spam filters (also known as blocklists) are constantly evolving to protect users from malicious content. One common method they employ is to pre-scan incoming emails. This involves automatically opening the email and clicking on all embedded links to check for phishing attempts, malware, or other security threats. This proactive scanning is designed to ensure the safety of the recipient before the email even lands in their inbox.

Barracuda Networks, for example, has been known to proactively click links in emails as part of its security protocols. This behavior is well-documented and can often lead to inflated click and open rates in your email service provider's reports. Many of these security scans might originate from cloud-based infrastructure, such as Amazon Web Services (AWS) or similar platforms, where many enterprise email security solutions are hosted.

Beyond Barracuda, other major providers, including

Google and

Microsoft, also employ various forms of automated scanning, particularly for their enterprise and educational clients. This means that while your numbers might look great, a portion of that engagement isn't from human interaction. Understanding this underlying mechanism is the first step in accurately interpreting your data.

Spotting synthetic interactions

While distinguishing between human and bot activity isn't an exact science, several indicators can help you spot artificial engagement. The most significant red flag is the timing of opens and clicks relative to delivery. If you see opens and clicks recorded moments, or even seconds, before the email is logged as delivered, it's a strong sign of automated scanning. Real users simply can't interact with an email before it reaches their inbox.

Typical human behavior

Varied timing: Opens and clicks occur at different times of day, reflecting individual schedules.
Selective clicks: Users click on specific links of interest, not every link in the email.
Organic patterns: Engagement varies across campaigns and subscriber segments.

Automated patterns

Instant interaction: Opens and clicks happen milliseconds apart, often before delivery. This is a primary indicator, as outlined in an article on distinguishing human from bot clicks.
All links clicked: Bots often click every single link in an email, regardless of content.
Consistent source: Clicks come from a small range of IP addresses, often associated with data centers or specific security vendors.

If you have access to raw data, examine the user agents associated with opens and clicks. Bots often use generic or recognizable user agent strings. Also, look at the IP addresses. If a significant number of opens and clicks come from the same few IP addresses, especially those not tied to individual users but rather to known data centers or security providers, it's a strong indicator of bot activity. For example, a high volume of activity from ess.barracuda.com in your MX records is a clue that Barracuda is scanning your emails. More insights on this can be found at Word to the Wise's article on Barracuda's behavior.

Cleaning your engagement data

The goal isn't necessarily to stop these automated scans, as they are part of modern email security. Instead, focus on minimizing their impact on your data and improving your analytical approach. Many email service providers (ESPs) now offer features to automatically filter out known bot activity. If yours doesn't, or if you need a more granular approach, manual data cleaning is an option.

Practical data cleaning steps

Analyze timestamps: Filter out opens/clicks that occur immediately upon delivery.
Segment by IP/User Agent: Create segments that exclude known bot IP ranges or suspicious user agents. This is part of how to identify and filter bot clicks from reports.
Focus on unique clicks: Pay more attention to unique clicks rather than total clicks, as bots often click multiple times.
Prioritize conversions: Ultimately, metrics like conversions, website visits, and purchases provide a more accurate measure of real engagement. Understanding how to accurately measure email engagement despite bot interference is key.

It's important to remember that artificial engagement, while annoying, doesn't necessarily hurt your sender reputation directly. Spam filters are doing their job to protect recipients. The primary issue is the skewed data it presents to marketers. If your deliverability is suffering, it’s more likely due to other factors such as sending to unengaged lists, high bounce rates, or being listed on a blocklist. Being on a blocklist or blacklist can significantly impact whether your emails reach the inbox. You can learn more about what it means to be blacklisted for your email program.

By actively identifying and filtering out this artificial engagement, you can gain a much more realistic view of your email marketing effectiveness. This allows for better campaign optimization, more accurate A/B testing, and a clearer understanding of your audience's true interests.

Advanced analysis and the future

Beyond basic filtering, some advanced techniques can help you refine your understanding of bot activity. One method involves setting up 'honey pot' links or hidden pixels that are only visible to bots or automated scanners, not human users. If these specific links or pixels show activity, you have definitive proof of bot engagement.

Indicator	Description	Typical bot pattern
User agent	Software string identifying the client making the request.	Generic strings, security software names, or unusual formats.Identifying bot user agents is a core technique.
IP range	Network address of the device performing the open/click.	Consistently from data centers (AWS, Azure) or security vendors.
Click timestamps	Time of interaction relative to email delivery.	Immediately upon or even before delivery, often within milliseconds of each other.
Link activity	Which links within the email are clicked.	Clicks on every link (including hidden ones), or generic links like 'view in browser'.
Unsubscribe behavior	Automated clicks on the List-Unsubscribe header.	Certain security filters, particularly from Microsoft, will click this link as part of their scan.This behavior by Microsoft/Outlook domains is a known characteristic.

The landscape of email privacy and security is constantly changing. With initiatives like Apple Mail Privacy Protection, open rates are already becoming less reliable as a direct measure of engagement due to pre-fetching. This makes the ability to understand and segment artificial engagement even more critical for marketers aiming to understand their true audience.

Your ESP plays a vital role here. Many modern platforms are actively developing and improving their methods to reliably distinguish human from bot activity. Keep an eye on their reporting features and consider integrating your email data with broader analytics platforms for a holistic view of user behavior.

Views from the trenches

Best practices

Always analyze click timestamps relative to delivery to identify pre-delivery interactions.

Segment your audience based on engagement patterns to isolate potential bot activity.

Prioritize downstream metrics like conversions, website visits, and purchases.

Common pitfalls

Solely relying on open and click rates without considering artificial engagement.

Misinterpreting high engagement rates as genuine subscriber interest.

Ignoring unusual click patterns, such as all links being clicked simultaneously.

Expert tips

Set up alerts for unusual activity spikes in your email marketing platform.

Use unique tracking parameters for critical links to differentiate human clicks.

Consider implementing DMARC to enhance sender reputation and reduce spam perception.

Marketer view

Marketer from Email Geeks says they have definitely observed excessive opens and clicks from security filters, especially Barracuda, even before emails are formally accepted by the recipient's server.

2018-10-03 - Email Geeks

Marketer view

Marketer from Email Geeks says that large numbers of opens and clicks originating from Amazon.com or AWS servers can indicate Barracuda spam filter activity, as Barracuda is often hosted there.

2018-10-03 - Email Geeks

Refining your email strategy

Understanding and accounting for artificial email opens and clicks is no longer optional for accurate email marketing analysis. While spam filters and security bots play an essential role in protecting recipient inboxes, their automated behaviors can significantly skew your engagement metrics.

By applying the identification techniques discussed, such as analyzing timestamps, IP addresses, and user agents, and by implementing strategies to filter or segment this data, you can achieve a more precise understanding of your audience's true engagement. This precision empowers you to make better strategic decisions, optimize campaigns more effectively, and ultimately drive genuine results.