Summary
The question of whether spam traps generate opens and clicks is a nuanced one within the email deliverability community. While traditional spam traps (often referred to as 'honeypots') are primarily designed to identify and penalize senders with poor list hygiene or malicious intent, some forms of automated interaction, including opens and clicks, can occasionally be associated with them. It's crucial to differentiate between activity from genuine spam traps, which are often passive, and automated interactions from spam filters or security scanners, which are designed to analyze email content, including links and tracking pixels.
Key findings
- Passive nature: Many traditional spam traps are designed to remain passive, simply receiving emails without engaging in opens or clicks. Their primary function is to catch senders mailing to invalid or suspicious addresses, leading to blocklistings and reputation damage.
- Investigation-driven activity: Some sophisticated spam trap networks or anti-spam systems may occasionally 'chase' links within emails as part of an investigation into the content, malware, or phishing attempts. This activity is not random but rather a deliberate security measure.
- Distinction from spam filters: False positives in open and click data are more commonly generated by security scanners and spam filters, which pre-fetch content and click links to check for malicious payloads, rather than by the spam traps themselves. This is a common source of confusion for marketers. For more information, see our guide on how to identify artificial email opens and clicks.
- Impact on metrics: While spam traps themselves might not frequently generate random engagement, their presence on your list indicates poor list hygiene, which severely impacts deliverability and can lead to your emails being flagged as spam or your domain getting put on a blocklist. Read our guide on what spam traps are and how they work.
Key considerations
- Focus on list hygiene: Regardless of open/click activity, hitting spam traps is a clear sign of issues with your email list. Prioritise regular list cleaning and robust acquisition practices to avoid them.
- Understand data anomalies: If you observe unusual open or click patterns, especially from specific IP ranges or at odd hours, investigate whether these are from spam filters or security systems rather than active spam traps. This can help prevent misinterpretations of your engagement metrics.
- Implement strong opt-in processes: Using double opt-in can significantly reduce the chances of acquiring spam trap addresses. While some argue that even double opt-in can occasionally hit spam traps (due to bot sign-ups, for example), it's generally a strong preventative measure. Find out more about how to avoid spam traps.
- Monitor blocklists and sender reputation: Regularly check your sender reputation and monitor major blocklists (or blacklists) to quickly identify if your sending practices are leading to spam trap hits. Early detection allows for faster remediation and protection of your deliverability.
What email marketers say
Email marketers often observe anomalies in their open and click rates, sometimes mistakenly attributing these to spam traps. The general sentiment among marketers is one of confusion and frustration when encountering unexpected engagement, especially from what appear to be non-human sources. While some understand the distinction between spam traps and security scanners, many grapple with how to accurately interpret their engagement metrics in the presence of automated interactions.
Key opinions
- Confusion over data spikes: Marketers frequently report seeing inexplicable spikes in open or click rates, particularly shortly after sending, and wonder if these are related to spam traps or other automated systems.
- Attributing to spam traps: There's a common misconception that spam traps are actively engaging with emails by opening them or clicking links, leading to distorted engagement data. Marketers sometimes misinterpret bot activity as spam trap interaction.
- Impact on reporting: Inaccurate open and click data, regardless of its source (spam trap or security scanner), complicates performance analysis and strategy adjustment for email campaigns.
- Desire for clarity: Many marketers seek clearer ways to distinguish between genuine user engagement and automated interactions to ensure their metrics are truly reflective of audience behavior. Our guide on how to avoid false email click and open data provides insights.
Key considerations
- Segment bot activity: Develop methods to identify and filter out bot-generated opens and clicks from your legitimate engagement metrics. This can involve analyzing IP addresses, user-agent strings, and interaction timing.
- Prioritize inbox placement: Instead of obsessing over artificial opens/clicks, focus on core deliverability issues like list hygiene to ensure your emails reach the inbox effectively. Read more about avoiding the spam folder.
- Educate teams: Ensure marketing teams understand the difference between spam traps (passive detection) and security scanners (active content checking) to prevent misdiagnosis of deliverability problems.
- Implement robust signup verification: Strengthen your signup forms with CAPTCHAs and other bot prevention measures to reduce the influx of invalid or spam trap addresses. This also reduces spambots submitting real emails.
A marketer from Email Geeks notes how challenging it is to determine if unusual click activity is from actual users or automated systems. They often see bursts of clicks immediately after sending, which seem too fast to be human interaction. This makes it difficult to trust the engagement metrics, especially when trying to segment audiences based on their behavior.
A marketer from Quora expresses concern about inflated open and click rates. They explain that these false positives skew their A/B testing results and make it harder to justify email marketing ROI to stakeholders. It leads to a constant need to manually review data and attempt to filter out non-human activity, which is time-consuming and imperfect.
What the experts say
Deliverability experts generally agree that traditional spam traps are not designed to generate random opens or clicks for the purpose of skewing data. Their primary role is passive detection. However, there's a clear distinction made between the behavior of spam traps and that of anti-spam systems, security tools, and bots, which *do* generate automated interactions as part of their content analysis or malicious activity.
Key opinions
- Rare and purposeful interaction: Experts confirm that while some highly sophisticated spam trap networks might occasionally interact (e.g., clicking a confirmation link), such instances are exceedingly rare and occur for specific investigative purposes, not to randomly inflate metrics.
- Not designed to skew data: The core function of spam traps is to identify poor sending practices, not to interfere with sender analytics. Any interaction is typically a byproduct of security checks, not a deliberate attempt to mislead marketers.
- Misattribution of activity: Many opens and clicks blamed on spam traps are in fact generated by spam filters, antivirus software, or other automated security systems that pre-scan emails for malicious content before delivery.
- Clear distinction: It is crucial for senders to understand the fundamental difference between passive spam traps and active security scanners to correctly diagnose deliverability issues and analyze engagement data.
Key considerations
- Understand the purpose: Remember that spam traps are primarily for identifying compromised sending infrastructure or poor list acquisition, not for inflating engagement metrics. Their presence signals a need for list hygiene improvements.
- Isolate bot activity: Focus on identifying and mitigating the impact of automated clicks and opens from security scanners. Techniques include analyzing IP addresses, user agents, and rapid succession clicks. This directly impacts how ISPs track engagement.
- Consult authoritative sources: Refer to reputable sources in the email industry, such as industry blogs and deliverability experts, to stay informed on the nuances of spam trap behavior and automated interactions. A good resource is Only Influencers articles on deliverability.
- Continuous list maintenance: Proactive list cleaning, including removing inactive subscribers and hard bounces, remains the most effective strategy to avoid spam traps, regardless of whether they click or not.
An expert from Email Geeks indicates that very few of their spam traps generate opens or clicks. They explain that the primary goal of these traps is to identify problematic mailing practices, not to engage in active interaction that would skew sender data. Any perceived engagement is usually a side effect of other security systems.
An expert from WordToTheWise elaborates that while some automated systems might click links to scan for malware, this behavior should not be confused with spam traps themselves. They emphasize that spam traps are passive instruments designed to detect poor list hygiene or illegal list acquisition, rather than generating false engagement metrics for marketers.
What the documentation says
Official documentation from various anti-spam organizations and email service providers (ISPs) typically defines spam traps as inactive email addresses used purely for identifying abusive senders. These documents rarely describe spam traps as entities that actively generate random opens or clicks. Instead, they focus on their detection capabilities and the consequences for senders who hit them, such as reputation damage and blocklistings.
Key findings
- Purpose of detection: Documentation consistently states that spam traps are deployed to catch senders who use scraped, purchased, or outdated email lists. Their primary goal is to maintain a clean email ecosystem, not to provide engagement data.
- Passive monitoring: Most documentation implies a passive role for spam traps, where their mere receipt of an email is sufficient to flag a sender. Active interaction like opens or clicks is not typically described as a standard behavior.
- Emphasis on list hygiene: The focus in official guides is always on prevention through robust list hygiene, implying that avoiding sending to these addresses altogether is the core strategy, irrespective of any potential, rare interactive behavior.
- Impact on sender reputation: Documentation often highlights the severe consequences of hitting spam traps, such as damage to sender reputation and potential blocklisting, underscoring their significance as a deliverability threat. For example, Mailchimp's documentation on spam traps clarifies their function.
Key considerations
- Adhere to best practices: Follow documented best practices for email acquisition and list management to minimize the risk of hitting spam traps. This includes permission-based marketing and regular list cleaning.
- Understand distinct functions: Recognize that the purpose of spam traps (detection of bad senders) is distinct from the function of security scanners (content analysis). This understanding is key to accurate troubleshooting.
- Prioritize list validation: Documentation often implicitly or explicitly supports the use of email validation services to filter out known spam traps and invalid addresses before sending, thereby protecting sender reputation. This is critical for improving deliverability with email validation.
- Monitor deliverability metrics: Utilize available tools and documentation from ISPs and anti-spam organizations to monitor your email deliverability, including bounce rates and complaint rates, which are direct indicators of list health and potential spam trap hits.
Documentation from OneSignal explains that spam traps are email addresses designed to catch spammers and identify poor list hygiene. They elaborate that these traps may consist of random combinations of letters, numbers, or symbols, appearing unlikely for a genuine email address. Their primary function is to serve as tripwires for unsolicited mail, not to actively engage with content via opens or clicks.
Mailchimp's documentation defines spam traps as email addresses used by ISPs and anti-spam organizations to find senders mailing to outdated contacts. This definition underscores the passive nature of these addresses, focusing on their role in identifying list quality issues rather than any active engagement that would influence open or click rates. They are primarily a detection mechanism.
