Why do spam filters click links in emails?

Spam filters and security systems click links to pre-scan content for malicious links, phishing attempts, or viruses before delivering the email to the recipient's inbox. This is a security measure to protect users.

How can I tell if a click is from a bot or a human?

Look for rapid clicks immediately after delivery, clicks from known data center IP ranges, or unusual user agent strings. Hidden honeypot links can also help confirm bot activity.

Do bot clicks harm my email deliverability?

Legitimate spam filter clicks usually don't directly harm deliverability. However, if your metrics are consistently inflated by bot activity, it can mislead your strategy and potentially lead to poor engagement with real users, which can indirectly impact sender reputation.

What is a "honeypot link" and how does it help?

A honeypot link is a link hidden from human visibility but accessible to bots. If a click is registered on this link, it indicates automated activity, allowing you to filter it from your true engagement metrics.

Should I remove bot clicks from my email reports?

Yes, filtering out bot clicks is recommended for accurate reporting. It provides a more realistic view of how human subscribers interact with your emails, which is crucial for optimizing campaigns and making informed marketing decisions.

Can bot clicks affect my automated email workflows?

Yes, if your automation triggers are based on clicks (e.g., lead scoring, segmentation), bot clicks can prematurely activate workflows or assign incorrect scores. Adjusting trigger timings and filtering bot activity can prevent this.

How to combat spam filter and bot clicks on emails? - Sender reputation - Email deliverability - Knowledge base

Email marketing is a powerful tool, but it comes with its share of complexities. One of the persistent challenges we face is distinguishing genuine recipient engagement from automated interactions, often generated by spam filters and various bots. These non-human clicks can significantly skew our analytics, making it difficult to gauge the true performance of our campaigns and the effectiveness of our strategies.

Understanding and combating these artificial clicks is crucial for maintaining data integrity and ensuring that our efforts are truly resonating with our human audience. It's not just about vanity metrics; accurate data informs crucial decisions about audience segmentation, content optimization, and budget allocation.

Understanding automated email interactions

Automated email interactions primarily come in two forms: security-driven clicks by spam filters or mail servers, and clicks from malicious bots. The former are far more common and usually originate from legitimate security systems that pre-scan emails to ensure they don't contain harmful content like malware or phishing links. These systems click every link to verify their safety before the email reaches the recipient's inbox.

This pre-scanning behavior, sometimes referred to as server clicks, is a standard practice across major mailbox providers such as

Google and

Microsoft. While beneficial for security, it artificially inflates click rates in our reports.

Typical behavior

Human clicks usually occur after a noticeable delay following delivery, allowing time for the email to be opened and read. Their engagement patterns appear natural and varied.

Latency: Clicks typically happen minutes or hours after receipt.
Browsers: Clicks originate from common web browsers and email clients.
IPs: IP addresses are usually residential or mobile network ranges.

Automated behavior

Bot clicks are often instantaneous, registering immediately upon delivery. They exhibit uniform, predictable patterns, frequently clicking all links simultaneously.

Speed: Clicks are recorded within seconds of delivery.
Environments: Clicks often come from data centers or cloud providers like Amazon Web Services.
User agent: Generic or outdated browser strings are frequently seen.

The primary impact of these bot clicks (or blocklist clicks) is on our email marketing metrics. Artificially inflated click rates can give a false sense of campaign success, leading us to misinterpret audience engagement and make inaccurate strategic decisions. This false data can lead to inefficient resource allocation and a misunderstanding of what truly resonates with our subscribers.

While legitimate security bot activity doesn't directly land your domain on a blacklist, consistently high volumes of clicks from unusual sources can sometimes trigger internal flags or contribute to a less-than-ideal sender reputation if not properly accounted for. It's about maintaining a clear, accurate signal of your sending health.

Identifying bot and spam filter clicks

Recognizing bot activity goes beyond looking at raw click numbers. I've found that paying close attention to specific indicators can help us pinpoint non-human engagement. The most telling signals are often the speed of the click, the originating IP address, and the user agent details associated with the click.

One of the most reliable indicators is the timestamp of the click. Bots tend to click links almost instantaneously upon receiving an email, often within a second or two of delivery. This rapid interaction is a strong red flag, as it's highly improbable for a human recipient to open, read, and click a link in such a short timeframe. This is a key method we use to identify artificial email opens.

Additionally, examining the IP address can reveal if clicks originate from known data centers or cloud providers, rather than typical residential or mobile networks. We've also noticed that filter clicks sometimes come from very outdated or generic user agent strings that don't correspond to common browser versions used by actual people.

Hidden link HTML snippetHTML

<a href="https://yourdomain.com/bot-trap" style="display:none !important; visibility:hidden !important; opacity:0; color:none;">Click here to confirm you're a bot</a>

A powerful technique to identify bots is by implementing a honeypot link. This is a link that's hidden from human visibility through CSS (e.g., set to display:none, or made the same color as the background), but is still clickable by automated systems. If this specific link registers a click, we can confidently assume it was a bot. This strategy helps us design programs to avoid counting bot engagement.

Strategies for accurate metrics

Once we've identified bot activity, the next crucial step is to mitigate its impact on our metrics and overall email program. The goal is to gain a clearer understanding of true human engagement, allowing for better campaign optimization and more accurate reporting.

Actionable filtering tips

Time-based filtering: Disregard clicks occurring within a few seconds (e.g., 3-10 seconds) of the email's arrival. This is a common practice among email service providers (ESPs).
IP address exclusions: Compile a list of known data center IP ranges (e.g., Amazon Web Services, Google Cloud) and exclude clicks originating from them.
User agent analysis: Look for outdated or generic user agents that don't correspond to typical human browser behavior.
Hidden link tracking: Track clicks on your honeypot links and automatically mark those as bot interactions.

Once identified, you should filter out bot clicks from your reports. This provides a clearer picture of human engagement, allowing for better campaign optimization. Additionally, if your marketing automation relies on clicks, adjust workflows to account for bot behavior. For instance, a lead scoring system might not award points for immediate, bot-like clicks.

Maintaining a healthy sender reputation

A clean email list is fundamental to good email deliverability. Regularly removing unengaged subscribers reduces the chances of your emails being sent to inactive or problematic addresses that might trigger more spam filter scans or spam traps. This proactive list hygiene minimizes the overall noise in your data.

Implementing a double opt-in process ensures that only genuinely interested subscribers are added to your list, significantly reducing the likelihood of bot sign-ups. This helps maintain a higher quality recipient base, which positively impacts deliverability and provides more reliable engagement data, free from unwanted blocklist activity.

Views from the trenches

Best practices

Implement time-based filtering to disregard clicks occurring within 3-10 seconds of email delivery.

Create hidden links in emails (honeypots) that only bots would click, allowing for their identification.

Regularly clean your email list to remove unengaged or suspicious subscribers.

Filter out clicks from known data center IP ranges, such as Amazon AWS or Microsoft Azure.

Common pitfalls

Relying solely on IP address filtering, as bot IPs can be dynamic and rotate frequently.

Failing to adjust automation triggers, leading to incorrect lead scoring or segmenting.

Not distinguishing between malicious bots and legitimate security scanners.

Ignoring user agent data, which can provide clues about non-human activity.

Expert tips

Analyze HTTP header elements like User Agent and Referer for patterns indicative of bot activity.

Consider the overall email engagement trends rather than individual click anomalies.

Use a double opt-in process to reduce bot sign-ups and improve list quality.

Segment your audience to understand how bot clicks might affect different groups.

Marketer view

Marketer from Email Geeks says: We used to try recognizing bot clicks by looking at timestamps, knowing most occur within a second or two of delivery, leading us to delay what we considered a valid click by that timestamp.

2019-11-01 - Email Geeks

Expert view

Expert from Email Geeks says: Filtering clicks that happen before the delivery response is crucial for accurate metrics.

2019-11-01 - Email Geeks

Moving forward with confidence

Combating bot and spam filter clicks is essential for accurate email marketing analytics and maintaining a strong sender reputation. By implementing intelligent identification and mitigation strategies, we can gain a clearer understanding of our audience's true engagement and make more informed decisions.

It's an ongoing process that requires vigilance and adaptation as bot technologies evolve. Regularly review your data, refine your filtering methods, and prioritize maintaining a clean and engaged email list. This proactive approach will help you maximize your email program's effectiveness and avoid the pitfalls of misleading data, even when faced with a spam blacklist.