Why bot clicks are a problem
Bot clicks are automated interactions generated by security systems (like spam filters or link scanners) before an email even reaches the recipient. These bots are often designed to scan all the links in an email to ensure they’re safe—but they inadvertently trigger "click" events that ESPs record as real engagement.
This creates multiple problems:
Artificially high CTRs: Your click-through rate may jump to 80–100% within seconds of sending an email. It looks impressive—but it’s not real.
False signals: If you’re using clicks to trigger follow-up actions (like personalized journeys), bot clicks can send people down the wrong paths and trigger follow-up emails that don’t make sense to the recipients.
Skewed A/B testing: Bots clicking every version of a CTA can wreck your ability to test what’s actually performing best, making it harder for you to understand which one is the better version of your email.
Types of bot activity
Here are some common ways bots interact with your emails so you can better understand what to watch out for:
Pre-fetching and link scanning
Many email security systems prefetch links in emails to check for malicious content. While this improves security, it can register as a click in your analytics, even though no human has interacted with the email.
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Security vendors like Proofpoint or Barracuda sometimes rewrite URLs to monitor and filter links. These rewritten links can still trigger clicks, complicating your tracking and reporting.
Email opens without loading images
Some bots open emails without rendering images or executing scripts. While the email actually gets opened, the engagement or opening of the email doesn't get recorded.
Rapid or sequential link checks
Bots often click multiple links in quick succession. This bulk clicking can create patterns that are clearly unnatural, such as sub-second delays between clicks or sequential clicks on all links.
Tactics to identify and manage bot clicks
Here are some practical steps you can take to identify and manage bot activity in your emails:
Identify distinct bot patterns
Bots behave differently from people in ways you can measure. Spotting those patterns makes it much easier to separate real clicks from automated noise.
Common indicators
Clicks appear immediately after delivery (typically 0–5 seconds)
Several links are clicked in rapid sequence, often within milliseconds of each other
Clicks are recorded even though the email was never opened
Clicks come from server IPs tied to security vendors such as Proofpoint, Barracuda, Mimecast, Microsoft SafeLinks, or Google Security
To fix it, track metadata for every click, including timestamps, IP addresses, and user-agent strings, and use this information to flag or filter interactions that match typical bot behavior.
Many bots also identify themselves through the User-Agent header, so maintaining an updated list of known scanners and automated libraries (e.g., curl, python-requests) allows you to exclude or mark suspicious requests, ensuring your metrics reflect actual user engagement.
Add tracking parameters to links
Adding unique parameters allows you to map every click back to the exact recipient, email, and link. Include identifiers such as email ID, recipient ID, and link ID.
When you notice unusual patterns like the same link being clicked by multiple recipients at the exact same timestamp, you can more easily flag suspicious behavior.
Tracking parameters also simplify correlation with server-side logs and analytics, making automated detection more accurate.
Introduce a JavaScript Layer (Human Verification)
Many bots do not execute JavaScript, making a lightweight verification step an effective way to confirm human clicks. When a recipient clicks a link, redirect them first to a verification page.
On this page, JavaScript can:
Set a cookie to mark a verified user
Perform a brief timed redirect (e.g., ~300 milliseconds) to the intended destination
Only log the click as “human” after these checks
Keep the JavaScript minimal, as some email clients disable scripting. This method allows you to filter out bot activity without impacting legitimate users while improving the accuracy of your engagement metrics.
Analyze header and behavior indicators
Bots often make requests that deviate from normal browser behavior. Common signals include missing standard browser headers (like Accept-Language), no cookies sent or returned, no JavaScript execution on the landing page.
Tracking these behaviors at the landing page allows you to flag clicks as suspicious without affecting legitimate users.
Use click maps
Many email service providers (ESPs), such as Mailmodo, offer a “click map” view that helps you visually understand where people are clicking in your emails. The click map overlays click data directly onto your email template so you can immediately see which links or buttons are drawing attention.
In Mailmodo, you access this by opening a sent campaign and selecting the “Clickmaps” tab. On one side, you see a list of links used in the email with metrics like number of clicks or percentage of total clicks, and on the other side, you get a preview of the email template, with clickable areas highlighted so you can see exactly where recipients clicked.
Click maps can help you spot suspicious or otherwise suspicious-looking patterns that might indicate bot activity. For example, if footer links or social icons (which you expect to have lower visibility) show unusually high click counts, that could be a sign that automated scanners, not real readers, are clicking.
Final thoughts
Even the most carefully planned campaigns can be affected by bot clicks, but identifying and managing them is entirely possible. Taking steps like tracking metadata, monitoring timing patterns, and segmenting suspicious activity ensures your metrics stay accurate.
Once you clean up your data, your engagement reports reflect the real behavior of your audience. That clarity allows you to improve your content, refine your strategies, and confidently invest in what works.