How can I identify bot user agents in my email click data?
Matthew Whittaker
Co-founder & CTO, Suped
Published 22 Apr 2025
Updated 19 Aug 2025
9 min read
Understanding who is clicking your email links is essential for accurate marketing insights and maintaining a healthy sender reputation. However, not all clicks come from human recipients. Automated bots, often deployed by internet service providers (ISPs) or security services, can interact with your emails, generating false positive clicks that skew your engagement metrics.
These bot clicks can inflate your click-through rates, making campaigns appear more successful than they are, or worse, they can trigger spam traps and damage your sender score if not properly identified and handled. Differentiating between legitimate user engagement and automated activity is a critical skill for any email marketer or deliverability specialist.
One of the most effective ways to identify these non-human interactions is by analyzing the user agent data associated with each click. User agents provide information about the client (browser, operating system, or bot) that initiated the click. By recognizing patterns and specific strings, you can begin to filter out unwanted bot activity and gain a clearer picture of your actual audience engagement. This process is key to preventing false email click and open data from anti-spam bots.
Understanding user agents
A user agent is a string of text that a client sends to a server to identify itself. When a browser, email client, or bot clicks a link in your email, it transmits this string to your tracking server. For instance, a typical web browser will send a user agent string that includes details like the browser name and version, operating system, and sometimes the device type. For example, a common string might look like Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36.
Bots, on the other hand, often have distinct user agent strings that immediately signal their automated nature. These strings can be very generic, contain specific keywords, or lack the complexity of a human-driven browser. Identifying these helps in recognizing automated scripts and crawlers.
Some bots may even try to spoof common browser user agents to appear legitimate, but their behavior (e.g., rapid, sequential clicking of all links in an email) can often give them away. It is crucial to collect and analyze this user agent data from your email click logs or your email service provider's (ESP) analytics. Most ESPs provide this data, even if they also offer their own bot filtering. For a comprehensive list of known bot user agents, you can consult resources like the Ultimate List of Crawlers and Known Bots.
Key indicators of bot activity
Beyond the user agent string itself, several other indicators can help you spot bot activity. Behavioral patterns are often a strong giveaway. For instance, if an email is opened and all links within it are clicked simultaneously or within a few milliseconds, it's a clear sign of automated behavior rather than human interaction. Bots often scan emails for malicious content or to pre-fetch linked pages.
Another common tactic for identifying bots is by looking at the associated IP addresses. Security scanners and spam detection bots (or even web scrapers) often originate from known data centers or IP ranges associated with automated services. While an IP address alone isn't definitive proof, combining it with user agent data strengthens your ability to confirm bot activity. You can also use invisible links to identify bot clicks.
You might also encounter user agents from security software, corporate email proxies, or internal tools used by companies to scan incoming emails. These can include strings from services like Barracuda Sentinel (EE), Microsoft Exchange, or even Office 365 Connectors. Recognizing these helps you refine your email reputation by accurately distinguishing real engagement.
Practical identification methods
There are several practical ways to identify and isolate bot user agents in your email click data. The first step is to ensure you're collecting comprehensive click data, including the user agent string and the IP address. Most ESPs provide this as part of their analytics, sometimes even offering built-in bot filtering, but you can also log this data on your own web server if you control the link destination.
Once you have the data, you can analyze it for patterns. Look for user agent strings that clearly indicate a bot, such as those containing bot, crawler, spider, or specific software names like python-requests (often indicating a script). You can also build a list of known bot user agents and use them to filter your data. Reputable sources like WhatIsMyBrowser.com’s User Agent database can be invaluable here. Implement these techniques to mitigate the impact of bot clicks.
Another strategy involves creating honeypot links within your emails, which are hidden from human view but accessible to bots. Any click on these links is a definitive sign of bot activity. By combining user agent analysis, IP address checks, behavioral pattern recognition, and honeypot tactics, you can significantly improve the accuracy of your email click data.
Impact on email metrics and deliverability
The presence of bot clicks can significantly distort your email marketing metrics. An inflated click-through rate might give you a false sense of campaign success, leading to misinformed strategic decisions. More importantly, consistent bot activity can negatively impact your sender reputation, making it harder for your legitimate emails to reach the inbox. ISPs and email providers use various signals, including engagement rates, to assess sender trustworthiness. If bot clicks are falsely inflating your engagement, it can mask real issues or signal suspicious activity.
Accurate click data is vital for understanding what resonates with your audience, optimizing subject lines, call-to-actions, and content. When bot clicks are filtered out, you gain a clearer picture of true subscriber engagement, enabling you to make data-driven decisions that genuinely improve your campaign performance and deliverability. This also helps in avoiding common issues like getting listed on a blocklist (or blacklist) due to perceived spammy behavior.
Moreover, certain types of bot activity can expose your email program to risks. For example, if a bot clicks on a link and then navigates to multiple pages on your site, it could impact your server load or skew website analytics. By proactively identifying and filtering bot user agents, you can protect your infrastructure and ensure your metrics reflect human interaction, leading to better email deliverability and more effective marketing strategies. Understanding how ESPs distinguish human vs. bot interactions is also helpful.
Views from the trenches
Regularly monitor: review your email click logs for unusual patterns or suspicious user agents. Many ESPs offer reporting that includes this data, or you can capture it on your own web server.
Segment your data: separate bot clicks from human clicks in your analytics. This provides a more accurate view of your actual engagement and helps in increasing email click-through rates.
Utilize hidden links: embed invisible links that only bots would click. Any interaction with these links flags the click as non-human.
Collaborate with your ESP: many email service providers are developing advanced bot detection features. Leverage these tools to automatically filter out known bot activity.
Refining your email insights
Best practices
Implement server-side logic to analyze user agent strings and IP addresses in real-time for immediate bot filtering.
Maintain a dynamic list of known bot user agents and IP ranges, updating it regularly based on observed traffic patterns.
Cross-reference click timestamps with the email send time; very rapid clicks after sending are often bot-generated.
Use A/B testing with slight variations in link structure to see if bot behavior changes, which can indicate detection methods.
Filter out clicks from IPs belonging to known security companies or cloud providers that scan emails.
Common pitfalls
Over-filtering legitimate clicks by being too aggressive with user agent blacklists, leading to underreported engagement.
Ignoring bot click data, resulting in skewed analytics and poor optimization decisions for campaigns.
Relying solely on user agent strings without considering behavioral patterns or IP data, as bots can spoof user agents.
Not regularly updating bot detection rules, allowing new or evolved bots to bypass existing filters.
Mistaking automated clicks from legitimate security scanners for malicious bot activity, which can lead to unnecessary remediation.
Expert tips
A simple method to start is to flag any user agent string that does not begin with 'Mozilla', as this often indicates bot activity.
Be aware that user agents like 'python-requests' indicate someone is running a script against your link, which is automated.
Pay attention to 'Amazon CloudFront' user agents; these are frequently associated with Microsoft Outlook protection services.
It's helpful to research the IP address of suspicious clicks; sometimes they can be traced back to known bot networks or data centers.
For very specific analysis, track the full user agent string, not just snippets, as subtle differences can distinguish bots.
Marketer view
A marketer from Email Geeks says they noticed that anything not starting with 'Mozilla' seems to be a bot when analyzing user agent data from clickers.
2023-06-27 - Email Geeks
Expert view
steve589 from Email Geeks says they found that 'Amazon CloudFront' user agents are often tied to domains with MX records pointing to protection.outlook.com, which can introduce irony into the data.
2023-06-27 - Email Geeks
Identifying bot user agents in your email click data is a continuous process that requires vigilance and a multi-faceted approach. By understanding what user agents are, recognizing suspicious patterns, and employing various identification techniques, you can significantly improve the accuracy of your email analytics. This, in turn, allows for more informed marketing decisions, stronger sender reputation, and ultimately, better email deliverability.
The insights gained from clean, human-only click data are invaluable for optimizing your email campaigns and ensuring your messages truly resonate with your audience. Remember that the landscape of bot activity is always evolving, so staying updated on new user agent strings and bot behaviors is crucial for long-term success.
