Omeda’s click bot data, research and detection explained in one place
Estimated reading time: 11 minutes
Most media email teams know bot clicks are a problem. However, bot clicks are a bigger problem than most dashboards show. This is Omeda’s full view — built from the data we see across billions of emails every year.
What is a bot click?
If you send email at any kind of scale, you already know your click data has a problem. The clicks are real. The clickers aren’t.
A bot click — sometimes called a non-human interaction (NHI), click bot, or fake click — is any automated click on an email link generated by software rather than a human reader. Most of the time, the culprit isn’t bad actors. It’s the enterprise email security tools sitting between your send and your subscriber’s inbox.
Products like Mimecast, Proofpoint, and Barracuda pre-scan every link in every incoming message before delivery, checking for malicious content. They aren’t evil, they’re doing their job. The problem is that their clicks often show up in your metrics looking exactly like human engagement — inflating click-through rates, corrupting engagement scores, and wrecking the behavioral data that your automation and segmentation depend on.
Other sources include spam bots that click to confirm live addresses, link prefetchers built into email clients, and scripts running from data-center infrastructure like AWS and Google Cloud.
Not all bots behave the same way. Security scanners are systematic — they click every link, every time, before delivery. Spam bots are opportunistic, clicking to confirm live addresses or trigger automated responses. The distinction matters because the fix for one doesn’t work on the other.
How big is the bot click problem?
87.3%
of all recorded click activity across Omeda’s platform in Q1 2026 came from non-human sources — across 1.77 billion emails processed.
Bot click share isn’t evenly distributed. Events, whitepapers, research, and webinar sends all came in above 96% bot share. Newsletters landed at 82.4%. Those aren’t comparable numbers, and they shouldn’t be treated as such. A raw click rate on a whitepaper campaign and a raw click rate on a newsletter are measuring very different things.
The full breakdown by email type is in the Q1 2026 Email Engagement Benchmark Report. The bot click section is worth reading carefully if click data plays any role in how you report performance — or how you structure automation.
Should I suppress fast clicks?
There’s advice circulating right now that goes something like this: if a click happens within five seconds of send, suppress that subscriber. It’s a bot. Problem solved.
It’s not. That logic fails in both directions — and following it makes your data worse, not better.
Security bots don’t only click fast
Enterprise security scanners don’t have a uniform behavior pattern. Yes, some click at the moment of delivery. But these products also re-index on their own schedule — they may go quiet for a week or a month, then resurface and rerun the scan. You’ll see huge spikes in click data that have nothing to do with your audience, on a delay, with no reliable pattern. A time-window filter around delivery catches some of those and misses others.
Some fast clicks are real people
Someone opens your email on their phone while waiting for a meeting to start and taps a link in three seconds. A blanket five-second suppression rule just removed them from your list — and from future sends they were actually reading.
The right response to fast clicks
The right response to a fast click is to evaluate the full click pattern around that recipient and that deployment — not to remove the subscriber from your list. Filtering a bad signal and penalizing a real person are not the same action.
How Omeda detects bot clicks
Omeda doesn’t use a time-based threshold. The platform runs a behavior-based detection algorithm that evaluates click behavior with each email that’s delivered — the question it answers for every single click event is simply: human, yes or no?
The detection model runs ten distinct rules across behavioral, statistical, and infrastructure categories. Each rule specifies not just whether to flag a click, but how aggressively to act on it.
| What Omeda looks for | What gets removed |
|---|---|
| Two clicks within 2 seconds | Offending click only |
| 10+ clicks within 30 seconds | All clicks from that recipient |
| Fake click share exceeds 50% | Selective removal based on confidence |
| Unique source IPs exceed 12 | All clicks |
| Total clicks exceed 200 | All clicks |
| Unique user agents exceed 9 | All clicks |
| User agent matches known scanner list | Offending click only |
| Source IP on client ignore list | Offending click only |
| Source IP on Omeda’s bot list | Offending click only |
| Link clicked within 5 seconds of send | Offending click only (not the subscriber) |
A few things worth noting for the table above:
- “Offending click” means only the specific click that triggered the rule is removed.
- “All clicks” means every click from that recipient on that deployment is invalidated — because the pattern is unambiguous.
- “Selective removal” means additional scrutiny kicks in and removal is proportional to confidence level.
- Notice what’s not in the table: suppress this subscriber. A click arriving within 5 seconds removes the click event, not the person. They stay on your list.
The full methodology — including all ten rules, reason codes, and report field definitions — is documented in the Omeda Knowledge Base.
Example
If you send an email to a subscriber at a corporate domain, the first five clicks that come back might all be the security product pre-scanning every link before the message reaches the inbox. The algorithm catches them, flags them as non-human, and passes the one real click through. Both the bot activity and the human click appear in Omeda’s click bot reporting — but only the human click appears in the front-end metrics your team and your advertisers actually see.
Additional detection: stealth links and data center filtering
Stealth link (honeypot)
Omeda supports an additional detection layer called a stealth link — a URL embedded in email HTML using CSS properties that make it invisible to human readers. No person can see it or click it. Security bots and link prefetchers can and do.
When Omeda records a click on the stealth link, every other click from that same IP address within that email is invalidated. The bot revealed itself by clicking something no human could see. Setup requires creating a dedicated landing page and registering the URL in Email Builder.
Full setup instructions: Email Stealth Link Setup in the Omeda Knowledge Base.
Advanced click bot suppression (data center IPs)
Omeda’s Advanced Clickbot Suppression gives clients the option to filter out clicks originating from known data center IP ranges (such as AWS, Google Cloud, or Azure) from standard click metrics. When enabled, these clicks are excluded from CTR reporting while remaining visible in the Clickbot Detail Report for auditing purposes.
This is a client-controlled opt-in, toggled in Email Builder under Tools > Ignored IPs. When enabled, suppression applies retroactively to clicks within the prior 60 days. When it’s off, data-center clicks still appear in the Clickbot Detail Report under Reason Code 11 — so you can review the data and make an informed call before enabling it.
Full configuration guide: Advanced Clickbot Suppression in the Omeda Knowledge Base.
Why bot share varies by email type
Not all email sends are equally contaminated, and understanding why matters for how you interpret your data.
Corporate domains carry more bot traffic
Enterprise email security solutions routinely scan links and content before messages reach recipients. As a result, event, webinar, and whitepaper campaigns often experience significant bot-generated opens and clicks. In many B2B environments, a large share of this activity originates from corporate email security systems rather than human engagement.
Low bot activity from consumer domains
Gmail and Yahoo show lower bot click numbers than corporate domains — but not because those providers filter bots on your behalf.
Newsletter familiarity changes the picture
Newsletters generated 60.1% of all click activity on Omeda’s platform in Q1 2026 — and 83.4% of all human clicks. They also had the lowest bot share among major high-volume email categories. While the exact reasons are unclear, factors such as sender reputation, consistent sending patterns, recipient familiarity, and list quality may contribute to the difference.
Independent data tells the same story
Omeda’s data isn’t an outlier. GlueLetter’s 2026 analysis of 105 million newsletter link clicks across dozens of publishers found that 56% of all newsletter click events were artificial — and the distribution by domain type mirrors what Omeda sees. Gmail and Yahoo sit at 6–7% bot share. But institutional domains tell a very different story: government email systems (.gov) came in at 85% artificial clicks, nonprofit domains (.org) at 93%, and educational institutions (.edu) at 80%. If a meaningful share of your audience works in government, academia, or large institutions, your click data is carrying more noise than most. (Looking at you, B2B publishers!)
That domain-level breakdown matters for how you interpret segment performance — and how you report to advertisers. A campaign that reaches a heavily institutional audience will always look noisier in raw click data than one concentrated in consumer inboxes. Knowing that going in changes the conversation.
What domain-level data actually tells you
Understanding that bot share varies by domain type is step one. Step two is knowing what to do with that information when you’re actually reading your data.
Omeda’s domain-level analysis of Q4 2025 click data breaks this down at a granular level. The headline: Gmail clicks still behave like intent signals — roughly 90% appear human. Hotmail, Outlook, and Live.com tell a different story, with bot shares ranging from 40% to over 52%. Outlook alone shows more automated clicks than human ones. Those sends aren’t measuring engagement. They’re measuring security infrastructure.
The practical implication: if you’re evaluating a corporate-domain-heavy event invite with the same benchmarks you use for a Gmail-heavy newsletter, you’re comparing incompatible systems. Campaign type compounds it further — live conference sends to Outlook inboxes showed roughly 69% bot activity in that analysis.
The fix isn’t suppression — it’s segmentation. Separating engagement analysis by receiving domain, email type, and cadence pattern gives you a read on what’s actually happening. The full domain-level breakdown is here.
Why bot clicks matter beyond reporting
Unfiltered bot clicks corrupt your reporting. That’s the obvious problem. The less obvious one is what they do to your marketing automation.
Most systems use click behavior to route subscribers into different paths. Click this link — you’re engaged, enter the nurture sequence. Don’t click — you’re cold, enter the re-engagement flow. When security bots generate fake clicks, they trip those branches. A subscriber who never interacted with the email gets flagged as highly engaged and routed into sequences designed for warm, active contacts.
From there, the system’s view of that subscriber gets progressively worse. The engagement score inflates. The segment membership shifts. When you eventually try to do something meaningful with that record — score leads for a sponsor, identify candidates for a paid conversion push — the underlying data doesn’t reflect real behavior.
Filtering bots keeps your automation branches honest
Omeda’s click bot filtering runs at the click-event level, so the cleaned data flows downstream into your segmentation, lead scoring, and automation logic — not just into your reporting dashboards.
The advertiser trust problem
Bot contamination isn’t just an internal data quality problem. It surfaces in advertiser conversations. When a publisher reports one number of ad clicks and an advertiser’s own tracking shows something lower, someone’s credibility takes the hit — and it’s usually the publisher’s. The publishers who can show filtered, verified click data have a meaningful advantage in those conversations. The ones reporting raw numbers are increasingly being asked to explain the gap.
A proactive approach: confirmation of interest
Bot filtering cleans what’s already in your data. But there’s a complementary strategy worth building into your hygiene practice: Confirmation of Interest (COI) campaigns.
Waiting for click data to degrade before acting on a segment leaves you perpetually behind. By the time you’re cleaning, you’ve already routed subscribers into wrong automation branches, reported inflated engagement numbers, and made decisions based on data that didn’t reflect real behavior.
A COI program asks subscribers to confirm they still want to hear from you — on a cadence that fits your list. The people who respond are real. The people who don’t give you a clear, actionable signal, not an ambiguous click count from a security scanner. This works especially well for corporate domain segments where bot contamination runs highest.
If the clicks aren’t reliable, don’t use them to define engagement. Go ask directly.
How to read your click data when something looks off
When a send comes back with an unusual click pattern, the right move is inspection — not suppression, not alarm.
Pull the Omeda Clickbot Summary Report for that deployment and look at the percentage negated. Then go to the Clickbot Detail Report and look at the reason codes behind the flagged clicks. The cumulative view shows you the wave pattern — delivery-time scanning versus the delayed re-index spikes that appear when a security product circles back a week or a month later. The detail view shows you exactly what was caught and why, email address by email address.
Each flagged click in the report shows the recipient email, the link clicked, source IP, user agent, timestamp, reason code, and whether the click was classified as real or non-human. For data-center clicks, the report names the provider. Nothing is hidden.
That level of visibility is what lets you have a productive conversation with an advertiser when campaign clicks look off, or with an internal team questioning why an automation sequence isn’t performing the way engagement scores suggested it would.
For the full Q1 2026 numbers — bot share by email type, newsletter vs. promo breakdown, and quarter-over-quarter trends — see the Q1 2026 Email Engagement Benchmark Report.
