InboxEagle
Bot Finder

Your Click Rate
Is Lying.
Find the Bots.

Security scanners, link-safety bots, and prefetch noise inflate opens and clicks — before those numbers hit your dashboards, segments, and models. Bot Finder scores every event in real time so you act on human engagement, not automation.

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Click Event Timeline

Campaign: Aug Sale

j***@gmail.com

Clicked · 14:32:07 · 3.2s after open

Human

k***@company.com

Mixed signals · 14:33:41 · review

Suspicious

m***@outlook.com

Clicked all 7 links · 14:32:09 · 120ms

Bot ⚠

s***@yahoo.com

Clicked · 14:34:51 · 8.7s after open

Human

t***@company.com

MS SafeLinks · 14:32:08 · 85ms · DC IP

Bot ⚠

a***@gmail.com

Clicked · 14:41:12 · 22.1s after open

Human
Bot-free Click Rate
14.2% 9.1% real

98.4%

Bot Detection Accuracy

< 1s

Typical Classification Time

3

Verdicts: Human, Suspicious, Bot

SES · Mailgun · Klaviyo

Native ESP Connections

How It Works

Bot-Free Engagement Data in Three Steps

Connect once, get clean engagement data on every campaign automatically.

Step 1 Integrated

Connect your sending platform

Hook up AWS SES, Mailgun, or Klaviyo — the same analysis runs everywhere. Opens and clicks flow in through the path that matches your ESP; your templates stay untouched.

Step 2 Analyzing

Every event gets a layered score

Bot Finder weighs multiple independent signal families — not a single rule — and combines them into one score with plain-English reasons. Privacy prefetch and known security tools are treated in context so legitimate subscribers are not punished.

Step 3 Flagged

Verdicts land where you already work

Classifications and confidence scores show up in InboxEagle — and can be delivered to your stack in real time so dashboards, suppression logic, and models see human, suspicious, and bot traffic separately.

Features

From ingestion to verdict — one Bot Finder stack

Native ESP hooks, layered scoring, dashboard intelligence, and optional delivery to your stack — without maintaining parallel bot logic everywhere.

SES, Mailgun & Klaviyo

First-class ingestion for the ESPs teams actually run at scale. Events are normalized into one model so you do not maintain parallel bot logic per provider.

Multi-signal scoring

Timing, infrastructure, clients, sequences, and historical context are evaluated together. Strong automation signals are caught early; borderline cases earn a suspicious verdict instead of a blind guess.

Human, suspicious, or bot

Three outcomes — not just a binary flag. Review the gray zone, tune how aggressively you act on automation, and keep confidence aligned with how your team uses the data.

Verifiable delivery

When Bot Finder sends results to your endpoints, payloads can be authenticated so your systems trust the source — not a replay or impersonation.

Fresh threat context

Infrastructure and abuse signals are refreshed on a schedule — not a one-time import — so scoring reflects how the internet looks today, not last quarter.

Journey-level clarity

See how automated opens relate to later human clicks — and when a real subscriber confirms engagement after machine noise — so funnels and attribution tell an honest story.

Click Event Timeline

Visual timeline of every click — human, suspicious, and bot — with per-event scores and reasons so operators can trust what they see.

Timing Analysis

Bot clicks happen in milliseconds and often fire on every link simultaneously. Bot Finder's timing models spot inhuman patterns while accounting for legitimate fast paths.

IP & Geo Intelligence

Cross-reference click IPs against known security scanner ranges, data center subnets, and geographic anomalies that indicate automated activity.

User Agent Fingerprinting

Detect security scanners, link-safety bots, and automated crawlers by their user agent signatures — including Microsoft SafeLinks and similar corporate filters.

Clean Engagement Reports

Filtered reports showing bot-free open rates, click rates, and per-link engagement — so your A/B test results and segmentation decisions reflect real behavior.

Bot Spike Alerts

Alert when an unusual volume of bot activity is detected on a campaign — a signal that security scanners or link-safety systems are aggressively scanning your mail.

Feedback that sharpens accuracy

When something is misclassified, your team can record corrections so future scoring reflects how you define real engagement — without exposing how the engine works under the hood.

How it thinks

More than a single rule or score

Bot Finder progresses through complementary checks — obvious automation is separated quickly; everything else earns a weighted blend of context. The exact implementation is ours; the outcome is a defensible verdict you can explain to leadership.

1

Immediate automation signals

When the pattern is unmistakable, the verdict is immediate — no wasted work on clear bot runs.

2

Behavior & sequence context

Timing, traversal, clients, and how an event fits the rest of the message journey.

3

Confidence from corroboration

Weak hints stay weak; multiple independent signals agreeing carry more weight.

4

Memory of what normal looks like

Recipients, campaigns, and infrastructure are compared to their own baselines when history exists.

5

Shared infrastructure awareness

Patterns observed across the ecosystem inform risk — without sharing your customer data.

6

Recipient-specific guardrails

Known trusted engagement can reduce false positives; repeat automation can be surfaced more firmly.

The Difference

Inflated Metrics vs. Real Engagement Data

Bots making up 30-50% of your engagement data poison every decision that relies on those numbers.

Without InboxEagle

Click rate 22% — bots make up 58% of clicks
  • Bot clicks inflate reported click rates by 2–5×
  • A/B test winners chosen based on bot activity
  • Win-back automation triggered by bot opens
  • Suppression lists miss truly unengaged contacts
  • Revenue attribution overstated due to fake clicks

With InboxEagle

Real Rate: 9.1%
  • Every event classified as human, suspicious, or bot with reasons
  • A/B tests scored on real human engagement only
  • Automation triggers protected from bot false positives
  • True unengaged contacts correctly identified for suppression
  • Accurate revenue attribution from real click-through data
Free 14-day trial · No credit card required

Trust Your Engagement Data Again. Eliminate Bot Noise.

Stop making decisions on inflated metrics. Bot Finder gives you layered, explainable verdicts across SES, Mailgun, and Klaviyo — one integration model, every campaign.

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FAQ

Frequently Asked Questions

What is email bot activity and why does it inflate metrics?
Email bots are automated systems — corporate email security scanners, link safety checkers (like Microsoft SafeLinks), and spam filters — that click every link in an email to check for threats. These clicks register as real engagements in your ESP, inflating open rates, click rates, and even triggering automation flows meant for engaged subscribers. Bot Finder separates bot events from real human engagement.
How does Bot Finder detect bot clicks vs. real clicks?
Each open or click is scored using many complementary signal families — timing, infrastructure, client fingerprints, sequences, and historical context — combined into one result with plain-english reasons. Obvious automation is separated from the gray zone, and privacy-driven prefetch is interpreted in context so real subscribers are not punished by default.
Does Bot Finder work with AWS SES, Mailgun, and Klaviyo?
Yes. Bot Finder ingests events natively from AWS SES, Mailgun, and Klaviyo through the integration path that matches your ESP. The same classification logic runs everywhere, so you are not maintaining separate bot rules per provider.
What does the suspicious verdict mean?
Suspicious sits between clear human engagement and high-confidence automation. It flags events that deserve a second look — for example, mixed signals or patterns that could be either a cautious human or a polite scanner. You choose how aggressively to treat that bucket in reporting and downstream workflows.
Will bot detection break my email automation flows?
No — Bot Finder surfaces verdicts in InboxEagle and optional delivery to your systems; it does not rewrite what your ESP sends. Your existing automation flows run as configured. Use Bot Finder data to audit which triggers were bot-driven and tighten segmentation where it matters.
Does Bot Finder handle Apple Mail Privacy Protection and similar prefetch?
Yes. Privacy proxies and image prefetch can look like instant opens. Bot Finder treats those scenarios in context so MPP-style signals do not automatically count as bot engagement, reducing false positives while still catching real automation.
Does InboxEagle detect Microsoft SafeLinks bot clicks?
Yes. Microsoft SafeLinks is one of the most common sources of false clicks in B2B email. Bot Finder recognizes SafeLinks-style proxy patterns and classifies them appropriately — giving you more accurate click data for Outlook recipients.
Can we trust results delivered to our own systems?
When you enable delivery to your endpoints, Bot Finder can include cryptographic verification so your services can confirm payloads genuinely came from InboxEagle — useful for security-conscious teams and automated pipelines.
How does accurate bot filtering improve email deliverability?
When bot clicks inflate your engaged segment, you keep mailing people who look active but are not. That erodes real engagement and can increase complaints — signals ISPs watch. Bot Finder helps you segment and suppress based on human behavior, which supports healthier reputation over time.