Bot Exclusion Intelligence

Keep bots, suspects and low-trust sessions out of your advertising signals.

EntryLap reads every visitor through traffic source, device behavior, browser signals, session quality and conversion context. The dashboard explains why a visitor is risky, how much audience pollution exists, and which exclusion rule should run first.

Create free workspace See detection signals

Human / suspect / bot score Paid traffic risk Exclusion audience workflow

68+ connected ecommerce stores

426 risky visitors identified

18.6% paid traffic risk detected

4.9/5 operator feedback score

What the bot layer improves

Use Bot Exclusion to understand where low-trust traffic enters, how it affects audiences, and which cleanup action should happen before scaling campaigns.

Cleaner audience88% Less retargeting waste72% Better learning signal84%

Bot

Suspect

Human

Paid risk

IP risk

Device

Browser

Event depth

01 · Signal classification

Separate real shoppers from low-trust sessions.

EntryLap groups visitors into human, suspect and bot signals so reporting and retargeting are not polluted by crawler-like or weak behavior.

Detect Score Exclude

Risky sessionslower after cleanup Clean learning signalstronger for optimization Retargeting qualityaudiences become cleaner

02 · Audience cleanup

Turn bot analysis into an action.

Create controlled exclusion rules from risky traffic while protecting converters and keeping useful shoppers in your audience pool.

Less wasteReduce budget going back to non-shopping sessions.

Cleaner MLHelp ad platforms learn from stronger human signals.

Safer rulesKeep converters protected while excluding weak sessions.

Clearer reportsShow source risk, device risk and reason tags in one view.

03 · Business outcome

Cleaner data before you scale budget.

Clean traffic signals make reports easier to trust, retargeting audiences safer to use and scaling decisions easier to explain to the whole team.

Detection logic

How EntryLap separates real shoppers from noisy sessions.

EntryLap does not rely on one weak signal. It combines behavior depth, source quality, session timing, device consistency, IP patterns and conversion safety before a visitor becomes part of an exclusion workflow.

Session duration and event depth Crawler, browser and automation patterns IP, datacenter and repeated source risk Converter-safe exclusion rules

74% review score

Signal decision

Classify before you exclude.

EntryLap separates human, suspect and bot-like behavior so teams can clean audiences without hiding useful shoppers or past converters.

Human signal Normal browsing depth, useful events, product engagement and consistent device behavior.

Suspect signal Weak engagement, short sessions, incomplete sensor data or unstable source patterns.

Bot signal Crawler-like user agent, datacenter-style traffic, flat behavior or repeated low-trust activity.

Safe rule Protect converters, separate paid risk from organic risk and keep cleanup actions explainable.

ReadCollect session, source, device and event behavior.

ScoreTurn mixed signals into human, suspect or bot quality.

ActBuild clean exclusion actions only when the reason is clear.

Traffic quality dashboard

See bot risk clearly before your team increases budget.

Connected store data reveals how human, suspicious and automated traffic affect campaigns, audiences and reporting.

Human vs Bot TrendSignal quality over time

What improves: your team can see whether cleanup is moving the account toward more real shoppers and fewer noisy sessions before increasing budget.

Bot Rate by SourceFind budget leaks

Paid socialReview

DirectClean up

UnknownHigh risk

SearchCleaner

What improves: instead of treating all traffic equally, EntryLap shows which sources should be excluded, reviewed or protected for learning.

Before vs After ExclusionCleaner learning signal

Risk trafficBefore

Clean signalAfter

Goal: lower audience pollution before the next retargeting or optimization cycle.

What improves: exclusion is not just a report; it becomes an action that keeps weak sessions away from Meta/Google learning signals.

Device Risk IntelligenceBad device patterns

iOSSensor review

DesktopCrawler review

AndroidBehavior review

What improves: device-level risk helps teams catch non-human patterns that normal click reports cannot explain.

Business impact

Why bot exclusion can reduce waste and improve revenue decisions.

When bot and suspect sessions stay inside remarketing and optimization pools, platforms can learn from weak visitors. EntryLap helps your team separate clean shoppers from noisy sessions before retargeting, reporting or scaling.

Reduce wasted retargeting

Exclude visitors that look like crawlers, datacenter traffic, very short sessions or non-shopping behavior before they keep receiving budget.

Common range: 12–38% risk by source

Cleaner machine learning

Cleaner event streams help Meta and Google learn from real human behavior instead of polluted, low-trust sessions.

Cleaner signal → better optimization

Protect real shoppers

Rules can avoid excluding converters and can separate paid risk from organic/direct risk, so cleanup stays controlled.

Safe exclusion workflow

Metrics explained

What every Bot Exclusion number means.

Use this table in onboarding and client reporting to explain what each traffic-quality signal means and what action it supports.

SignalWhat EntryLap readsHow it helps

Human scoreClean engagement, realistic session duration, device behavior and meaningful product/funnel actions.Prioritize clean visitors for reporting, retargeting and learning signals.

Bot scoreLow-trust session, generic crawler UA, missing behavior profile, datacenter-like source or hard-risk visitor pattern.Send risky sessions into exclusion workflows instead of ad learning.

Audience pollutionThe share of visitors that may weaken retargeting or optimization audiences.Know whether to clean audiences before scaling campaigns.

Paid riskRisky traffic connected to paid sources or campaign-tagged sessions.Estimate wasted budget and identify ad sources to review first.

Synced / excludedHow many risky visitors were added to exclusion actions.Verify that detection became action, not just a report.

Store owner feedback

“EntryLap made it clear that our retargeting pool was not clean. The bot page showed source risk, device risk and exact visitor reasons in one place.”

Fashion ecommerce operator · 4.9/5

Media buyer feedback

“It is easier to explain why a campaign should not scale yet. We can show bot pressure, paid risk and signal quality before increasing budget.”

Performance team · 4.8/5

Agency feedback

“Instead of sending a spreadsheet, we show the exclusion chart, source risk and the next action. Clients understand the cleanup process faster.”

Agency reporting workflow · 4.9/5