How to Use BotRefund to Document Bot Behavior for Ad Refund Claims

BotRefund documents bot behavior by installing a lightweight client-side script on your landing pages that records 110+ independent signals per visit — including mouse movement patterns, scroll behavior, browser fingerprint inconsistencies, timing anomalies, and attribution data like click IDs and campaign parameters. The system cross-checks each signal against a prediction model that reaches 99% confidence when the evidence supports it, then produces a session-by-session report formatted for Google and Meta invalid-traffic review teams. You install the script, let it run while your campaigns spend, and download a refund-ready report that includes click IDs (GCLID, FBCLID), timestamps, session replays, and signal-level explanations.

What BotRefund Documents and Why It Matters

BotRefund focuses on the visitor journey after a paid click. It captures browser-level evidence that server logs miss: pointer paths that snap to grid lines instead of curving naturally, scrollbar width mismatches that reveal automated browsers, iframe context leaks from automation frameworks, superhuman input speeds under one millisecond, and the absence of humanlike mouse tremor. Each signal is stored as independent evidence, not a verdict, so privacy tools or corporate networks don't trigger false positives. The platform correlates these signals with your ad-platform click identifiers so every flagged session ties back to a specific campaign, ad set, creative, and placement.

This matters because Google and Meta only refund invalid activity when you supply evidence in their review format. Server-side IP filters catch basic scrapers but miss residential proxy networks and sophisticated botnets that mimic human IPs. Client-side behavioral documentation fills that gap by proving the visitor behind the click did not behave like a person.

Key Facts

Capability	Detail	Source
Detection signals	110+ independent behavioral, browser, hardware, network, and attribution checks	S2
Confidence threshold	99% when session evidence supports it	S2, S3, S5
Refund success rate	83% of 2,500+ audited clients recover funds from Google and Meta	S2
Report format	Click IDs, campaign details, timestamps, session recordings, signal-by-signal reasoning	S2
Platform coverage	Google Ads and Meta (Facebook/Instagram) invalid-traffic claims	S1, S2, S4, S6
Case example	FinTrust recovered $140,000 (14% of spend) and lifted conversion rate 18%	S8

How the Detection Works: Signal Categories

BotRefund groups its 110+ checks into behavioral families. Each family contributes one piece of the overall pattern:

• Click behavior — Ghost click detection catches clicks that fire without the natural human intent sequence (S2).
• Trap behavior — Honeypot interactions reveal bots that respond to hidden page elements real users never see (S2).
• Pointer behavior — Robotic linear movements and grid-aligned paths flag unnaturally straight or block-snapped trajectories (S2).
• Motion behavior — Absence of humanlike mouse tremor detects the missing micro-jitter present in every real hand (S2).
• Speed behavior — Superhuman input speed under 1ms identifies actions faster than any person can perform (S2).
• Engagement behavior — Absence of clicks or scrolling highlights sessions too static for genuine browsing (S2).
• Session behavior — Unnatural durations (too short, too long, or too uniform) signal scripted visits (S2).
• Browser fingerprint checks — Scrollbar Width Leak (S3) and Clean Context Iframe (S5) expose automation frameworks that patch or hide browser APIs inconsistently.

No single signal proves fraud. BotRefund keeps each as evidence and feeds the full pattern into an AI prediction model that weighs corroboration across browser, network, device, and behavior layers (S3, S5).

Step-by-Step: Documenting Behavior for a Refund Claim

1. Add the script to every landing page that receives paid traffic. The snippet loads asynchronously and does not block page render.
2. Verify click-ID capture in the dashboard. Confirm GCLID (Google) and FBCLID (Meta) parameters are attached to sessions so evidence ties to the exact campaign, ad set, creative, and placement (S1, S2).
3. Run campaigns normally for a meaningful sample — typically 7–14 days or until you have several thousand paid clicks. Do not pause or restructure campaigns mid-audit; you need the live placement mix.
4. Review the flagged sessions in the BotRefund dashboard. Each session shows a timeline, signal breakdown, and a replay. Look for clusters: same placement, same creative, same hour bursts (S1).
5. Export the refund-ready report. The report includes click IDs, timestamps, campaign metadata, session recordings, and signal-by-signal reasoning formatted for Google and Meta review teams (S2).
6. File the claim through the platform's invalid-activity or traffic-quality form. Attach the BotRefund report. BotRefund's team can assist with claim wording and follow-up negotiation (S2).
7. Track the outcome. Credits appear in your ad account. Reinvest or reallocate based on cleaned data.

Building a Refund-Ready Report

Google and Meta reviewers expect specific fields. BotRefund structures each report with:

• Click identifier (GCLID / FBCLID)
• Campaign, ad set, creative, placement, device, geo
• Timestamp of click and session start
• Session recording (scrubbed of PII)
• Signal list with pass/fail and confidence weight
• AI prediction summary (bot / human / inconclusive)
• Narrative explanation linking signals to platform policy definitions

The platform teams use this format internally, so a matching submission reduces back-and-forth. BotRefund's 83% approval rate across 2,500+ audits comes from this alignment plus negotiation experience (S2).

Common Mistakes and Limitations

• Starting the audit after pausing campaigns — you lose the live placement mix that reveals which sources drive bots (S1).
• Treating every bad lead as a bot — weak offers attract real but unqualified people. BotRefund separates low intent from automation (S1).
• Expecting 100% coverage — sophisticated actors may evade some signals. The 99% confidence applies when evidence supports it; inconclusive sessions are labeled, not forced (S3, S5).
• Using server logs alone — they miss client-side behavior like mouse tremor, scrollbar leaks, and iframe context (S2, S3, S5).
• Filing without click IDs — platforms cannot match sessions to billed clicks without GCLID/FBCLID (S2).

BotRefund does not replace your analytics, CRM, or tag manager. It adds an evidence layer for paid-traffic quality. It also does not block traffic in real time; it documents for refund claims and suppression lists.

When to Use This vs. Other Approaches

Approach	Best For	Gap
BotRefund (client-side behavioral evidence)	Proving invalid clicks to Google/Meta for refunds; protecting pixel training data	Does not block at edge; requires script install
Cloudflare / edge WAF	DDoS mitigation, CDN, infrastructure security	Limited behavioral evidence for ad-platform refund format
Server-log IP filters	Known data-center ranges, basic scrapers	Misses residential proxies, human-like botnets
Platform auto-credits	Obvious rapid-click patterns Google/Meta already catch	Leaves 60–80% of invalid activity uncredited (S6)

Many advertisers keep their edge provider and add BotRefund for the marketing-layer evidence. The jobs coexist (S7).

FAQ

How long until I have enough data to file a claim?

Typically 7–14 days of live spend across the placements you want audited. You need a few thousand paid clicks to surface statistically meaningful clusters.

Does the script slow down my page?

It loads asynchronously and is designed for negligible impact on Core Web Vitals. Most sites see no measurable change.

What if I run campaigns on both Google and Meta?

BotRefund captures GCLID and FBCLID automatically. One script covers both platforms; the dashboard separates reports by source.

Can I use the data to exclude placements in-platform?

Yes. Export the placement-level bot rates and add the worst offenders to your placement exclusion lists in Google Ads and Meta Ads Manager.

What happens if Google or Meta rejects the claim?

BotRefund's team reviews the rejection reason, supplements evidence if gaps exist, and resubmits. The 83% success rate includes negotiated approvals after initial denial (S2).

Is there a minimum spend requirement?

No published minimum. The free audit tier lets you test detection volume before committing. Enterprise plans start under $10,000/mo (S2).

How does BotRefund handle privacy regulations?

Session recordings are scrubbed of personally identifiable information. The system stores behavioral signals, not form content or keystrokes.

Further reading and comparison sources

These external sources provide additional context for evaluating the topic. Their inclusion is not an endorsement.

• How I Built Refund Processing System using AI Agents from Scratch ...
• How can I get a refund? | Chatbot App
• Return and Exchange Chatbot: Cut Refund Handling 40-60% | Quickchat ...

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