Seatext library / BotRefund evidence
Browser Behavior Data Needed for a Successful Invalid Click Refund Claim
Ad platforms require timestamped interaction logs showing non-human patterns: missing mouse events, mechanical timing, identical session patterns across multiple IPs, and statistical deviation from human baselines. BotRefund packages this evidence automatically, making it easier...
✓ Built for advertisers who need clear, refund-ready traffic evidence.
To win an invalid click refund claim, you need browser behavior data that proves the clicks were not human. Ad platforms like Google and Meta require timestamped interaction logs that show non-human patterns: missing mouse events, mechanical timing, identical session patterns across multiple IPs, and statistical deviation from human baselines. BotRefund packages this evidence automatically, so you can submit a claim without manual forensic work.
What Browser Behavior Data Counts as Evidence
Ad platforms accept client-side behavioral logs as proof of invalid traffic. The key is to capture signals that a real person would not produce. BotRefund's detection system logs the following behaviors:
- Ghost click detection – Catches click activity that happens without the natural sequence of human intent.
- Trap behavior – Honeypot trap interactions: watches for bots that respond to hidden or intentionally deceptive page elements.
- Pointer behavior – Robotic linear mouse movements: flags unnaturally straight pointer paths that rarely appear in real user sessions.
- Motion behavior – Absence of humanlike mouse tremor: looks for the tiny imperfections and jitter typical of human movement.
- Speed behavior – Superhuman input speed (<1ms): identifies interactions that happen faster than a person could realistically perform.
- Path behavior – Grid-aligned movement patterns: detects movement that snaps to precise lines or blocks instead of natural curves.
- Engagement behavior – Absence of clicks or scrolling: highlights sessions that stay too static to match a real browsing journey.
- Session behavior – Unnatural session durations: catches visit lengths that are too short, too long, or too uniform to be human.
These signals, when timestamped and tied to a specific ad click (like a GCLID or FBCLID), form the core of a refund claim. Each behavior type creates a data point that platforms can verify against their own internal baselines.
Why Ad Platforms Require Client-Side Behavioral Logs
Google and Meta run server-side filters that catch obvious bots. Those filters miss sophisticated traffic that uses residential proxies, AI-generated mouse curves, and real browser engines. Server logs show IP, user agent, and timestamp. They do not show mouse tremor, click latency, or scroll depth. Client-side scripts capture the missing layer. The platforms ask for this data because their own systems cannot see it. When you submit a claim, you are providing evidence that the platform's automated filters did not have.
Industry data shows that between 15% and 25% of paid traffic across major networks is completely invalid. This includes scraper bots, click farms, competitor scripts, and placement fraud. Default platform reporting leaves you blind to these operations. Client-side tracking closes that gap.
How Invalid Click Patterns Differ from Human Behavior
Human browsing is messy. People hesitate, scroll unevenly, move mice in curves, and pause to read. Bots optimize for speed and consistency. The differences appear in measurable ways:
- Mouse path geometry – Humans produce Bezier-like curves with micro-jitter. Bots often move in straight lines or snap to grid coordinates.
- Click timing – A human click takes 100–300 milliseconds from mouse-down to mouse-up. Bots can register clicks in under 1 millisecond.
- Scroll behavior – Humans scroll in variable increments, sometimes reversing. Bots either do not scroll or scroll at fixed intervals.
- Session variance – Human session lengths follow a long-tail distribution. Bot sessions cluster at identical durations.
- Interaction sequence – Humans explore: hover, scroll, click, read. Bots often click immediately on load or follow a fixed script.
Modern fraud networks use AI to simulate human curvature and random intervals. They route clicks through hijacked IoT devices to appear as residential IPs. They trigger conversion pixels with fake form submissions. These tactics bypass basic filters but still leave statistical fingerprints in client-side logs.
Step-by-Step: How to Collect and Submit the Evidence
Step 1: Install a Client-Side Tracking Script
You need a script on your landing page that records every interaction. BotRefund adds to your website in about one minute. No credit card required. The script logs mouse movements, clicks, scrolls, session duration, and more. It also captures click IDs (GCLID for Google, FBCLID for Meta) automatically.
Step 2: Let the Script Run and Accumulate Data
Do not turn it off. The more sessions you capture, the stronger your evidence. BotRefund automatically flags sessions that match non-human patterns. The system builds a baseline of normal traffic for your site, then highlights deviations.
Step 3: Export the Behavioral Proof Logs
BotRefund generates a report that shows each invalid click with the specific behavior that triggered the flag. This report is your evidence package. It includes timestamps, click IDs, behavior classifications, and visual session replays. The export is formatted for ad platform review teams.
Step 4: Submit the Claim to the Ad Platform
For Google Ads, you file a manual refund request with the Click Quality team. Include the exported logs and explain how each behavior indicates non-human activity. Reference the GCLIDs. For Meta, the process is similar—submit the evidence through the billing dispute channel with FBCLIDs. Both platforms require a formal investigation form.
Step 5: Follow Up and Escalate if Needed
Ad platforms may ask for more details. Keep your logs organized and be ready to explain the technical signals. BotRefund also offers negotiation and escalation support for larger accounts. Google's Click Quality team typically reviews claims within a few weeks. BotRefund's negotiation process can speed this up for larger accounts.
Platform-Specific Requirements: Google Ads vs Meta Ads
Both platforms require timestamped client-side logs tied to click IDs. The submission channels differ.
| Requirement | Google Ads | Meta Ads |
|---|---|---|
| Click ID parameter | GCLID | FBCLID |
| Submission channel | Click Quality team / investigation form | Billing dispute channel |
| Invalid categories accepted | Competitor clicks, publisher fraud, bot traffic | Automated crawlers, click farms, partner placement fraud |
| Lookback window | Up to 2017 with evidence | Similar historical range |
| Evidence format | Behavioral logs, session replays, GCLID list | Behavioral logs, session replays, FBCLID list |
Google officially categorizes invalid clicks into traffic segments they agree to credit back if you provide sufficient proof. These include competitor click activity, publisher click fraud, and bot traffic with web scrapers. Meta divides ad traffic into valid and invalid. Valid traffic represents real users who engage. Invalid traffic represents automated visits or fraudulent publisher clicks.
Accidental clicks (such as double-clicking an ad or fat-finger mobile interactions) are generally not refundable on either platform because they are considered human error.
Common Pitfalls That Cause Claim Rejection
Claims fail when evidence is incomplete or misaligned with platform expectations. Common issues:
- Missing timestamps – Logs without precise timestamps cannot be matched to billed clicks.
- No click IDs – GCLID or FBCLID must accompany each flagged session.
- Vague behavior descriptions – "Bot-like" is not enough. You must cite specific signals: linear mouse path, sub-millisecond click, zero scroll.
- Insufficient sample size – A handful of flagged sessions may be dismissed as noise. Platforms look for patterns across many IPs.
- CPM campaigns – This approach works for click-based campaigns. It does not apply to impression-based (CPM) campaigns where you are not charged per click.
- Human but poorly targeted traffic – If your traffic is genuinely human but poorly targeted, behavioral evidence will not help you get a refund.
Ad platforms may reject claims if the evidence is not timestamped or if the behavior patterns are not clearly non-human. Organized logs with clear annotations improve approval odds.
Advanced Detection: How Modern Bots Evade Basic Filters
Fraud networks continuously refine techniques. Current trends that bypass default filters:
- AI-powered bot telemetry – Fraud networks use AI model generators to simulate human mouse curvature, click intervals, and page scrolling. By introducing random, organic-like irregularities, bots bypass simple pattern-detection rules.
- Residential proxy expansion – Malicious actors route clicks through networks of hijacked smart devices (IoT) in target local areas. This presents the ad platform with legitimate residential IP addresses, making location-based exclusions ineffective.
- Audience network exploitation – As display and partner networks expand to include millions of long-tail mobile apps and websites, publishers use background scripts to generate fake impressions and clicks.
- Conversion pixel poisoning – Sophisticated botnets trigger conversion pixels by filling out lead forms with fake data or clicking checkout buttons. This corrupts smart bidding algorithms, causing Google's AI to bid higher for fraudulent traffic.
These tactics make server-side filtering insufficient. Client-side behavioral analysis remains the most reliable way to detect the difference between emulated and genuine human interaction.
Key Facts About Invalid Click Refunds
| Fact | Detail |
|---|---|
| Budget impact | Bot clicks steal up to 20% of your Google and Meta ad budget. |
| Refund approval rate | BotRefund reports an approved rate across client refund claims submitted to ad platforms. |
| Setup time | Typical time to add BotRefund to your website and start your free bot audit is about 1 minute. |
| Eligible platforms | Google Ads and Meta (Facebook/Instagram) billing disputes. |
| Evidence type | Client-side behavioral logs: mouse movement, click patterns, session timing, and more. |
| Historical reach | Recover bot-click refunds from Google Ads spend dating back to 2017. |
| Invalid traffic share | Industry data shows 15–25% of paid traffic across major networks is invalid. |
Frequently Asked Questions
How long does a refund claim take?
It varies. Google's Click Quality team typically reviews claims within a few weeks. BotRefund's negotiation process can speed this up for larger accounts.
What if I don't have a tracking script installed yet?
You can install BotRefund now and start collecting data. Refund claims can cover past spend dating back to 2017 if you have the evidence.
Can I file a claim for Meta ads too?
Yes. BotRefund supports both Google Ads and Meta billing disputes. The evidence requirements are similar.
Do I need to be technical to use this?
No. BotRefund handles the technical detection and report generation. You just install the script and export the report.
What if the ad platform rejects my claim?
You can appeal. BotRefund provides escalation support and can help you negotiate with the platform.
Is there a cost to try it?
BotRefund offers a free bot audit. You can add the script and see what it detects before committing.
Does this work for CPM campaigns?
No. This approach works for click-based campaigns on Google and Meta. It does not apply to impression-based (CPM) campaigns where you are not charged per click.
What about accidental clicks?
Accidental clicks (like double-clicks or fat-finger taps) are generally not refundable because they are considered human error.
Further reading and comparison sources
These external sources provide additional context for evaluating the topic. Their inclusion is not an endorsement.
Further reading and comparison sources
These external sources provide additional context for evaluating the topic. Their inclusion is not an endorsement.
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