Seatext library / BotRefund evidence
How to Reduce Bot Traffic Without Blocking Search Engines
Use behavioral detection and fingerprinting to identify automated visitors while explicitly allowing known crawlers like Googlebot. BotRefund applies 106 independent checks — including WebGL texture constraints, mouse tremor analysis, and superhuman input speed —...
✓ Built for advertisers who need clear, refund-ready traffic evidence.
Start by distinguishing between crawlers you want (Googlebot, Bingbot) and automated visitors that waste ad spend. The reliable way to do this is client‑side behavioral fingerprinting combined with a whitelist of verified search‑engine user agents and IP ranges. BotRefund’s detection runs in the browser, collects 106 independent signals — hardware and GPU fingerprinting, WebGL texture constraints, pointer motion, click timing, session duration patterns — and feeds them into an AI model that weighs the full pattern instead of relying on any single rule. That model returns a bot‑or‑human verdict with 99% accuracy, and the platform automatically suppresses conversion pixels for flagged sessions so Google and Meta AI train only on real users.
Prerequisites before you begin
- Access to your website’s
<head>or tag manager to paste a single JavaScript snippet (setup takes about one minute). - Admin rights on your Google Ads and/or Meta Ads accounts to link conversion pixels and enable refund‑evidence collection.
- A baseline of at least 30 days of ad spend data so the audit can compare pre‑ and post‑protection performance.
Step‑by‑step implementation
- Add the detection script. Paste the BotRefund snippet into your site’s
<head>or via GTM. The script begins collecting browser, network, device, and behavioral evidence immediately. - Whitelist known crawlers. In the BotRefund dashboard, confirm the default allow‑list includes Googlebot, Bingbot, and other major search‑engine user agents and IP blocks. Add any custom crawlers you rely on (e.g., monitoring services).
- Enable pixel protection. Turn on “Pixel Protection” so conversion events (GCLID, FBCLID) from sessions flagged as bots are suppressed in real time. This keeps your ad platforms’ optimization engines trained on human conversions only.
- Run the free live audit. Book the 15‑minute audit call; BotRefund will walk through flagged sessions, show video proof for each invalid click, and quantify the percentage of ad spend lost to bots (clients typically see up to 20% of Google/Meta budget affected).
- Submit refund claims. Use the generated Refund Evidence Dossier — organized click IDs, timestamps, behavioral annotations — to file billing disputes with Google Ads and Meta. BotRefund’s historical reach goes back to 2017.
- Monitor and iterate. Review the dashboard weekly. The AI model self‑updates as new bot patterns appear, but you can adjust sensitivity thresholds if you see false positives on unusual but legitimate devices.
Verification step
After 7–14 days, compare your conversion‑rate and cost‑per‑acquisition numbers against the pre‑install baseline. In the FinTrust neobank case study, bot click rate was 14%, ad spend refunded reached $140,000, and conversion rate rose 18% after suppression began. A similar lift in your own metrics confirms the filter is working without blocking legitimate crawlers.
Why behavioral fingerprinting beats simple IP blocking
IP blocklists and robots.txt only stop bots that announce themselves. Modern botnets rotate residential proxies, spoof user agents, and run headless browsers (Puppeteer, Selenium, Playwright) that mimic real Chrome or Firefox fingerprints. BotRefund’s 106 checks — including WebGL texture constraint analysis, absence of humanlike mouse tremor, superhuman input speed (<1 ms), grid‑aligned movement paths, and ghost‑click detection — catch the inconsistencies that spoofed profiles cannot hide. Each signal is kept as evidence, not a verdict; the AI model cross‑checks all signals before deciding.
Key facts from BotRefund’s detection engine
| Signal category | What it catches | Source |
|---|---|---|
| Hardware & GPU fingerprinting | Mismatches between claimed device and actual graphics, fonts, audio, processor behavior | S1 |
| WebGL texture constraint | Virtual machines and spoofed profiles that report one device while graphics behavior tells another story | S1 |
| Ghost click detection | Click activity without the natural sequence of human intent | S2, S5, S8 |
| Honeypot trap interactions | Bots responding to hidden or deceptive page elements | S2, S5, S8 |
| Robotic linear mouse movements | Unnaturally straight pointer paths rare in real sessions | S2, S5, S8 |
| Absence of humanlike mouse tremor | Missing micro‑jitter typical of human movement | S2, S5, S8 |
| Superhuman input speed (<1 ms) | Interactions faster than a person can perform | S2, S5, S8 |
| Grid‑aligned movement patterns | Movement snapping to precise lines/blocks instead of natural curves | S2, S5, S8 |
| Absence of clicks or scrolling | Sessions too static to match a real browsing journey | S2, S5, S8 |
| Unnatural session durations | Visits too short, too long, or too uniform to be human | S2, S5, S8 |
Common mistake: relying on a single signal
Treating any one anomaly — a missing mouse tremor, a fast form fill, an unusual WebGL readout — as proof of a bot creates false positives. Privacy tools, corporate networks, travel, and uncommon devices can all produce atypical but genuine behavior. BotRefund avoids this by keeping every signal as evidence and letting the AI model weigh the complete pattern across browser, network, device, and behavior dimensions.
Options and trade‑offs for bot management
| Approach | Setup effort | Crawler safety | Detection depth | Refund support | Best fit |
|---|---|---|---|---|---|
| BotRefund (behavioral AI + pixel suppression) | ~1 minute snippet install | Built‑in whitelist for Googlebot, Bingbot, custom crawlers | 106 signals, AI verdict, 99% accuracy claim | Automated evidence dossiers, historical to 2017 | Advertisers spending $10k–$5M+/mo on Google/Meta who want recovery + protection |
| WAF / rate limiting (e.g., Cloudflare, AWS WAF) | Moderate (rule config, tuning) | Must manually maintain allow‑lists | IP reputation, request velocity, basic JS challenges | None | Sites needing edge‑layer DDoS / scrape protection, not ad‑spend recovery |
| GA4 / analytics filters | Low (UI config) | No effect on crawlers | Post‑hoc session filtering only | None | Teams that only need cleaner reports, not live pixel protection or refunds |
| CAPTCHA / challenge pages | Low–moderate | Blocks crawlers unless explicitly bypassed | Challenge‑response only | None | High‑value forms (login, checkout) where friction is acceptable |
Practical scenarios
- Lead‑gen campaigns on Meta: Affiliate partners use headless browsers and residential proxies to flood forms. BotRefund’s superhuman‑speed and pointer‑behavior signals catch the automation; pixel protection stops those leads from poisoning Meta’s optimization.
- Search ads with high CPC: Competitors or click‑farms run bots that mimic real users. WebGL texture constraint and hardware fingerprinting expose the VM / spoofed‑profile mismatch; refund dossiers recover wasted spend back to 2017.
- Enterprise compliance: Security teams need audit trails. The Refund Evidence Dossier provides timestamped click IDs, behavioral annotations, and video proof that ad‑platform reps accept.
Limitations and when this advice does not apply
- Sites with zero ad spend on Google or Meta — there is no refund mechanism to activate.
- Environments that block third‑party JavaScript (strict CSP, some intranets) — the detection snippet cannot load.
- Purely organic traffic concerns — BotRefund focuses on paid‑click validation; it does not rewrite
robots.txtor server‑side crawl budgets. - Historical refunds depend on ad‑platform policy windows; Google and Meta may reject claims older than their allowed lookback periods.
Terminology quick reference
- GCLID / FBCLID: Click identifiers Google Ads and Meta append to landing‑page URLs; used to tie a session back to a specific paid click.
- Pixel protection: Real‑time suppression of conversion pixels for sessions flagged as bots, so ad platforms’ machine‑learning models train only on human conversions.
- Refund Evidence Dossier: Organized export of flagged click IDs, timestamps, behavioral signals, and video recordings formatted for Google/Meta billing disputes.
- WebGL texture constraint: A fingerprinting check that detects mismatches between a browser’s claimed device and its actual graphics‑stack behavior.
FAQ
Will this block Googlebot or hurt my SEO?
No. The default whitelist includes verified Googlebot and Bingbot user agents and IP ranges. You can add any other crawlers you depend on. The detection runs client‑side and does not alter robots.txt or server responses.
How long until I see refund money?
Refund timelines depend on Google and Meta review cycles (typically 2–8 weeks). BotRefund prepares the dossier instantly; the platforms control approval speed.
What if my site already uses Cloudflare or a WAF?
BotRefund complements edge WAFs. The WAF stops volumetric attacks; BotRefund catches sophisticated bots that pass edge checks but fail behavioral verification. Both can run simultaneously.
Does the snippet slow down page load?
The script is lightweight and loads asynchronously. Typical impact is well under 50 ms; most users see no measurable change in Core Web Vitals.
Can I adjust sensitivity for unusual but legitimate traffic?
Yes. The dashboard lets you tune thresholds per signal category. Start with defaults, review flagged sessions in the first week, then relax any signal that produces false positives on your specific audience.
What ad spend levels does BotRefund support?
Tiered plans cover under $10k/mo up to over $5M/mo. Enterprise contracts include dedicated escalation paths and custom SLAs.
Is there a long‑term contract?
No credit card required to start the free audit. Monthly plans can be cancelled anytime; enterprise terms are negotiated per account.
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