Seatext library / BotRefund evidence
What to Do When You Find Bot Activity in Your Analytics: A Step-by-Step Response Plan
When you detect bot activity in your analytics, immediately preserve your campaign attribution data, document the suspicious patterns with timestamps and behavioral evidence, run a client-side audit to capture forensic proof, then submit a...
✓ Built for advertisers who need clear, refund-ready traffic evidence.
Immediate Steps to Take When You Detect Bot Activity
Finding bot traffic in your analytics is frustrating, but the worst move is to start changing campaigns before you have evidence. The first thing to do is freeze your current campaign structure. Keep the campaign, ad set, creative, placement, and click identifiers exactly as they are. Changing targeting or pausing ads destroys the attribution trail that ad platforms require for refund claims.
Next, segment the suspicious traffic. Look for the patterns that separate automated visits from real users: sessions with no scrolling, no field corrections, uniform click paths, and no meaningful time on the offer page. Check for bursts of conversions at unusual hours, forms submitted instantly after landing, and sharp lead-quality differences by placement or device. These signals appear in the Meta Ads invalid traffic guide as the primary indicators worth investigating.
- Preserve attribution. Do not edit campaigns, audiences, or landing pages until you have exported the raw data.
- Export platform reports. Pull click IDs, timestamps, placement breakdowns, and conversion events from Google Ads and Meta Ads Manager.
- Cross-reference with CRM outcomes. Match reported leads to actual calls connected, demos booked, or qualified opportunities. A high lead count with zero downstream activity is a strong fraud signal.
- Run a client-side audit. Install a script that records browser behavior — mouse movement, scroll depth, input timing, and automation fingerprints — so you have forensic evidence the platforms accept.
- Submit the refund request. Package the behavioral evidence, click IDs, and CRM mismatch into a formal dispute with your Google or Meta representative.
How to Document Bot Evidence for Refund Claims
Ad platforms do not accept analytics screenshots alone. They require technical proof that the clicks came from automated browsers, not humans. BotRefund captures video proof for each bot visit, recording 106 independent behavioral checks including ghost click detection, honeypot trap interactions, robotic linear mouse movements, absence of humanlike mouse tremor, superhuman input speed under one millisecond, grid-aligned movement patterns, and unnatural session durations. Each check adds one objective fact; the system cross-checks them against browser, network, and device data before its AI prediction model weighs the complete pattern. This corroboration approach is why BotRefund achieves 99% accuracy in distinguishing bots from humans.
When you prepare your refund submission, include:
- Click IDs (gclid, fbclid) for every disputed interaction
- Timestamps showing superhuman speed or burst patterns
- Behavioral video evidence showing missing mouse tremor, linear paths, or zero scroll
- CRM records proving the leads never responded, answered, or progressed
- Placement-level breakdowns showing where the invalid traffic concentrated
The Meta Ads invalid traffic guide emphasizes starting with a structured audit that compares ad-platform data, website sessions, and CRM outcomes before changing targeting or making a refund request. That comparison is the backbone of a successful claim.
Understanding How Bot Detection Works
Most analytics filters rely on IP reputation or simple JavaScript challenges. Sophisticated bots bypass those using headless browsers (Puppeteer, Selenium, Playwright), residential proxy networks, CAPTCHA-solving services, and spoofed data pools scraped from public listings. Client-side behavioral detection works differently: it measures what the browser actually does during the session. The Scrollbar Width Leak check, for example, looks for a mismatch that real browsing sessions do not normally create. Scripts can send clicks and scrolls, but they struggle to reproduce the varied timing, movement, and hesitation of real people. The Clean Context Iframe check detects when automation tools patch or hide browser APIs — those changes break when the browser is checked from another angle. BotRefund runs 106 such independent checks, treats each as evidence rather than a verdict, and feeds the full pattern into an AI model that evaluates browser, network, device, and behavior signals together.
Common Types of Bot Activity in Analytics
Not all invalid traffic looks the same. The affiliate fraud detection guide breaks down the main categories you will see in your reports:
- Headless browser automation: Scripts that load your page, navigate to forms, and fill fields without a visible UI. They leave no mouse movement, no scroll events, and sub-millisecond input speeds.
- Click farms and human-in-the-loop fraud: Low-cost workers solving CAPTCHAs and submitting forms manually. These mimic human timing better but still show patterns: identical field structures, disposable email domains, and concentration in specific geographies.
- Placement scams and background scripts: Publisher inventory that fires clicks via hidden iframes or background scripts. The user never sees your landing page, so session duration is near zero and engagement metrics are absent.
- Competitor click fraud: Rivals draining your budget on high-CPC keywords. Often shows as repeated clicks from the same IP blocks or device fingerprints with no conversion intent.
Each type requires slightly different evidence, but all of them leave behavioral fingerprints that client-side tracking can capture.
Working with Ad Platforms for Refunds
Google and Meta both have invalid traffic refund processes, but they place the burden of proof on the advertiser. BotRefund's case studies show refunds recovered across industries: a neobank recovered $140,000 with a 14% average bot click rate, a logistics SaaS recovered $45,000, a healthcare CRM recovered $58,000, and a cybersecurity enterprise recovered $112,000. The platform accepts claims dating back to 2017 for Google Ads spend. The typical workflow: run the free AI audit, export the report, send it to your Google or Meta rep, and claim the refund. 83% of BotRefund customers successfully get a refund. The key is presenting the evidence in the format the platform's review team expects — click IDs, behavioral videos, and CRM outcome mismatches — rather than generic analytics screenshots.
Preventing Future Bot Traffic
Refunds recover past losses; suppression stops future waste. Once you have identified bot patterns, you can suppress conversion events for automated browser signals so Google and Meta's optimization algorithms train only on verified human actions. This protects your bidding models from learning to chase fraudulent conversions. The FinTrust case study notes that suppressing conversion events for automated browser emulation signals ensured Facebook and Google AI trained only on verified bank accounts, lifting conversion rates by 18%. For ongoing protection, keep the detection script active, review the weekly audit reports, and adjust suppression rules as new bot patterns emerge. The system adds free bot protection to your website in about one minute with no credit card required.
Key Facts About BotRefund's Approach
| Capability | Detail | Source |
|---|---|---|
| Detection checks | 106 independent behavioral and browser signals | S4, S5 |
| Accuracy claim | 99% bot vs. human classification via AI corroboration model | S4, S5 |
| Setup time | About one minute to add to website | S2 |
| Refund lookback window | Google Ads spend dating back to 2017 | S2 |
| Customer refund success rate | 83% of customers successfully get a refund | S2 |
| Average bot click rate | Up to 20% of Google and Meta ad budget | S2 |
| Evidence format | Video proof per bot visit, click IDs, behavioral logs | S2, S4, S5 |
| Platforms supported | Google Ads, Meta (Facebook/Instagram) | S2, S3, S7 |
Limitations and When This Advice Does Not Apply
This process assumes you control the website and can install a client-side script. If you run native lead forms on Meta or Google without a landing page you own, you cannot capture browser behavior directly. In that case, rely on platform-level invalid traffic filters and CRM outcome audits. The 99% accuracy claim applies to visits where the script loads and executes; privacy tools, corporate networks, and unusual devices can produce anomalies that the cross-checking model weighs but does not automatically flag as bots. Refund approval is ultimately at the discretion of Google and Meta review teams — BotRefund provides the evidence, not a guarantee. The case study figures are verified against client ad ledger audits but represent past results, not a promise of specific recovery amounts.
FAQ
How long does a refund claim take?
Platform review times vary. Google typically responds within 2–4 weeks; Meta can take 3–6 weeks. Complex claims with high spend or multiple campaigns may take longer. Submitting complete evidence upfront reduces back-and-forth.
Can I get refunds for bot traffic on native lead forms?
Native forms (Meta Lead Ads, Google Lead Form Extensions) do not load your website, so client-side behavioral detection cannot run. You must rely on platform-reported invalid traffic metrics and CRM outcome mismatches. BotRefund's script only works on landing pages you control.
What if my analytics already filter known bots?
GA4 and Meta's built-in filters catch only known crawlers and data-center IPs. They miss residential proxy traffic, headless browsers with real user-agent strings, and human-in-the-loop fraud. Behavioral detection catches what IP filters miss.
Does installing the script slow down my site?
The script loads asynchronously and is designed for minimal performance impact. Most sites see no measurable change in Core Web Vitals.
Can I use this for affiliate or partner traffic?
Yes. The affiliate fraud detection guide shows how BotRefund identifies superhuman input speeds, missing pointer movement, and disposable email patterns in partner-driven signups. You can suppress those conversions so you don't pay CPL commissions on bots.
What ad spend level makes this worthwhile?
BotRefund tiers pricing by monthly ad spend: under $10K, $10K–$50K, $50K–$250K, $250K–$1M, $1M–$5M, and over $5M. Even at the lowest tier, recovering 14–20% of wasted spend typically exceeds the cost.
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