How to Use BotRefund to Exclude Poor Traffic from Meta and Google Campaigns

To exclude poor traffic with BotRefund, install the onsite tracking script on your landing pages, let it gather session-level behavioral evidence across your paid campaigns, then use the dashboard's flagged sessions and refund-ready reports to suppress conversion events in Meta Ads Manager and Google Ads or to file invalid-activity claims. The platform correlates each suspicious session with its originating click ID (GCLID or fbclid), campaign, placement, and creative so you can block or exclude the exact traffic sources that deliver automated or low-quality visits.

What BotRefund does and how it identifies poor traffic

BotRefund sits on your website and observes every visitor session that arrives from paid clicks. It does not rely on IP reputation lists alone. Instead, it runs over 110 independent checks per session covering biometric and behavioral interactions, browser and device consistency, network context, pointer and scroll behavior, click and typing timing, rendering details, and navigation flow. Each check produces an objective fact about the visit — for example, whether the mouse moved in unnaturally straight lines, whether scroll events occurred at superhuman speed, or whether the browser leaked automation fingerprints such as a mismatched scrollbar width. A single anomaly is never treated as a verdict; the system cross-checks every signal against the others and feeds the complete pattern into a prediction model that classifies the session as bot or human with 99% confidence when the evidence supports it.

This approach differs from server-side log analysis, which only sees IP addresses, headers, and user-agent strings. Server-side tools miss advanced botnets that rotate residential proxies and mimic legitimate headers. Client-side observation catches the behavioral gaps that automation tools cannot easily fake: the tiny tremors in human mouse movement, the hesitation before a click, the varied timing of form field interactions, and the natural scroll patterns that come from reading.

Prerequisites before you start

• Active Meta or Google Ads campaigns sending traffic to landing pages you control.
• Ability to add a JavaScript snippet to those landing pages (or to your tag manager).
• Access to your CRM or lead database to match BotRefund's session IDs with downstream outcomes (calls connected, demos booked, qualified opportunities).
• Admin or analyst permissions in Meta Ads Manager and Google Ads to create conversion suppression rules or file invalid-activity claims.

If you cannot edit the landing page code, you cannot deploy the behavioral layer. In that case, you are limited to platform-side invalid-traffic filters, which the source material notes catch only a fraction of automated activity.

Step-by-step implementation process

1. Create a BotRefund account and get the tracking script. The script loads asynchronously and does not block page rendering.
2. Install the script on every landing page that receives paid traffic. Include the click ID parameter (GCLID for Google, fbclid for Meta) in the page URL so BotRefund can attribute each session to its originating campaign, ad set, creative, and placement.
3. Run a free bot audit. BotRefund offers a free audit that scans recent traffic and returns a sample report. Use this to confirm the script is firing and to see the volume of flagged sessions before committing.
4. Let the system collect data for at least one full weekly cycle. Traffic patterns vary by day of week and time of day. A week of data captures placement-level spikes, creative-level quality differences, and audience-expansion anomalies.
5. Review the dashboard's flagged sessions. Each flagged session shows the click ID, timestamp, campaign hierarchy, placement, device, and a signal-by-signal breakdown (e.g., ghost click detected, honeypot trap triggered, superhuman input speed <1ms, grid-aligned mouse movement, no scrolling, unnatural session duration).
6. Cross-reference flagged sessions with CRM outcomes. Export the list of flagged click IDs and check whether those leads resulted in connected calls, booked demos, or qualified opportunities. The source material emphasizes that a high reported lead count paired with zero downstream outcomes is a primary indicator of invalid traffic.
7. Create suppression rules in your ad platforms. In Meta Ads Manager, use the flagged placement, creative, or audience-expansion segments to exclude or narrow targeting. In Google Ads, upload the flagged GCLIDs as conversion adjustments or use the invalid-activity claim form with BotRefund's refund-ready report attached.
8. File refund claims where warranted. BotRefund formats each finding into a report that includes click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning structured in the format Google and Meta reviewers expect. The company's team has negotiated over 2,500 audits and achieves an 83% recovery rate across clients.
9. Monitor and iterate. After exclusions or claims, watch the next week's flagged-session volume and CRM match rate. Adjust targeting or creative based on which placements or audiences produced the highest bot rates.

Key signals BotRefund uses to flag poor traffic

The platform groups its 110+ checks into behavioral categories. The following are the most actionable for exclusion decisions:

• Ghost click detection: Clicks that fire without the natural sequence of human intent (no hover, no approach movement, no pre-click hesitation).
• Honeypot trap interactions: Bots that click or fill hidden form fields or invisible links that real users never see.
• Robotic linear mouse movements: Pointer paths that are unnaturally straight, lacking the micro-curves and corrections of human motion.
• Absence of humanlike mouse tremor: Missing the tiny imperfections and jitter typical of physiological movement.
• Superhuman input speed (<1ms): Form submissions, clicks, or keystrokes faster than a person can physically perform.
• Grid-aligned movement patterns: Mouse trajectories that snap to precise pixel lines or blocks instead of natural curves.
• Absence of clicks or scrolling: Sessions that stay completely static, loading the page but never interacting.
• Unnatural session durations: Visits that are too short (instant bounce), too long (idle tab), or too uniform across many sessions.
• Scrollbar width leak: A browser fingerprint mismatch where automated browsers reveal inconsistent scrollbar dimensions.
• Clean context iframe anomalies: Automation tools that patch or hide browser APIs often break when the browser is checked from an isolated iframe context.

Each signal is kept as evidence, not a verdict. The AI model weighs the complete pattern across browser, network, device, and behavior data. This corroboration is why the platform reaches 99% confidence instead of producing false positives from privacy tools, corporate networks, or unusual devices.

How to verify the exclusion is working

1. After applying suppression rules or filing claims, wait one full attribution window (typically 7 days for Meta, 30 days for Google).
2. Compare the flagged-session rate before and after. The dashboard shows trend lines for bot percentage by placement, creative, and audience.
3. Check CRM match rate: the percentage of paid clicks that become qualified leads should rise as bot traffic is removed.
4. Review cost per qualified lead (not cost per raw lead). If CAC drops while lead volume holds, the exclusion is working.
5. If you filed refund claims, track the credit status in Google Ads' billing section or Meta's account quality center. BotRefund's reports are structured to match the evidence format platform reviewers require.

A common mistake is treating every unresponsive contact as fraud and over-excluding audiences. The source material warns: "Not every bad lead is a bot, and that matters. Treating every unresponsive contact as fraud can make a team exclude a valuable audience." Always cross-reference flagged sessions with CRM outcomes before changing targeting.

Limitations and when this approach does not apply

• No landing page control: If you send traffic to a third-party form or a platform-hosted instant experience, you cannot install the client-side script.
• Very low traffic volume: Statistical confidence requires enough sessions to build patterns. The free audit will indicate whether volume is sufficient.
• Offline conversion imports only: If you only import offline conversions without click IDs, you cannot link BotRefund's session evidence to the original paid click.
• Platform-side automatic credits: Google and Meta already issue some invalid-activity credits automatically. BotRefund targets the portion their systems miss — typically advanced botnets using residential proxies and behavioral mimicry.
• Non-paid traffic: The tool is built for paid-click attribution. It does not replace a general WAF or CDN bot shield for organic or direct traffic.

Key facts

FAQ

How long before I see flagged sessions in the dashboard?

Sessions appear in near real-time once the script is live. For reliable exclusion decisions, wait at least one full weekly cycle to capture day-of-week and placement-level variance.

Can I use BotRefund without filing refund claims?

Yes. Many teams use the flagged-session data solely to suppress conversions in Meta and Google, which stops the platforms' bidding algorithms from optimizing toward bot traffic. The refund-ready report is optional but increases recovery odds.

Does BotRefund block bots in real time?

The primary product is detection and evidence, not a real-time firewall. You use the evidence to exclude traffic sources in the ad platforms. Some enterprise plans offer real-time conversion suppression via API.

What if my CRM doesn't store click IDs?

You need the click ID (GCLID or fbclid) to link a flagged session to its originating campaign. If your forms or CRM strip these parameters, add hidden fields to capture them on submit. Without click IDs, you can still see aggregate bot rates by placement but cannot suppress at the click level.

How does this differ from Cloudflare or a WAF bot shield?

Edge shields (Cloudflare, Akamai, etc.) operate at the network layer and excel at DDoS mitigation and known-bot IP blocking. BotRefund operates at the marketing layer: it preserves attribution, observes the post-click visitor journey, and produces evidence formatted for ad-platform refund reviewers. The two layers can coexist.

What does the free bot audit include?

The audit scans your recent paid traffic, runs the full signal suite, and returns a sample report showing flagged sessions, bot percentage by placement, and an estimate of recoverable spend. No commitment is required to run it.

Can BotRefund help with TikTok, LinkedIn, or other paid channels?

The source material focuses on Google and Meta. The detection engine is platform-agnostic — it observes browser behavior regardless of traffic source — but the refund-negotiation experience and report formatting are specific to Google and Meta's claim processes.

To flag a campaign with BotRefund, you add the BotRefund script to every landing page that receives paid traffic from Meta or Google. The script silently records browser, network, device, and behavioral signals — such as mouse movement, scroll depth, input timing, and rendering anomalies — for each visitor session. After enough traffic accumulates, you open the BotRefund dashboard, select the campaign or date range, and generate a report that maps suspicious sessions to their click IDs (GCLID for Google, fbclid for Meta), placement, creative, and timestamp. That report is formatted to match the evidence structure each platform’s review team expects. You then submit the claim through the platform’s invalid-activity or refund workflow, and BotRefund supports the negotiation with documentation and follow-up arguments.

What BotRefund Does and Why Flagging Matters

BotRefund is a client-side detection and evidence layer built specifically for paid-traffic refunds. Unlike server-side log analysis that only sees IP addresses and headers, BotRefund runs in the visitor’s browser and captures 110+ independent signals — including pointer behavior, scrollbar width leaks, clean-context iframe checks, and superhuman input speed — to distinguish automated visits from real people with 99% confidence [S2]. Each finding is cross-checked across browser, network, device, and behavior data before the AI model assigns a bot-or-human verdict [S3].

Flagging a campaign means producing a structured evidence package that ties invalid sessions to the exact paid clicks that brought them. Meta and Google both operate invalid-activity credit systems, but their automated filters catch only a fraction of bot traffic [S6]. A refund-ready report bridges that gap by giving reviewers session-level proof: click IDs, campaign hierarchy, timestamps, session recordings, and signal-by-signal reasoning [S2].

Prerequisites Before You Start

• Active paid campaigns on Meta (Facebook/Instagram) or Google Ads sending traffic to pages you control.
• Ability to add JavaScript to those landing pages (direct access, GTM, or CMS header injection).
• Conversion tracking in place (Meta Pixel, Google Ads conversion tag, or GA4) so you can later correlate BotRefund sessions with reported conversions.
• Admin access to the ad accounts for submitting refund claims.
• At least 7–14 days of traffic after installation to build a representative evidence set.

Step-by-Step: Flagging a Campaign with BotRefund

1. Create a BotRefund account and complete the onboarding flow. The free audit tier lets you verify detection coverage before committing.
2. Install the tracking script on every landing page URL used in the target campaigns. Place it in the <head> so it loads before user interaction. If you use Google Tag Manager, add it as a Custom HTML tag firing on Page View – All Pages.
3. Verify data collection in the BotRefund dashboard. Within minutes you should see live sessions with signal breakdowns (pointer, scroll, timing, rendering, network). Confirm that click IDs (GCLID, fbclid) are being captured alongside each session.
4. Run campaigns normally for 7–14 days. Do not pause or restructure campaigns during this window; you need a stable baseline. BotRefund’s investigation workflow explicitly advises preserving attribution before changing anything [S1].
5. Open the campaign view in the BotRefund dashboard. Filter by campaign name, date range, or traffic source (Meta vs. Google). The UI groups sessions by placement, creative, audience, and device.
6. Review flagged sessions. Each session shows a confidence score, the specific signals that triggered it (e.g., “superhuman input speed <1ms”, “grid-aligned movement patterns”, “absence of humanlike mouse tremor” [S2]), and a session replay.
7. Generate the refund-ready report. Choose the campaign or ad-set level. The report exports a PDF/CSV that includes: click ID, campaign/ad-set/ad, placement, timestamp, session duration, signal summary, and a narrative explanation formatted for platform reviewers [S2].
8. Submit the claim:
   • Google Ads: Tools → Billing → Invalid activity credits → Request credit. Attach the BotRefund report and reference the GCLIDs.
   • Meta Ads: Business Help → Contact Support → Advertising → Billing & Payments → Invalid Traffic. Provide the report with fbclids, campaign IDs, and placement breakdown.
9. Track the negotiation. BotRefund’s team can handle follow-up correspondence, supplying additional session recordings or signal explanations if the reviewer asks. Across 2,500+ audits, 83% of clients recover funds [S2].

Understanding the Evidence BotRefund Collects

BotRefund’s 110+ checks fall into six families. No single signal is a verdict; the AI model weighs the complete pattern [S3].

Each session receives a confidence score. BotRefund only flags sessions where the corroborated pattern reaches 99% confidence [S2]. The report also preserves attribution metadata (campaign, ad set, creative, placement, device, click ID) so the evidence maps 1:1 to the line items in Ads Manager or Google Ads.

Submitting Refund Claims to Meta and Google

Google Ads Invalid Activity Credit

Google’s system issues automatic credits for some invalid clicks, but the majority of sophisticated bot traffic requires a manual claim [S6]. The claim form asks for click IDs, date range, and a description. Attach the BotRefund PDF. Google’s review team looks for: GCLID-level mapping, timestamp alignment, and a plausible explanation of why the clicks are invalid. BotRefund’s report provides all three.

Meta Invalid Traffic Refund

Meta does not publish an automated credit dashboard for advertisers. You open a support case under “Invalid Traffic” and supply fbclids, campaign IDs, placement breakdown, and the evidence report. Meta reviewers expect to see placement-level quality differences — e.g., a sharp lead-quality drop on Audience Network vs. Facebook Feed — which BotRefund’s campaign-pattern signals surface [S1].

Common Mistakes and How to Avoid Them

Limitations and When This Advice Does Not Apply

• Non-paid traffic: BotRefund flags sessions tied to paid click IDs. Organic, direct, or email traffic is not covered by ad-platform refund policies.
• Pages you cannot tag: If traffic lands on third-party funnels (e.g., lead-gen forms hosted by a partner) where you cannot inject JavaScript, BotRefund cannot collect client-side signals for those sessions.
• Very low volume campaigns: Fewer than ~500 clicks in the analysis window may not produce statistically reliable signal clusters.
• Platform policy changes: Google and Meta update invalid-activity definitions. BotRefund updates its report format accordingly, but past success does not guarantee future approval.
• Fraudulent advertiser behavior: If the advertiser themselves generates invalid clicks, the platforms will deny the claim and may suspend the account.

Key Facts

FAQ

How long does it take to get a refund after submitting the report?

Google typically responds in 5–15 business days. Meta support cases can take 2–6 weeks depending on queue depth and whether the reviewer requests additional evidence. BotRefund’s negotiation support aims to shorten this by providing complete documentation upfront.

Can I use BotRefund only for the audit and file the claim myself?

Yes. The dashboard lets you export the refund-ready report without engaging BotRefund’s negotiation team. However, the 83% recovery rate reflects end-to-end handling including follow-up correspondence [S2].

Does BotRefund block bots in real time or only flag them for refunds?

BotRefund’s primary product is detection and evidence for refunds. It can suppress conversion events for flagged sessions (preventing pixel poisoning) but does not act as a WAF or edge blocker [S7].

What if my campaigns use server-side tracking (CAPI/Offline Conversions) only?

BotRefund still needs the client-side script on the landing page to collect behavioral signals. Server-side events alone do not provide the browser-level evidence platforms require for manual refund review.

Is there a minimum spend threshold to make this worthwhile?

BotRefund’s pricing scales with traffic volume. The free audit lets you measure the bot rate first. In the FinTrust case, a 14% bot click rate on significant spend yielded a $140k recovery [S8].

Can BotRefund differentiate between competitor click fraud and general bot traffic?

The signals identify automation, not intent. Competitor click fraud is a subset of automated traffic. The report shows the pattern (e.g., bursts from specific placements or geos) which you can correlate with competitive intelligence, but BotRefund does not attribute motive.

What happens if Google or Meta rejects the claim?

BotRefund’s team reviews the rejection reason, supplements the evidence with additional session recordings or signal explanations if applicable, and resubmits. The 83% recovery rate includes successful appeals after initial denials [S2].

To get a free bot audit from BotRefund, you create an account, add their tracking code to your landing pages, and let the system observe live traffic from your Google and Meta campaigns. The audit runs automatically, analyzing over 100 behavioral, browser, hardware, network, and attribution signals per session. When enough data is collected, you receive a refund-ready report that includes click IDs, campaign details, timestamps, session recordings, and a signal-by-signal explanation formatted for platform review teams.

What the free BotRefund audit covers

The free audit examines every paid session that reaches your site after a Google or Meta click. It does not rely on IP lists or user-agent strings alone. Instead, it runs 106 independent client-side checks — such as scrollbar width consistency, clean context iframe behavior, pointer tremor, input speed, and grid-aligned movement — to build a corroborated picture of whether a visitor is human or automated. Each check contributes one piece of evidence; the final verdict comes from an AI model that weighs the complete pattern across browser, network, device, and behavior data. BotRefund states this approach reaches 99% confidence when the session evidence supports it.

The audit also preserves attribution. It captures the click identifier (GCLID for Google, fbclid for Meta), campaign, ad set, creative, placement, and timestamp so that any invalid traffic finding can be tied directly to the paid click that brought the visitor. This attribution layer is what allows the report to be submitted to Google and Meta in the format their reviewers expect.

Prerequisites before you start

• Active paid campaigns on Google Ads or Meta Ads (Facebook/Instagram) sending traffic to a website you control.
• Ability to add JavaScript to the landing page or site header. The snippet is lightweight and loads asynchronously.
• Admin access to the ad accounts if you later want to file a refund claim, because the claim must be submitted from the account that incurred the spend.
• Conversion events configured in the ad platforms (lead forms, purchases, sign-ups) so the audit can correlate bot signals with conversion outcomes.

If you run campaigns through an agency, coordinate with them so the tracking code is placed on the correct pages and the audit report is shared with the team that manages refund requests.

Step-by-step: how to request and run the free audit

1. Visit the BotRefund site and click "Get free bot audit." The call-to-action appears on the homepage, blog posts, and detection documentation pages.
2. Create an account. You'll provide an email and set a password. No credit card is required for the free audit tier.
3. Add your domain. Enter the website URL where your paid traffic lands. BotRefund will generate a unique tracking snippet for that domain.
4. Install the snippet. Paste the JavaScript into the <head> of your landing page or site-wide header. The script loads asynchronously and does not block page rendering.
5. Verify installation. In the BotRefund dashboard, confirm the script is firing by visiting your own landing page with a test click (or using the platform's verification tool). You should see your test session appear in the live view.
6. Let traffic accumulate. Run your campaigns normally. The audit needs a representative sample of paid sessions. For most advertisers, a few days to a week provides enough data, depending on volume.
7. Receive the audit report. BotRefund processes the collected sessions and delivers a report that lists each flagged session with click ID, campaign metadata, timestamps, session recording, and the specific signals that contributed to the bot classification.

What happens after you install the tracking code

Once the snippet is live, BotRefund begins evaluating every session that arrives with a paid click parameter. For each session it records:

• Browser and device fingerprints (canvas, WebGL, audio context, font enumeration, etc.)
• Network context (IP reputation, data center vs. residential, VPN/proxy indicators)
• Behavioral signals (mouse movement, scroll depth, click timing, form interaction patterns, session duration)
• Evasion checks (debugger detection, automation framework artifacts, iframe context consistency)

Each signal is scored independently. A single anomaly — such as a missing scrollbar width variation — does not trigger a bot verdict. The system cross-checks every signal against the others and feeds the full pattern into its prediction model. Only when multiple independent signals align does the session receive a high-confidence bot classification. This corroboration approach is why BotRefund cites 99% confidence in the traffic it flags.

During the audit period you can watch sessions populate in the dashboard. The live view shows session status (human, suspicious, bot), the click ID, campaign, and a replay link. This transparency lets you spot placement-level spikes or creative-level quality differences before the final report arrives.

Reading the audit report: signals and confidence levels

The final report groups sessions by classification and provides a summary table:

• Human sessions — normal behavioral variance, no correlated anomalies.
• Suspicious sessions — one or two signals out of range but insufficient corroboration for a bot verdict. These are flagged for review but not included in refund claims.
• Bot sessions — multiple independent signals align (e.g., superhuman input speed <1ms, linear pointer paths, no scroll engagement, data center IP, automation framework leak). Each bot session includes a signal-by-signal breakdown explaining why it was classified as automated.

The report also aggregates findings by campaign, ad set, creative, placement, and device. This lets you see, for example, that 27% of clicks from Audience Network placements were bots while Search placements showed 3%. You can then decide whether to exclude the problematic placement, adjust targeting, or proceed with a refund claim.

From audit to refund: the evidence package Google and Meta accept

BotRefund formats the audit output into a refund-ready package that matches what Google and Meta review teams request. The package includes:

• Click IDs (GCLID/fbclid) for every flagged session
• Campaign, ad set, creative, and placement identifiers
• Timestamps with timezone
• Session recordings or reconstructed interaction timelines
• Signal-by-signal reasoning for each bot classification
• A summary of total invalid spend by campaign and date range

According to BotRefund, across 2,500+ brands audited, 83% of clients recover funds from Google and Meta using these reports. The high approval rate comes from three factors: the 99% detection confidence, the platform-ready report format, and experience negotiating claims with both platforms' review teams. BotRefund can also support the negotiation directly, providing documentation and arguments that platform reviewers need to approve the credit.

For Google Ads, the claim maps to the Invalid Activity Credit system. For Meta, it maps to the Invalid Traffic refund process. In both cases, the platform's automated systems catch some invalid traffic automatically, but the audit surfaces additional bot clicks that the platform missed — especially advanced botnets using residential proxies and behavioral mimicry that evade server-side filters.

Limitations and when the free audit may not be enough

• Traffic volume matters. Very low-spend campaigns may not generate enough sessions for a statistically meaningful audit within the free tier's observation window.
• Server-side only campaigns. If you use server-side conversion APIs without client-side pixel fires, the audit cannot observe the browser session. BotRefund requires the visitor to load the page with the snippet installed.
• Non-Google/Meta channels. The free audit is optimized for Google and Meta paid traffic. Other ad platforms (TikTok, LinkedIn, Twitter/X) may not pass click identifiers in a format the system can attribute.
• Privacy tools and corporate networks. Legitimate users on strict corporate proxies, VPNs, or privacy browsers can trigger individual signals. The cross-checking model reduces false positives, but edge cases exist. The report marks these as "suspicious" rather than "bot" so you can review them manually.
• Refund approval is not guaranteed. Google and Meta make the final decision. BotRefund's 83% recovery rate is an aggregate across clients; individual outcomes depend on the platform's review, the strength of the evidence, and the specific policy interpretation at the time of claim.

Key facts at a glance

Frequently asked questions

How long does the free audit take to complete?

It depends on your paid traffic volume. Most advertisers see a usable report within 3–7 days. High-volume accounts may have enough data in 24–48 hours. The dashboard shows live session counts so you can gauge progress.

Do I need to pause my campaigns during the audit?

No. Run campaigns normally. The audit observes live traffic without interfering. Pausing would reduce the sample size and could hide placement-level patterns that only appear at scale.

Can I use the free audit report to file a refund claim myself?

Yes. The report is formatted for Google and Meta review teams. You can submit it through each platform's invalid traffic / invalid activity claim flow. BotRefund also offers managed claim support as a paid service if you prefer not to handle the back-and-forth.

What if the audit finds very little bot traffic?

That is a valid outcome. It means your paid traffic is largely human. You still gain a baseline measurement and the confidence that your conversion data is not being poisoned by automation. No refund claim is needed in that case.

Does the tracking snippet affect page speed or Core Web Vitals?

The snippet loads asynchronously and is designed to be lightweight. BotRefund states it does not block rendering. Most sites see no measurable impact on LCP, FID, or CLS.

Can I run the audit on a staging or development site?

The audit requires real paid clicks with valid click identifiers. Staging environments typically do not receive Google or Meta paid traffic, so the audit would have no sessions to analyze. Install on the production landing pages that receive ad clicks.

What happens after the free audit ends?

You keep the report and can act on its findings (exclude placements, adjust targeting, file claims). If you want continuous monitoring, real-time suppression of bot conversion signals, and ongoing claim support, BotRefund offers paid plans. The free audit is a one-time snapshot.

BotRefund does not run a traditional deduplication database. Instead, it detects duplicate and fraudulent leads by examining each visitor session for evidence of automation. When the same bot network or click farm submits multiple forms, the sessions share telltale patterns: identical browser fingerprints, superhuman input speed, missing mouse tremor, grid-aligned pointer paths, and no meaningful page engagement. BotRefund captures these signals client-side, correlates them with the click ID (fbclid or gclid) that brought the visitor, and builds a session-by-session evidence pack that Google and Meta accept for invalid-activity refunds.

To use BotRefund for this purpose, you install its tracking script on your landing pages, let it collect a baseline of traffic, then review the dashboard for clusters of high-confidence bot sessions. Each flagged session includes a click ID, timestamp, campaign metadata, and a signal-by-signal explanation. You can export these clusters, suppress the associated conversion events in your ad platforms, and submit the report for a credit. The workflow is designed for marketing teams, not infrastructure engineers — no CDN changes, no log parsing, no server-side integration required.

What BotRefund Actually Measures

BotRefund runs 106 independent browser checks (plus network and attribution signals) on every visit. Each check produces one objective fact — for example, whether the scrollbar width matches a real browser, whether an iframe context is clean, whether mouse movements show human tremor, or whether inputs occur faster than 1 millisecond. No single check decides "bot"; the system weighs the complete pattern through an AI model that reaches 99% confidence when the evidence supports it. This corroboration approach matters for duplicate leads: a single anomaly could be a privacy tool or corporate network, but a cluster of sessions sharing multiple anomalies across different IPs and user agents is strong evidence of coordinated automation.

Key Signals That Reveal Duplicate or Fraudulent Leads

The source documentation highlights five signal categories worth investigating when lead quality drops:

• Contactability: Disconnected numbers, invalid email domains, repeated addresses, or an unusual concentration of one country code.
• Timing: Several leads arriving in short bursts, forms submitted immediately after landing, or conversions concentrated at unusual hours.
• Session behavior: No scrolling, no field corrections, uniform click paths, and no meaningful time on the offer page.
• Campaign patterns: A sharp lead-quality difference by placement, creative, audience expansion, device, or landing page.
• CRM outcome: A high reported lead count paired with no calls connected, demos booked, qualified opportunities, or repeat engagement.

BotRefund surfaces these patterns automatically. When you see a placement or creative generating leads that share the same behavioral fingerprint — same input speed, same missing tremor, same scrollbar anomaly — you have a duplicate-lead cluster driven by automation, not by real people filling forms twice.

Step-by-Step: Setting Up BotRefund to Audit Lead Quality

1. Add the script to your landing pages. Paste the BotRefund snippet in the <head> of every page that receives paid traffic. The script loads asynchronously and does not block page render.
2. Preserve attribution before changing campaigns. Keep campaign, ad set, creative, placement, and click identifiers (fbclid, gclid) intact in your analytics and CRM. BotRefund ties each session to these IDs so the refund report maps back to the exact paid click.
3. Let traffic accumulate for 7–14 days. A baseline period lets the model calibrate to your normal human traffic. Do not pause campaigns or change targeting during this window.
4. Open the dashboard and filter by confidence. Sessions flagged at 99% confidence are the starting point. Sort by campaign, placement, or landing page to see where bot clusters concentrate.
5. Review session recordings and signal breakdowns. Each flagged session shows a replay, a list of triggered checks (e.g., "Superhuman input speed (<1ms)", "Absence of humanlike mouse tremor"), and the click ID. Confirm the pattern looks like automation, not a privacy tool or unusual device.
6. Export the cluster as a refund-ready report. The report includes click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning formatted for Google and Meta review teams.
7. Suppress conversion events for flagged click IDs. In Google Ads and Meta Ads Manager, use the click IDs to exclude those conversions from your optimization signals. This stops the bidding algorithm from learning on bot data.
8. Submit the refund claim. BotRefund's team can format and negotiate the claim, or you can file it yourself using the exported evidence. Across 2,500+ audits, 83% of clients recover funds.

Reading the Evidence: What a Bot Session Looks Like

A human session shows imperfection: pauses between fields, backspacing, curved mouse paths, variable scroll speed, and time spent reading. A bot session often shows the opposite: every field filled in <1ms, pointer moving in straight grid-aligned lines, no scroll events, no mouse tremor, and a scrollbar width that doesn't match the browser's reported rendering engine. BotRefund's individual checks — such as Scrollbar Width Leak and Clean Context Iframe — each add one independent fact. The AI prediction weighs all 106+ facts together. When you open a flagged session, you see which checks fired and why the model concluded "bot." This transparency lets you explain the finding to a platform reviewer or a skeptical stakeholder.

Integrating With Your CRM and Ad Platforms

BotRefund does not replace your CRM deduplication rules. It operates upstream: it tells you which paid clicks produced automated sessions so you can stop counting those conversions. The practical integration points are:

• Click ID pass-through: Ensure your forms capture fbclid/gclid in hidden fields and write them to the lead record. BotRefund uses the same IDs.
• Conversion API / offline conversions: When you suppress a bot click, also remove or mark the corresponding offline conversion event so the platform's optimization sees the correction.
• Suppression lists: Export the flagged click IDs and upload them as exclusion audiences or invalid-click lists where the platform supports it.
• Reporting cadence: Schedule a weekly review of new high-confidence clusters. Bot traffic patterns shift when fraud operators rotate infrastructure.

Limitations and When This Approach Does Not Apply

• Human duplicates: If a real person submits the same form twice (e.g., double-click, page refresh), BotRefund will see two human sessions. This is a form-handling or CRM deduplication issue, not a bot issue.
• Low-volume campaigns: The model benefits from volume to establish a baseline. Very small test campaigns may not generate enough sessions for high-confidence clustering.
• Non-JavaScript environments: If a significant portion of your traffic comes from environments that block client-side scripts (some enterprise proxies, certain embedded browsers), those sessions won't be analyzed.
• Privacy tools and corporate networks: VPNs, anti-fingerprinting extensions, and managed devices can trigger individual checks. BotRefund's cross-checking reduces false positives, but you should still review borderline sessions manually.
• Server-side fraud only: If fraud occurs entirely server-to-server (e.g., API abuse, postback spoofing) without a browser visiting your page, client-side detection cannot see it.

Key Facts

Common Mistakes to Avoid

Practical Scenarios

Scenario 1: Sudden Lead Spike on a New Creative

A new Facebook creative drives a 3x lead volume increase. Cost per lead looks stable. Sales reports zero contactability. BotRefund dashboard shows 87% of the new creative's sessions flagged at 99% confidence — identical pointer paths, superhuman input speed, no scroll. You export the click IDs, suppress the conversions, and file a refund claim for that creative's spend.

Scenario 2: Gradual Quality Decline Across Placements

Over three weeks, lead-to-opportunity rate drops from 12% to 4%. No single placement stands out. BotRefund reveals a cluster of sessions from Audience Network placements sharing the same Clean Context Iframe anomaly and grid-aligned mouse movements. You exclude Audience Network from the campaign, suppress the flagged click IDs, and recover two weeks of spend.

Scenario 3: Competitor Click Fraud on Brand Terms

Brand search campaigns show high click volume but zero conversions. BotRefund detects ghost clicks (click activity without human intent sequence) and trap interactions (honeypot elements triggered) concentrated on a few IP blocks. The refund-ready report includes timestamps and click IDs for each ghost click. You submit the claim and add the IPs to your exclusion list.

Terminology Quick Reference

• Click ID (fbclid/gclid): Unique identifier appended to the landing page URL by Meta or Google when a user clicks an ad. Essential for tying a session to a paid click.
• Invalid activity / invalid traffic: Platform term for clicks or impressions not resulting from genuine user interest (bots, accidental clicks, competitor fraud).
• Pixel poisoning: When bot conversions train the ad platform's optimization algorithm to target more bot-like users.
• Refund-ready report: Evidence package formatted to the platform's review specifications — click IDs, timestamps, session recordings, signal reasoning.
• Suppression: Removing or marking a conversion event so it no longer feeds the bidding algorithm.
• Corroboration: Requiring multiple independent signals to agree before labeling a session as bot. Reduces false positives from privacy tools or unusual devices.

FAQ

Does BotRefund automatically block bots from submitting forms?

No. BotRefund is an evidence and refund layer, not a WAF or form blocker. It detects and documents automated sessions so you can suppress their conversions and claim refunds. For real-time blocking, pair it with a form-level honeypot or a lightweight challenge.

How long before I see results?

Most teams see high-confidence clusters within 7–14 days of installing the script, depending on traffic volume. The model needs a baseline of human traffic to calibrate.

Can I use BotRefund only for Meta (Facebook/Instagram) campaigns?

Yes. The script works on any landing page receiving paid traffic. The refund workflow supports both Meta and Google Ads. You can filter the dashboard by platform.

What if my forms don't capture click IDs today?

Add hidden fields for fbclid and gclid to your forms and write them to the lead record in your CRM. Without click IDs, you can still see bot clusters in BotRefund, but you cannot map them to specific paid clicks for suppression or refund claims.

Does BotRefund work with server-side tracking (CAPI, Enhanced Conversions)?

Yes. BotRefund's client-side evidence complements server-side tracking. When you suppress a bot click, also remove the corresponding server-side conversion event so the platform's optimization sees the correction.

How does BotRefund differ from Cloudflare or a WAF?

Cloudflare and WAFs operate at the network edge (IP reputation, request headers, rate limiting). BotRefund operates in the browser after the click, capturing behavioral, rendering, and interaction signals that edge layers cannot see. They serve different jobs; many advertisers run both (S7).

What does BotRefund cost?

Pricing is not published in the source pack. The homepage references an "Under $10,000/mo" tier and a "Select a range" control. Contact BotRefund for a quote based on your monthly ad spend and traffic volume.

To use BotRefund to identify suspicious sessions, you first add the BotRefund tracking snippet to every page of your site. The snippet runs in the visitor's browser and collects behavioral data such as mouse movement speed, click timing, and scroll activity.

Overview: Why behavioral detection matters

IP‑based filters can be evaded by rotating addresses or using residential proxies. Behavioral signals are harder to fake because they reflect how a real person moves, clicks, and reads a page. BotRefund looks at over a hundred independent browser actions instead of relying only on network data.

Source S1 notes that Meta campaigns often show normal cost per lead while sales teams receive unreachable contacts, a pattern that can hide automated traffic. Source S4 explains that default network filters miss advanced proxies, so client‑side behavioral audits are needed to catch fake clicks that poison conversion tracking.

Detection mechanics: the 106 checks and risk score

BotRefund runs 106 independent checks. Examples include click behavior (ghost click detection), pointer behavior (robotic linear mouse movements), speed behavior (super‑human input speed under 1 ms), path behavior (grid‑aligned movement), engagement behavior (absence of clicks or scrolling), and session behavior (uniform click paths, no field corrections).

Two specific checks described in the source pack are the Scrollbar Width Leak (S3) and the Clean Context Iframe (S5). Each looks for a mismatch that a real browsing session does not normally create, such as altered browser APIs or unexpected scrollbar dimensions.

A single anomaly is not enough to label a visitor as a bot. BotRefund treats each signal as evidence, cross‑checks it with other browser, network, device, and behavior data, and feeds the full pattern into an AI prediction model. This corroboration is why the vendor claims up to 99 % accuracy (S3, S5).

The risk score shown in the dashboard is a weighted sum of the 106 checks. Higher scores indicate stronger evidence of non‑human behavior, but the exact weighting is proprietary; the model decides which combinations matter most.

Setup: adding the snippet and verifying collection

You need access to the website’s HTML or a tag manager, a BotRefund account, and permission to run JavaScript on your pages. No server changes are required.

1. Log in to BotRefund and copy the tracking snippet from the Setup page.
2. Paste the snippet just before the closing tag on every page, or add it through your tag manager as a custom HTML tag.
3. Publish the change and verify that the snippet loads by opening the browser console and looking for the BotRefund object.
4. In the BotRefund dashboard, enable Session recording and set the sensitivity level to Standard (the default catches the most common bot patterns).
5. Allow at least 24 hours for data to accumulate before reviewing results.

Source S2 notes that the snippet can be added in about one minute and that a free bot audit is available without a credit card.

Using the dashboard to review suspicious sessions

After data collection, open the Sessions tab and apply the Suspicious filter. Each flagged session shows a risk score, a timestamp, and a replay button.

Click the replay to watch the visitor’s mouse movements, clicks, and scrolls. Look for the patterns BotRefund highlights: super‑human speed, grid‑aligned pointer paths, missing scroll activity, or uniform click paths that lack natural hesitation.

Use the Export button to download a CSV or PDF report that includes the session ID, risk score, and the raw signal values. This report can be attached to a refund request with Google Ads or Meta.

The risk score is a weighted sum of the 106 checks; higher scores mean the session deviates more from typical human behavior across many signals.

Preparing refund claims for Google Ads and Meta – common pitfalls and workflow

A common mistake is to submit BotRefund data alone. Ad platforms require their own invalid activity reports to corroborate the evidence. Another pitfall is mismatched timestamps; always preserve the original attribution before changing campaigns or pausing ads.

Workflow:

1. Preserve attribution: export the Google Ads or Meta click report for the same date range before making any changes.
2. Download the BotRefund export of flagged sessions (session ID, timestamp, risk score).
3. Match BotRefund timestamps or session IDs to the platform’s click identifiers (GCLID for Google Ads, Meta click ID).
4. If the same clicks appear in both lists as invalid, you have corroborated evidence.
5. Submit the BotRefund export together with the ad‑platform report to start a refund claim.

Source S6 explains that Google offers invalid activity credits but the process is not automatic; understanding how to file a claim is key to recovering money. BotRefund helps navigate this process with an advertised 83 % success rate.

Source S1 adds that Meta advertisers should look at contactability, timing, session behavior (no scrolling, no field corrections, uniform click paths), campaign patterns, and CRM outcomes to separate normal lead‑quality variation from automated activity.

Source S8 shows a real‑world example: the neobank FinTrust suppressed conversion events for automated browser emulation signals, protected lead quality, and recovered $140,000 in ad spend.

Source S7 notes that BotRefund can prepare reports in a format that Google and Meta can review, supporting negotiations with both platforms.

Limitations, best practices, and frequently asked questions

BotRefund works best on sites that receive at least a few hundred sessions per day. Very low traffic may not generate enough data for reliable scoring (S2).

The tool relies on JavaScript execution; visitors who block scripts or use browsers that strip the snippet will not be scored (S2). Non‑web environments such as mobile apps or server‑to‑server API calls are outside BotRefund’s scope; a different fraud solution is needed for those channels.

Because privacy tools, travel networks, or unusual devices can produce unexpected behavior for genuine people, BotRefund treats each signal as evidence, not a verdict, and cross‑checks it with other data (S3, S5).

Practical tips:

• Start with the Standard sensitivity setting; after reviewing a few flagged sessions, adjust up or down based on the rate of false positives you observe.
• Use tag managers to deploy the snippet quickly and to pause or remove it without editing code.
• Schedule automatic exports of the Suspicious report (CSV or PDF) so you have ready‑to‑submit evidence for regular refund cycles.
• When a replay looks legitimate, exclude that session from the export and consider lowering the sensitivity or adding a whitelist rule if available.
• Keep a log of matched GCLIDs or Meta click IDs to speed up the refund claim process.

FAQ:

1. Why does BotRefund look at mouse movement instead of just IP addresses? Because many bots rotate IPs or use residential proxies; behavioral clues are harder to fake (S1, S4).
2. How long does it take to see results after installing the snippet? You can start seeing flagged sessions within a few hours, but waiting 24 hours gives a more stable risk score (S2).
3. What does the risk score mean? It is a weighted sum of the 106 checks; higher scores indicate stronger evidence of non‑human behavior (S2, S3, S5).
4. Can I adjust which signals BotRefund uses? Yes, in the dashboard you can enable or disable specific checks, but the default set is optimized for most ad‑fraud scenarios (S2).
5. Is there a cost for the free bot audit? No. The audit is free and requires no credit card; you only pay if you choose a paid plan for continuous protection (S2).
6. What should I do if BotRefund flags a session that looks legitimate? Review the replay carefully; if you are still unsure, exclude that session from the report and consider lowering the sensitivity (S2).
7. How do I handle false positives in my refund claim? Exclude the questionable sessions from the export, keep a record of why they were removed, and rely on the remaining corroborated evidence.
8. Can I integrate BotRefund with Google Tag Manager? Yes, add the snippet as a custom HTML tag and publish through the container (S2).
9. Is it possible to automate the export of suspicious sessions for regular reporting? Yes, use the Export button to schedule CSV or PDF downloads, or use the API if available (not detailed in sources but implied by export functionality).

To use BotRefund for identifying suspicious visits, you add its tracking script to your landing pages, allow it to record visitor sessions, and then examine the resulting evidence — click IDs, timestamps, session replays, and signal-by-signal reasoning — that shows which visits are automated. The system cross-checks over 100 independent signals (mouse movement, scroll behavior, browser API consistency, timing, network context, and more) and only flags a visit as bot traffic when multiple signals align, producing a report formatted for Google and Meta refund claims.

What BotRefund Actually Does

BotRefund is a client-side auditing layer that sits on your website and observes every paid-visit session after the click. Unlike server-side filters that only see IP addresses and headers, it records browser-level behavior: pointer paths, scroll depth, typing rhythm, iframe context, and hundreds of other micro-signals. Each session receives a verdict — human or bot — backed by a cluster of corroborating evidence, not a single rule. The output is a refund-ready report that includes click identifiers (GCLID, FBCLID), campaign metadata, timestamps, session recordings, and a signal-by-signal explanation that platform reviewers can evaluate.

Key Signals BotRefund Monitors

The platform groups its 110+ checks into behavioral, browser, hardware, network, and attribution categories. The following signals are drawn from the client source pack and represent the concrete evidence layers you can review:

• Pointer behavior: Robotic linear mouse movements, absence of humanlike mouse tremor, grid-aligned movement patterns.
• Speed behavior: Superhuman input speed (under 1 millisecond) for clicks, scrolls, or form submissions.
• Engagement behavior: Absence of clicks or scrolling, sessions that stay too static to match a real browsing journey.
• Session behavior: Unnatural session durations — too short, too long, or too uniform to be human.
• Trap behavior: Honeypot trap interactions — bots responding to hidden or intentionally deceptive page elements.
• Click behavior: Ghost click detection — click activity that happens without the natural sequence of human intent.
• Browser integrity checks: Scrollbar Width Leak (mismatch between reported and actual scrollbar dimensions), Clean Context Iframe (automation tools patching or hiding browser APIs that break under cross-context inspection).
• Attribution signals: Click IDs, campaign, ad set, creative, placement, device, and timestamp preserved per session.

These signals are not used in isolation. As the documentation states, "A single anomaly is not a bot verdict. Privacy tools, travel, corporate networks, and unusual devices can produce unexpected behavior for genuine people. BotRefund keeps this signal as evidence — not a verdict — and cross-checks it against independent browser, network, device, and behavior data."

Step-by-Step: Setting Up BotRefund to Identify Suspicious Visits

1. Create an account and add your domain. Sign up at BotRefund, verify your domain, and choose the sites or subdomains you want to audit.
2. Install the tracking script. Paste the provided JavaScript snippet into the <head> of every landing page that receives paid traffic (Google Ads, Meta Ads, or both). The script loads asynchronously and does not block page rendering.
3. Verify data collection. Visit your own page with a test click (use a UTM-tagged URL or click your own ad in preview mode). Confirm the session appears in the BotRefund dashboard within a few minutes, showing a session recording and signal breakdown.
4. Let traffic accumulate. Run your campaigns normally for at least 7–14 days to gather a representative sample across placements, creatives, audiences, and devices. Do not pause or restructure campaigns during this baseline period — preserving attribution is critical for later refund claims.
5. Review the dashboard. Open the sessions view. Filter by verdict (bot/human), confidence score, campaign, placement, or date range. Each flagged session shows a replay, a list of triggered signals, and the click ID that ties it to your ad platform.
6. Export a refund-ready report. Select the sessions you want to contest and generate the report. It packages click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning in the format Google and Meta reviewers expect.
7. Submit the claim. File the invalid-traffic or invalid-activity claim in Google Ads or Meta Ads Manager, attaching the BotRefund report. BotRefund's team can also handle the negotiation on your behalf.

Understanding the Evidence: From Signals to Verdicts

BotRefund's 99% confidence claim comes from corroboration, not any single check. The AI prediction model weighs the complete pattern across browser, network, device, and behavior evidence. For example, a session might show superhuman input speed (<1ms) and grid-aligned mouse paths and no scroll activity and a Scrollbar Width Leak anomaly. When four independent signals align, the probability of a false positive drops sharply. The platform explicitly avoids rule-based verdicts: "Accuracy comes from corroboration, not one browser tell."

This matters because server-side filters (IP reputation, user-agent lists, data-center blocklists) miss advanced botnets that rotate residential proxies, mimic real user-agents, and execute JavaScript. Client-side observation catches the execution environment itself — the browser APIs, rendering quirks, and human micro-behaviors that automation frameworks struggle to replicate perfectly.

Practical Investigation Workflow

The source pack outlines a structured audit workflow that pairs BotRefund evidence with your own CRM and ad-platform data:

1. Preserve attribution before changing the campaign. Keep campaign, ad set, creative, placement, and click identifiers intact while you investigate. Pausing or restructuring destroys the link between a flagged session and the click you paid for.
2. Compare three data layers. Ad-platform data (reported leads, cost per lead), website sessions (BotRefund recordings, engagement metrics), and CRM outcomes (calls connected, demos booked, qualified opportunities, repeat engagement).
3. Look for the signal clusters that matter. Contactability issues (disconnected numbers, invalid email domains, repeated addresses), timing anomalies (bursts of leads, immediate form submission after landing, unusual hours), session behavior (no scrolling, no field corrections, uniform click paths), campaign-pattern gaps (sharp lead-quality differences by placement, creative, audience expansion, device, or landing page), and CRM outcome mismatches (high reported lead count with zero downstream progress).
4. Segment by placement and creative. Invalid traffic often concentrates in specific placements (e.g., Audience Network, Reels, third-party publisher inventory) or creative formats. Use the click ID and placement data in BotRefund reports to isolate the worst offenders.
5. Decide: suppress, exclude, or claim. You can suppress conversion events for flagged sessions so your bidding algorithms stop optimizing for bots, exclude placements/audiences that consistently deliver invalid traffic, or file refund claims with the platform using the BotRefund report.

Limitations and When This Approach Doesn't Apply

• Client-side only. BotRefund cannot see traffic that never executes JavaScript (e.g., pure HTTP scrapers that don't render the page). Those are caught by server-side logs and platform-level filters.
• Requires script installation. You must control the landing page code. If you send traffic to a third-party form or a platform-hosted instant experience where you cannot inject scripts, BotRefund cannot observe those sessions.
• Not a real-time blocker. The primary product is audit and refund evidence, not a WAF that blocks bots at the edge. It can suppress conversion signals for flagged sessions, but the visit still loads the page.
• Privacy and compliance. Session recordings capture user behavior. Ensure your privacy policy and consent flows cover this data collection, especially under GDPR, CCPA, or similar regulations.
• Platform approval is not guaranteed. Google and Meta make final refund decisions. BotRefund's 83% client recovery rate reflects historical outcomes, not a guarantee.
• Minimum traffic thresholds. Very low-volume campaigns may not generate enough sessions for statistically meaningful signal clusters.

Key Facts

Terminology Quick Reference

• Click ID (GCLID / FBCLID): Unique identifier appended to landing-page URLs by Google Ads and Meta Ads, linking a session to a specific paid click.
• Pixel poisoning: When bot conversions feed false signals into ad-platform optimization algorithms, causing them to bid more for similar low-quality traffic.
• Invalid activity credit (Google) / Invalid traffic refund (Meta): Platform reimbursement programs for clicks/impressions deemed non-genuine.
• Client-side audit: Analysis running in the visitor's browser, capturing behavior, rendering, and API evidence that server logs cannot see.
• Server-side audit: Analysis of web-server logs (IP, headers, user-agent) — useful for basic scraper detection but blind to advanced browser automation.
• Signal cluster: Multiple independent anomalies aligning on the same session, raising confidence that the visit is automated.
• Refund-ready report: Evidence package structured to match the evidentiary standards of Google and Meta review teams.

FAQ

How long does it take to see results after installing the script?

Sessions appear in the dashboard within minutes of a visit. For a statistically useful sample, plan on 7–14 days of normal campaign traffic before drawing conclusions or filing claims.

Does BotRefund block bots in real time?

No. Its core function is forensic evidence collection and refund-ready reporting. It can suppress conversion events for flagged sessions so your bidding algorithms ignore them, but it does not prevent the page from loading.

Can I use BotRefund on Meta Instant Experiences or third-party lead forms?

Only if you can inject the tracking script into the page. Meta Instant Experiences and many third-party form hosts do not allow custom JavaScript, so those sessions cannot be observed client-side.

What if Google or Meta rejects the refund claim?

BotRefund's team supports the negotiation with additional documentation and arguments. Historical data shows an 83% recovery rate across 2,500+ audits, but approval is ultimately at the platform's discretion.

How does BotRefund differ from Cloudflare or other edge bot protection?

Edge providers (Cloudflare, Akamai, etc.) focus on infrastructure protection — DDoS mitigation, WAF rules, CDN delivery. BotRefund focuses on the marketing layer: preserving attribution, observing the post-click visitor journey, and producing evidence formatted for ad-platform refund claims. The two can coexist; many advertisers keep their edge provider and add BotRefund for the evidence layer.

Is there a minimum spend requirement?

The source pack does not specify a minimum spend. The Enterprise tier is noted for budgets under $10,000/mo, suggesting the product serves a range of spend levels. Contact sales for current packaging.

What happens to the data if I pause a campaign?

BotRefund preserves the evidence after a campaign is paused. The session recordings, click IDs, and signal data remain accessible for refund claims filed later.

BotRefund improves lead quality by identifying bot and invalid traffic that reaches your lead forms, then giving you the evidence to stop those signals from poisoning your conversion data. The process has four phases: install the onsite tracker, connect your Google and Meta ad accounts so click IDs (GCLID, FBCLID) attach to each session, review the dashboard's session-by-session evidence, and export refund-ready reports or suppression lists that keep fake leads out of your CRM and your bidding algorithms.

What BotRefund actually does for lead quality

BotRefund sits on your landing pages and collects 110+ behavioral, browser, hardware, network, and attribution signals per visit. Its AI weighs the complete pattern across those signals and labels each session as human or bot with 99% confidence when the evidence supports it. Each finding includes a clear, session-by-session explanation instead of a generic invalid-traffic estimate. The platform then turns those findings into refund-ready reports with click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning formatted for Google and Meta review teams.

When you suppress bot conversion events, the ad platforms' optimization algorithms stop training on fake leads. That means your cost per acquisition reflects real prospects, your lookalike audiences model actual buyers, and your sales team spends time on contacts that can convert. The FinTrust case study showed a 14% average bot click rate and an 18% conversion rate increase after suppressing automated browser emulation signals so Facebook and Google AI trained only on verified bank accounts.

Prerequisites before you start

• Active paid campaigns on Google Ads or Meta Ads — BotRefund needs click identifiers (GCLID, FBCLID) to tie sessions back to specific campaigns, ad sets, creatives, and placements.
• Access to add JavaScript to your landing pages — The tracker must load on every page a paid visitor can reach, including thank-you and confirmation pages.
• Admin or analyst access to your ad accounts — You'll need to connect the accounts in BotRefund so it can pull campaign metadata and later push suppression lists or refund claims.
• A CRM or lead database you can query — You'll compare BotRefund's bot labels against downstream outcomes (calls connected, demos booked, qualified opportunities) to verify the system's accuracy for your traffic mix.

Step-by-step implementation process

1. Create a BotRefund account and add your domain. The onboarding flow generates a unique tracking snippet.
2. Install the tracking script on every landing page. Place it in the <head> so it loads before any user interaction. Confirm it fires by checking the live visitor view in the dashboard.
3. Connect Google Ads and Meta Ads accounts. Use the integrations page to authorize BotRefund. This pulls campaign, ad set, creative, placement, and click-ID data into each session record.
4. Let the system collect a baseline. Run traffic for 7–14 days without changing campaigns. BotRefund builds a behavioral profile of your specific audience and flags anomalies against that baseline.
5. Review the dashboard's flagged sessions. Each flagged session shows the specific signals that triggered the bot label — e.g., superhuman input speed (<1ms), absence of humanlike mouse tremor, grid-aligned movement patterns, or scrollbar width leaks. The evidence is cross-checked across browser, network, device, and behavior data.
6. Export a refund-ready report or suppression list. Reports include click IDs, timestamps, session recordings, and signal-by-signal reasoning in the format Google and Meta reviewers expect. Suppression lists can be uploaded to the platforms' invalid-traffic or conversion-exclusion tools.
7. Submit refund claims or apply suppressions. For Google, file an invalid activity credit claim with the exported evidence. For Meta, use the refund request flow with the same documentation. BotRefund's team has worked through 2,500+ audits and knows how to present evidence to both platforms' reviewers.
8. Monitor lead-quality metrics weekly. Track contactability rates, CRM qualification rates, and cost per qualified lead. Expect the bot percentage to drop as the platforms' algorithms stop optimizing for the suppressed traffic patterns.

Key signals BotRefund analyzes to separate bots from humans

No single signal proves fraud. BotRefund's accuracy comes from corroboration across independent evidence layers. Here are the main categories:

• Click behavior — Ghost click detection catches click activity that happens without the natural sequence of human intent.
• Trap behavior — Honeypot trap interactions watch for bots that respond to hidden or intentionally deceptive page elements.
• Pointer behavior — Robotic linear mouse movements flag unnaturally straight pointer paths; absence of humanlike mouse tremor looks for the tiny imperfections and jitter typical of human movement.
• Speed behavior — Superhuman input speed (<1ms) identifies interactions faster than a person could realistically perform.
• Path behavior — Grid-aligned movement patterns detect 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 catch visit lengths that are too short, too long, or too uniform to be human.
• Browser and device consistency — Checks like Scrollbar Width Leak and Clean Context Iframe reveal mismatches that automated browsers struggle to reproduce.

Privacy tools, corporate networks, and unusual devices can produce unexpected behavior for genuine people. BotRefund keeps each signal as evidence — not a verdict — and cross-checks it against independent browser, network, device, and behavior data before the AI prediction weighs the complete pattern.

How to interpret and act on the data

The dashboard groups flagged sessions by campaign, placement, creative, audience expansion, device, and landing page. Look for sharp lead-quality differences across those dimensions. A practical investigation workflow from BotRefund's Meta invalid-traffic guide recommends:

1. Preserve attribution before changing the campaign. Keep campaign, ad set, creative, placement, and click identifier data intact so you can trace each bad lead back to its source.
2. Compare ad-platform data, website sessions, and CRM outcomes. A high reported lead count paired with no calls connected, demos booked, or qualified opportunities is a strong signal that invalid traffic is inflating your numbers.
3. Check contactability. Disconnected numbers, invalid email domains, repeated addresses, or an unusual concentration of one country code often correlate with bot submissions.
4. Check timing. Several leads arriving in short bursts, forms submitted immediately after landing, or conversions concentrated at unusual hours suggest automation.
5. Check session behavior. No scrolling, no field corrections, uniform click paths, and no meaningful time on the offer page are classic bot patterns.

Not every bad lead is a bot. Treating every unresponsive contact as fraud can make you exclude a valuable audience. Start with the structured audit before changing targeting or making a refund request.

Verification step: confirm the improvement is real

After you submit suppressions or refund claims, wait 14–30 days for the platforms' algorithms to retrain on the cleaned signal. Then compare three metrics against your pre-BotRefund baseline:

• Contactability rate — percentage of leads with working phone/email.
• Qualification rate — percentage of leads that become sales-qualified opportunities.
• Cost per qualified lead — total ad spend divided by qualified leads.

If contactability and qualification rates rise while cost per qualified lead falls, the suppression is working. If they don't move, review whether the flagged sessions were actually bots or whether your lead-quality problem has a different root cause (offer mismatch, audience targeting, form friction).

Limitations and when this advice does not apply

• Organic and direct traffic — BotRefund focuses on paid click attribution. It can still flag bots on organic visits, but refund claims only apply to paid clicks with valid click IDs.
• Low-volume campaigns — If you spend under a few thousand dollars per month, the sample size may be too small for high-confidence pattern detection.
• Single-page funnels without thank-you pages — The tracker needs to see the full journey including the conversion confirmation to attach the click ID to the outcome.
• Platforms beyond Google and Meta — Refund-ready reports are formatted for Google and Meta review teams. Other ad platforms may not accept the same evidence format.
• Genuine low-intent humans — Real people who click accidentally, fill forms casually, or change their minds will not be flagged as bots. Lead-quality issues from weak offers or broad targeting need creative and audience fixes, not bot suppression.

Key facts

FAQ

How long before I see lead-quality improvements?

Most teams see measurable changes in contactability and qualification rates within 14–30 days after submitting suppressions, once the ad platforms' algorithms retrain on the cleaned conversion signal.

Does BotRefund block bots in real time?

BotRefund is primarily an evidence and reporting layer. It identifies and documents bot sessions so you can suppress their conversion signals and claim refunds. It does not function as a real-time WAF or edge blocker.

Can I use BotRefund alongside Cloudflare or another edge provider?

Yes. Many advertisers keep their edge layer for DDoS mitigation and CDN delivery while adding BotRefund for the marketing-focused evidence layer that preserves attribution and creates refund-ready reports.

What if Google or Meta rejects my refund claim?

BotRefund's team supports the negotiation with documentation and arguments their reviewers need. The 83% recovery rate across 2,500+ audits reflects that experience. If a claim is denied, the evidence still lets you suppress those conversion events going forward.

How much traffic volume do I need for reliable detection?

There's no published minimum, but campaigns spending under a few thousand dollars per month may not generate enough sessions for high-confidence pattern detection across all 110+ signals.

Will BotRefund flag legitimate users who use privacy tools or corporate VPNs?

Privacy tools, travel, corporate networks, and unusual devices can produce unexpected behavior. BotRefund treats each anomaly as evidence, not a verdict, and cross-checks it against independent browser, network, device, and behavior data before the AI prediction weighs the complete pattern.

What's the difference between BotRefund and server-side log analysis?

Server-side audits look at IP addresses, request headers, and user-agent data. They catch basic scrapers but struggle with advanced botnets that rotate IPs and spoof headers. BotRefund's client-side audits analyze the visitor's browser behavior — mouse movement, scroll patterns, timing, rendering details — which are much harder for bots to fake consistently.

Direct answer: connect detection to suppression, then feed clean signals to sales

BotRefund runs 110+ browser, network, and behavioral checks on every paid click. When a session is flagged as automated with 99% confidence, the platform can suppress the conversion event before it reaches your Meta Pixel or Google Ads tag. That means your CRM and sales queue only see leads that passed the behavioral audit. You also get a refund-ready report with click IDs, timestamps, and session recordings formatted for Google and Meta review, so the same evidence that protects sales also supports budget recovery.

Prerequisites before you start

• Active Google Ads and/or Meta Ads accounts with conversion tracking installed.
• Access to your website's tag manager or ability to add a lightweight JavaScript snippet.
• Admin rights in your CRM or lead-routing tool to map BotRefund's verified-lead flag.
• A process for reviewing the weekly audit summary BotRefund sends via email or dashboard.

Step-by-step implementation

1. Install the BotRefund snippet. Paste the provided JavaScript into your tag manager or directly on landing pages. The script loads asynchronously and begins collecting 110+ signals (pointer behavior, scroll patterns, browser consistency, network context, etc.) on every paid visit.
2. Enable conversion suppression. In the BotRefund dashboard, turn on "Suppress invalid conversions" for each connected ad account. This stops the conversion pixel from firing when the AI model scores a session as bot traffic with 99% confidence.
3. Map the verified-lead flag to your CRM. BotRefund adds a custom parameter (e.g., br_verified=true) to the lead payload. Configure your form handler or CRM webhook to only route leads with that flag to the sales queue. Leads without the flag can be held for review or discarded.
4. Set up the weekly audit digest. Choose recipients (growth lead, sales ops, finance). The digest shows total paid clicks, bot percentage, suppressed conversions, and a link to the refund-ready report for each platform.
5. File refund claims using the generated reports. Each report includes click IDs (GCLID/FBCLID), campaign/ad set/creative breakdown, timestamps, session recordings, and signal-by-signal reasoning. Submit these through Google Ads' invalid activity form or Meta's ad-quality appeal flow. BotRefund's historical approval rate is 83% across 2,500+ audits.
6. Verify the loop monthly. Compare CRM-reported lead count vs. BotRefund-verified lead count. Check that sales-connected calls, demos booked, and qualified opportunities trend up while raw lead volume may drop. Confirm that ad-platform credit notifications match the refund-ready reports you submitted.

How the evidence layer works

BotRefund does not rely on IP lists or user-agent strings alone. Each visit is scored across independent vectors: biometric interaction (mouse tremor, scrollbar width leak, clean-context iframe), evasion traps (debugger detection, anti-stealth checks), speed behavior (sub-millisecond inputs), and path behavior (grid-aligned movements). A single anomaly is never a verdict; the AI model weighs the complete pattern across browser, network, device, and behavior data to reach 99% confidence. This corroboration approach is why platform reviewers accept the reports.

Key facts from BotRefund's source pack

Common mistakes to avoid

• Suppressing without reviewing. Treat the first two weeks as a calibration period. Spot-check a sample of suppressed sessions in the dashboard before fully automating CRM routing.
• Ignoring placement-level differences. BotRefund often reveals that one placement (e.g., Audience Network) drives 80% of bot traffic while another is clean. Adjust placement targeting instead of pausing the whole campaign.
• Equating all bad leads with bots. S1 notes that weak campaigns attract real but unready people. Use CRM outcome data (no calls connected, no demos booked) alongside BotRefund's verdict to distinguish fraud from fit.
• Filing refund claims without click IDs. Platform reviewers require GCLID/FBCLID. BotRefund's reports include them; exporting raw CSVs from Ads Manager usually does not.

Practical scenarios

Scenario A: Lead-gen campaign with high form volume, low sales contact rate

Install BotRefund, enable suppression, and map br_verified to your CRM. Within a week you see 22% of form submissions flagged as bot. Sales now receives 78% fewer leads but connects with 3x more prospects per 100 calls. The refund-ready report yields a $12,000 Google Ads credit.

Scenario B: E-commerce brand seeing inflated ROAS from click farms

BotRefund detects grid-aligned pointer paths and superhuman input speed on a specific creative. Suppression stops those conversions from poisoning the pixel. Meta's algorithm relearns on verified purchasers; CAC drops 15% in 14 days. The same evidence supports a Meta refund claim for the prior quarter.

Scenario C: Agency managing multiple client accounts

Use the agency dashboard to run free bot audits for prospects. For active clients, centralize the weekly digest in a shared Slack channel. Sales ops at each client maps verified leads to their CRM. Agency files consolidated refund claims quarterly, citing BotRefund's 83% approval rate as a selling point.

Limitations and when this does not apply

• BotRefund only protects paid traffic that lands on pages where the snippet is installed. Organic, direct, or email traffic is not analyzed.
• Suppression works at the pixel level. If your CRM ingests leads via a separate server-side webhook that bypasses the pixel, you must also filter on the br_verified parameter there.
• Refund approval is ultimately decided by Google and Meta. BotRefund's 83% historical rate is not a guarantee for any single claim.
• The 99% confidence threshold means some sophisticated bots may pass if they perfectly mimic human behavior across all 110+ vectors. No system catches 100%.
• Enterprise pricing applies above $10,000/mo ad spend. Smaller accounts use the self-serve tier with the same detection engine but fewer negotiation hours.

Terminology quick reference

• Pixel poisoning: Invalid conversions feeding the ad platform's optimization algorithm, causing it to bid more for bot-like audiences.
• GCLID / FBCLID: Google Click ID and Facebook Click ID — unique identifiers appended to landing-page URLs that tie a session to a specific paid click.
• Refund-ready report: A PDF/CSV package formatted to match the evidence structure Google and Meta reviewers expect.
• Suppression: Preventing the conversion pixel from firing for a specific session based on real-time bot scoring.
• Invalid activity credit: Google's term for reimbursements on clicks/impressions deemed non-genuine.

FAQ

How long until sales sees cleaner leads?

Typically 24–48 hours after the snippet is live and suppression is enabled. The first week includes a learning period where the model calibrates to your traffic patterns.

Does BotRefund block bots from visiting the site?

No. It observes, scores, and optionally suppresses the conversion event. Blocking at the edge (WAF/CDN) is a separate layer; BotRefund's job is evidence and pixel protection.

Can I use BotRefund without filing refund claims?

Yes. Many teams use it solely for lead-quality filtering and pixel protection. The refund-ready reports are generated automatically; you decide whether to submit them.

What happens if a real user is falsely flagged?

The 99% confidence threshold is conservative. In the rare event of a false positive, the session recording and signal breakdown in the dashboard let you override and re-fire the conversion manually.

How does this integrate with HubSpot, Salesforce, or custom CRMs?

BotRefund passes a URL parameter and/or data-layer event. Your form handler or CRM webhook reads br_verified=true and routes accordingly. No native CRM plugin is required.

Is there a free trial or audit?

BotRefund offers a free bot audit that scans a sample of your paid traffic and delivers a one-time report. The full suppression and refund workflow requires a paid plan.

What ad spend level justifies the cost?

If bot clicks are consuming 10%+ of budget (BotRefund sees up to 20% across accounts), the recovered spend and saved sales time usually cover the subscription within the first refund cycle.

To use BotRefund to identify ad traffic with no real conversion promise (bot clicks, fake leads, and automated sessions that will never turn into customers), start by installing its tracking script on your landing pages to capture 110+ behavioral, browser, and network signals for every visitor who clicks through from a paid ad. The tool cross-checks these signals to flag automated sessions with 99% confidence, then generates refund-ready reports formatted for Google and Meta review teams. You do not need to manually parse server logs or guess at fraud patterns; BotRefund builds the evidence record for you.

What "No Promise" Ad Traffic Looks Like

Invalid ad traffic that delivers no conversion promise falls into three common categories: bot clicks that exhaust your budget without any user engagement, fake lead submissions with disconnected numbers or invalid email domains, and automated browsing sessions that never scroll, read, or interact with your offer. Unlike low-intent real users who may simply not be ready to buy, these sessions leave repeatable technical and behavioral patterns: unusually fast form completion, identical field structures, or conversion events with no meaningful page engagement.

This traffic is costly: bots load pages but do not convert, which raises your customer acquisition cost (CAC) and lowers your campaign return on ad spend (ROAS). Without browser-level auditing, you will pay for these visits without knowing they are wasting your budget.

Prerequisites Before Setting Up BotRefund

You only need two things to start using BotRefund for invalid traffic detection: access to your website’s codebase to install the tracking script, and active Google Ads or Meta ad campaigns with conversion tracking enabled. The tool works with all major landing page builders and ad platforms, and does not require you to replace your existing CDN, WAF, or edge security tools.

If you have already noticed suspicious patterns in your ad data — such as a high lead count paired with no connected calls, demos booked, or qualified opportunities — you can upload historical campaign data to BotRefund for a retroactive audit. No prior fraud detection experience is required.

Step-by-Step Process to Identify No-Promise Traffic

1. Install the BotRefund tracking script: Add the provided snippet to your website’s global header or Google Tag Manager container. The script runs client-side to capture behavioral data (scroll depth, click timing, mouse movement) and technical data (browser APIs, device properties, network context) for every visitor who clicks through from a paid ad.
2. Link your ad accounts: Connect your Google Ads and Meta Ads accounts to BotRefund so it can automatically associate visitor sessions with campaign, ad set, creative, placement, and click ID data. This preserves attribution so you can tie invalid traffic directly to specific ad spend.
3. Run an initial audit: After 24-48 hours of data collection, BotRefund will generate a report of flagged sessions, including session recordings, signal-by-signal reasoning, and timestamps. Review the flagged sessions to confirm they match your definition of invalid traffic (e.g., no scroll activity, superhuman input speed, disconnected contact details).
4. Suppress invalid conversion events: Use BotRefund’s integration to block flagged sessions from firing conversion events in your ad platform. This prevents bot traffic from poisoning your campaign optimization data and inflating your CAC metrics.
5. Generate a refund-ready report: For any flagged invalid traffic that has already incurred ad spend, export BotRefund’s formatted report. The report includes all the evidence Google and Meta review teams require: click IDs, campaign details, session recordings, and a breakdown of the signals that indicate automated activity.

How to Verify Your BotRefund Findings

BotRefund flags sessions as potentially invalid based on a weighted analysis of 110+ signals, not a single rule. To verify a finding, check the session replay included in the report: real users will show natural scroll pauses, mouse movement jitter, and field corrections, while bot sessions will have uniform click paths, no scrolling, and form submissions completed in under 1 millisecond.

You can also cross-reference flagged sessions with your CRM data: if a lead has a disconnected phone number, invalid email domain, or no follow-up engagement, it is likely a fake submission with no conversion promise. BotRefund’s reports are structured to make this cross-check easy, with all session data tied to the corresponding lead record.

Key Limitations of BotRefund’s Detection

BotRefund is not a guarantee of refund approval: final decisions rest with Google and Meta’s review teams, who may request additional evidence or deny claims for other policy reasons. The tool also does not catch 100% of invalid traffic, as sophisticated bots that perfectly mimic human behavior may occasionally slip through, though its 99% confidence rate is among the highest in the market.

Additionally, BotRefund is designed for ad spend recovery, not general website security. It does not block DDoS attacks, filter malicious server requests, or replace WAF tools. If your primary goal is infrastructure protection, you will need a separate edge security solution.

Common Mistakes to Avoid When Using BotRefund

• Treating every unresponsive lead as fraud: Not all low-quality leads are bots. Real users may submit incomplete information or not be ready to buy, so always cross-reference BotRefund’s technical signals with your CRM outcomes before filing a refund claim.
• Pausing campaigns before preserving evidence: If you suspect invalid traffic, keep your campaigns running long enough for BotRefund to collect full session data. Pausing campaigns early can delete the attribution data you need to tie bot activity to specific ad spend.
• Submitting generic refund claims: Google and Meta reject most invalid traffic claims because they lack specific evidence. Use BotRefund’s pre-formatted reports, which include the exact click IDs, timestamps, and signal breakdowns their teams require to process claims quickly.

Frequently Asked Questions

Does BotRefund guarantee I will get a refund?

No. BotRefund provides the evidence required to support a refund claim, but final approval decisions are made by Google and Meta. Its 83% client recovery rate is based on historical claim outcomes, but individual results may vary depending on the specifics of your invalid traffic and the platform’s current policies.

How long does it take to see BotRefund flag invalid traffic?

Most users see flagged sessions within 24-48 hours of installing the tracking script and linking their ad accounts. Retroactive audits of historical campaign data can take 3-5 business days to complete, depending on the volume of traffic reviewed.

Will BotRefund slow down my website?

No. The BotRefund tracking script is lightweight (under 10KB) and loads asynchronously, so it does not impact page load speed or user experience for real visitors.

Can BotRefund detect fake leads from Meta lead forms?

Yes. BotRefund analyzes both on-site landing page sessions and Meta lead form submissions, flagging fake leads with the same 110+ signal analysis. It can also tie fake lead form submissions back to specific ad campaigns and placements to support refund claims for lead generation ad spend.

Do I need technical expertise to use BotRefund?

No. The setup process takes less than 10 minutes for most users, and BotRefund’s interface is designed for marketing teams, not developers. The tool also provides pre-built report templates and claim support for users who are new to the refund process.

How is BotRefund different from server-side bot detection tools?

Server-side tools only analyze IP addresses and request headers, which misses advanced botnets that use residential proxies or mimic real user behavior. BotRefund uses client-side behavioral analysis to capture how real users interact with your page (scroll depth, mouse movement, click timing) — signals that bots cannot easily replicate. This makes it far more accurate for identifying invalid ad traffic that server-side tools miss.

What BotRefund actually measures

BotRefund is a bot detection and ad refund platform for Google and Meta campaigns. It does not ship a dashboard widget labeled "contact rate." What it does provide is a session-by-session verdict on whether a paid click came from a human or an automated agent, backed by 110+ behavioral, browser, hardware, network, and attribution signals. Each flagged session includes click IDs, timestamps, session recordings, and signal-by-signal reasoning formatted for Google and Meta refund reviews.

Because the platform identifies which leads are bots, form spam, or otherwise invalid, you can subtract that volume from your raw lead count. The remainder — human, contactable leads — divided by total paid clicks gives you a genuine contact rate. The key is connecting BotRefund's session evidence to your CRM outcomes.

Signals that map to contact quality

BotRefund surfaces several signal clusters that directly indicate whether a lead can be reached:

• Contactability signals — disconnected numbers, invalid email domains, repeated addresses, unusual country-code concentrations.
• Timing signals — bursts of leads in short windows, forms submitted immediately after landing, conversions at unusual hours.
• Session behavior — no scrolling, no field corrections, uniform click paths, no meaningful time on the offer page.
• Campaign patterns — sharp lead-quality differences by placement, creative, audience expansion, device, or landing page.
• CRM outcome correlation — high reported lead count paired with no calls connected, demos booked, qualified opportunities, or repeat engagement.

These signals come from the platform's onsite behavioral audit, not from server logs alone. That means you see what the visitor actually did in the browser — mouse movement, scroll depth, typing rhythm, rendering quirks — which server-side filters miss.

Step-by-step: turning BotRefund data into a contact rate

1. Install the BotRefund script on your landing pages and thank-you pages. The script captures the full visitor journey after the paid click.
2. Run a free bot audit to establish a baseline. The audit returns a session-level report showing which clicks are human, which are bots, and the evidence for each verdict.
3. Export the refund-ready report (CSV or PDF). It contains click IDs (GCLID/FBCLID), campaign/ad set/creative/placement, timestamps, and the signal breakdown for every flagged session.
4. Join the report to your CRM on click ID. Tag each lead as "BotRefund: human" or "BotRefund: bot/invalid."
5. Calculate true contact rate: (Leads tagged human that resulted in a connected call, booked demo, or qualified opportunity) ÷ (Total paid clicks). Compare this to the raw lead-to-contact rate to see the inflation caused by invalid traffic.
6. Segment by campaign dimension — placement, creative, audience, device — to find where contact rate collapses. BotRefund's campaign-pattern signals highlight these splits automatically.
7. Submit refund claims for the bot/invalid portion using BotRefund's formatted evidence. The platform's team negotiates with Google and Meta on your behalf; 83% of clients recover funds across 2,500+ audits.

Common mistake: treating every unresponsive lead as fraud

A weak campaign can attract real people who aren't ready to buy. BotRefund's workflow explicitly warns against labeling every bad lead as a bot. The platform keeps each anomaly as evidence — not a verdict — and cross-checks it against independent browser, network, device, and behavior data before the AI model assigns a 99% confidence verdict. Use the CRM outcome signal (no calls connected, no demos booked) as a secondary filter, not the primary one.

Verification step: does the contact rate improve after suppression?

After you submit refund claims and add BotRefund's suppression lists to your ad platforms (so future bot clicks don't fire conversion pixels), watch the next 7–14 days of CRM data. A genuine contact rate should rise because the denominator (paid clicks) shrinks while the numerator (human leads) holds steady. The FinTrust case study showed a 14% average bot click rate and an 18% conversion rate increase after behavioral auditing and suppression.

Key facts

Limitations and when this approach does not apply

• BotRefund only covers paid traffic from Google and Meta. Organic, direct, referral, or email leads are outside its scope.
• You need click IDs (GCLID/FBCLID) passed through to your CRM. If your forms or tracking strip these, the join step fails.
• The platform does not dial phones or send test emails. It infers contactability from data patterns, not live verification.
• Refund negotiations depend on Google and Meta policy; not all flagged sessions qualify for credit.
• Enterprise pricing applies above $10,000/mo ad spend; smaller accounts use the self-serve tier.

Terminology quick reference

• Invalid traffic — clicks or impressions Google/Meta determine are not genuine user interest (bots, accidental clicks, competitor click fraud, data-center IPs).
• Pixel poisoning — when bot conversions train the ad platform's optimization algorithms on fake outcomes, degrading future targeting.
• Click ID (GCLID/FBCLID) — the unique parameter appended to landing-page URLs that ties a session back to a specific ad click.
• Refund-ready report — evidence packaged in the exact format Google and Meta reviewers expect for invalid-activity claims.
• Suppression list — a list of IPs, device fingerprints, or behavioral signatures sent to the ad platform to block future clicks from known bad actors.

FAQ

Does BotRefund give me a "contact rate" number automatically?

No. It gives you the session-level truth data (human vs. bot) that you join to your CRM to compute the rate yourself.

Can I use BotRefund without submitting refund claims?

Yes. The detection and suppression value stands alone. Many teams use the evidence to clean conversion pixels and improve bidding signals even if they don't pursue refunds.

How long does the free bot audit take?

Typically a few days of traffic volume. The script collects sessions, the AI scores them, and you receive a report with session recordings and signal breakdowns.

What if my CRM doesn't capture click IDs?

You'll need to modify your form handler or tag manager to persist GCLID/FBCLID into a hidden field. Without that join key, you can't map BotRefund verdicts to individual leads.

Does BotRefund work on Meta lead forms (instant forms)?

The platform audits traffic that reaches your landing page. Instant forms that never leave Meta's ecosystem aren't visible to client-side scripts. You'd need to drive that traffic to your own page first.

How does BotRefund differ from Google's automatic invalid-activity credits?

Google's automated systems catch server-level patterns (rapid clicking, known bad IPs). BotRefund adds client-side behavioral evidence — mouse tremor, scroll depth, rendering quirks — that server logs cannot see. This catches advanced bots that evade Google's filters.

What's the typical bot click rate advertisers see?

BotRefund's homepage states "Bot clicks steal up to 20% of your Google and Meta ad budget." The FinTrust case study measured a 14% average bot click rate.

Direct answer: what opportunity rate means in BotRefund

Opportunity rate is the share of paid clicks that turn into qualified sales conversations — connected calls, booked demos, or pipeline-ready leads. BotRefund calculates it by first removing automated and invalid traffic from your Meta and Google campaigns, then matching the remaining human sessions to your CRM results. The difference between platform-reported leads and CRM-qualified opportunities reveals how much budget was wasted on bots, scrapers, and low-intent clicks.

Why measuring opportunity rate changes budget decisions

Meta and Google report leads or conversions, but they cannot tell you which of those contacts your sales team can actually reach. When a campaign shows a steady cost per lead while the sales team sees disconnected numbers, copied messages, or enquiries that never progress, the gap is often invalid traffic. BotRefund's audit compares ad-platform data, website sessions, and CRM outcomes before you change targeting or request a refund. That comparison is the foundation of a reliable opportunity rate.

Prerequisites before you start

• Active Meta or Google Ads campaigns sending traffic to a landing page you control
• Access to the website's <head> to install the BotRefund script (or tag-manager permission)
• CRM or lead-tracking system that records call outcomes, demo bookings, or qualification stages
• Click IDs (GCLID, FBCLID) passed through your forms so sessions can be linked to pipeline data

Step-by-step process to measure opportunity rate with BotRefund

1. Install the detection script. Add BotRefund's client-side snippet to your landing pages. It captures 110+ behavioral, browser, hardware, network, and attribution signals per session — including mouse tremor, scroll behavior, input speed, and iframe context checks.
2. Run a baseline audit. Let traffic accumulate for 7–14 days without changing campaigns. BotRefund flags each session as human or automated with 99% confidence, preserving click IDs, timestamps, and session recordings.
3. Export the refund-ready report. The report includes campaign, ad set, creative, placement, click identifier, and signal-by-signal reasoning in the format Google and Meta reviewers expect.
4. Match verified human sessions to CRM outcomes. Join the report's click IDs to your CRM records. Count qualified opportunities (connected calls, booked demos, SQLs) divided by verified human clicks. That quotient is your opportunity rate.
5. Compare against platform-reported metrics. Contrast the opportunity rate with Meta's or Google's reported lead count and cost per lead. The delta quantifies budget lost to invalid traffic.
6. File refund claims where warranted. BotRefund's team formats the evidence, writes the claim, and supports negotiation with Google and Meta. Across 2,500+ audits, 83% of clients recover funds.

Key signals BotRefund uses to separate humans from bots

No single signal proves fraud. BotRefund cross-checks independent browser, network, device, and behavior evidence, then weighs the complete pattern with an AI prediction model. The table below summarizes the signal categories drawn from the source pack.

How to verify the measurement is working

After the first audit cycle, check three things: (1) the bot-flag rate aligns with known problem placements (e.g., Audience Network, Messenger inbox), (2) CRM-qualified opportunity count rises as a percentage of verified human clicks, and (3) the refund-ready report passes platform review without requests for additional data. If any check fails, review the signal breakdown for that placement and adjust suppression rules before the next claim cycle.

Limitations and when this approach does not apply

• Requires client-side script installation; cannot audit traffic on pages you do not control (e.g., instant forms hosted entirely on Meta).
• Measures opportunity rate only for click-based campaigns where a landing page visit occurs. View-through or impression-only conversions are outside scope.
• CRM matching depends on consistent click-ID pass-through. Broken UTM or parameter stripping breaks the link.
• Refund success depends on platform policy; BotRefund's 83% recovery rate is historical, not a guarantee.

Terminology quick reference

• Opportunity rate: Qualified sales opportunities ÷ verified human clicks from paid campaigns.
• Invalid traffic: Automated interactions (bots, scrapers, click farms, publisher scripts) that generate clicks but cannot convert.
• Pixel poisoning: Conversion pixels trained on bot events, causing the ad algorithm to optimize for more bot traffic.
• Refund-ready report: Evidence package formatted to Google and Meta's review specifications, including click IDs, timestamps, session recordings, and signal reasoning.
• Click ID (GCLID/FBCLID): Unique identifier appended to landing-page URLs that ties a session to a specific ad click.

FAQ

How long before I see a reliable opportunity rate?

Plan for 7–14 days of baseline traffic after script install. Shorter windows risk sampling noise; longer windows capture weekly placement cycles.

Does BotRefund block bots in real time or only report them?

It detects and reports with session-level evidence. Suppression of conversion events for flagged sessions is configured in your ad platform (e.g., Meta CAPI, Google Enhanced Conversions) using the exported click IDs.

Can I use this with server-side tracking only?

No. Server-side logs miss browser-level signals like mouse tremor, scroll behavior, and iframe context. BotRefund's 99% confidence comes from client-side corroboration across 110+ independent checks.

What if my CRM doesn't store click IDs?

Add a hidden field to your forms that captures the GCLID or FBCLID from the URL. Without it, you cannot join verified sessions to pipeline outcomes.

How does BotRefund differ from Cloudflare or WAF bot protection?

Edge providers protect infrastructure. BotRefund protects ad-spend measurement: it preserves attribution, observes the post-click journey, and produces marketing-ready evidence for refund claims. The two layers can coexist.

What does the free bot audit include?

A sample analysis of your traffic using the same 110+ signals, with a summary of bot percentage by campaign and placement. No contract required to start.

Can opportunity rate be measured for lead-gen forms hosted on Meta (Instant Forms)?

Not directly, because the form loads inside Meta's iframe where client-side scripts cannot run. Measure opportunity rate on your own landing pages; use the audit to inform targeting exclusions for Instant Form campaigns.

Key facts from BotRefund source pack

What BotRefund actually measures

BotRefund is a bot-detection and ad-refund platform. It analyzes 110+ behavioral, browser, hardware, network, and attribution signals to flag automated visits with 99% confidence. Each flagged session comes with a session-by-session explanation, click IDs, timestamps, and signal-level reasoning formatted for Google and Meta refund reviews.

Qualification rate — the percentage of leads that meet your sales-ready criteria — is a downstream metric you calculate in your CRM or marketing automation. BotRefund improves the input to that calculation by stripping out non-human leads before they reach your pipeline.

Why invalid traffic distorts qualification rate

When bots fill forms or click ads, they inflate lead counts without any chance of becoming qualified opportunities. The source pack notes that a campaign can show a steady cost per lead while the sales team receives unreachable contacts, copied messages, or enquiries that never progress. Common signals of invalid traffic include:

• Contactability issues: disconnected numbers, invalid email domains, repeated addresses, unusual country-code concentrations
• Timing anomalies: bursts of leads, immediate form submissions after landing, conversions at odd hours
• Session behavior: no scrolling, no field corrections, uniform click paths, no meaningful time on page
• Campaign patterns: sharp lead-quality differences by placement, creative, audience expansion, device, or landing page
• CRM outcomes: high reported lead count paired with no calls connected, demos booked, qualified opportunities, or repeat engagement

If you measure qualification rate on raw lead volume, bot traffic makes the denominator artificially large and the rate artificially low.

Step-by-step: using BotRefund data to clean your qualification metric

1. Install the BotRefund script on your landing pages and thank-you pages. The script captures client-side behavioral signals that server-side logs miss.
2. Run a free bot audit to establish a baseline. The audit reports the percentage of bot clicks (the FinTrust case study saw a 14% average bot click rate) and identifies which campaigns, placements, and creatives are most affected.
3. Enable conversion-signal suppression for sessions flagged as automated. BotRefund can suppress conversion events sent to Meta and Google so the platforms' optimization algorithms train only on verified human conversions.
4. Export refund-ready reports that include click IDs (GCLID, FBCLID), campaign details, timestamps, session recordings, and signal-by-signal reasoning. Use these reports to:
   • Request invalid-activity credits from Google and Meta (83% of BotRefund clients recover funds)
   • Build a suppression list of click IDs to exclude from your CRM import or to tag as "invalid" in your marketing automation
5. Recalculate qualification rate using only leads that passed the BotRefund filter. Compare the cleaned rate to the raw rate to quantify the distortion.
6. Monitor ongoing. BotRefund continues to flag new invalid sessions in real time. Keep the suppression active and refresh your qualification-rate dashboard weekly.

Verification step

After the first full week of suppression, pull two numbers from your CRM: (a) total leads imported, and (b) leads that reached your qualified stage (e.g., SQL, demo booked). Divide (b) by (a). Then pull the same numbers from the week before BotRefund suppression. The cleaned rate should be higher, and the gap between the two rates approximates the bot-driven inflation you removed.

Key facts

How the detection works

BotRefund runs 106 independent checks (the source pack describes two examples: Scrollbar Width Leak and Clean Context Iframe). Each check produces one piece of objective evidence — not a verdict. The system cross-checks every signal against browser, network, device, and behavior data, then feeds the complete pattern into an AI prediction model that outputs a bot/human classification with 99% accuracy when the evidence supports it.

Because a single anomaly can come from privacy tools, corporate networks, or unusual devices, BotRefund never relies on one signal. It requires corroboration across multiple independent vectors before flagging a session.

What you need before you start

• Access to edit the website's <head> or tag manager to install the BotRefund script
• Admin access to Google Ads and/or Meta Ads Manager to connect click IDs (GCLID, FBCLID) and submit refund claims
• CRM or marketing-automation admin rights to import suppression lists or tag invalid leads
• A defined qualification stage (SQL, MQL, demo booked, etc.) so you can measure the before/after rate

Limitations

• BotRefund does not define your qualification criteria — that remains your sales/marketing decision.
• It only covers paid traffic from Google and Meta. Organic, direct, referral, and other paid channels are outside its scope.
• Refund approvals depend on Google and Meta reviewers; BotRefund provides evidence and negotiation support but cannot guarantee every claim succeeds.
• The 99% confidence figure applies when the session evidence supports it; low-signal sessions may remain unclassified.
• Installation requires client-side JavaScript execution. Visitors with aggressive script blockers may not be analyzed.

Common mistakes to avoid

Practical scenarios

Scenario A: Lead-gen campaign with high form volume, low sales contact rate

Install BotRefund, run the audit, and suppress bot conversions. The CRM receives fewer but cleaner leads. Qualification rate rises because the denominator no longer includes automated submissions. Use the refund report to recover wasted spend.

Scenario B: E-commerce site optimizing for purchase conversions

BotRefund flags bot clicks that never add to cart. Suppress those conversion signals so Google/Meta bidding algorithms optimize for real buyers. Track return-on-ad-spend (ROAS) improvement alongside qualification rate.

Scenario C: Agency managing multiple client accounts

Run audits across all accounts. Prioritize clients with the highest bot click rates for immediate suppression and refund claims. Report cleaned qualification rates to clients as a quality metric.

FAQ

Does BotRefund calculate qualification rate for me?

No. It provides the cleaned lead data (by flagging and suppressing bot sessions) so your CRM or analytics tool can calculate an accurate rate.

How long until I see a change in qualification rate?

Typically one full traffic cycle (7–14 days) after enabling suppression, assuming stable ad spend and targeting.

Can I use BotRefund without requesting refunds?

Yes. The detection and suppression features work independently of the refund workflow.

What if a real user gets flagged as a bot?

BotRefund's 99% confidence threshold and multi-signal corroboration minimize false positives. Each flagged session includes a full evidence trail you can review before suppressing.

Does it work for organic or email traffic?

No. BotRefund only analyzes sessions that arrive via paid Google or Meta clicks with click IDs attached.

How much does it cost?

Pricing is not published in the source pack. The homepage mentions an "Under $10,000/mo" enterprise tier and a free bot audit to start.

Can I export the flagged click IDs to my own suppression list?

Yes. Refund-ready reports include click IDs (GCLID, FBCLID), campaign details, and timestamps that you can import into your CRM or tag manager.

Next steps

Start with the free bot audit to see your baseline bot click rate. If the audit shows a meaningful percentage of invalid traffic, enable suppression, connect your ad accounts for refund claims, and rebuild your qualification-rate dashboard on the cleaned lead stream.

BotRefund monitors suspicious patterns by collecting 110+ independent behavioral, browser, hardware, network, and attribution signals from every visitor to your site, then cross-referencing those signals to flag automated traffic with 99% confidence. To use it for pattern monitoring, first install its lightweight tracking script on your site, then review the flagged session data to identify repeatable bot behaviors like superhuman form completion speed, uniform linear mouse movements, or sessions with no scrolling or page engagement. You can then export these findings as refund-ready reports to claim invalid ad spend from Google and Meta, with BotRefund’s team supporting 83% of client claims successfully.

What Suspicious Patterns BotRefund Is Designed to Catch

BotRefund does not flag one-off odd behavior as bot traffic. It looks for repeatable, non-human patterns that consistently correlate with invalid ad clicks and fake form submissions. Common suspicious patterns it monitors include:

• Contactability red flags: Disconnected phone numbers, invalid email domains, repeated addresses, or an unusual concentration of leads from a single country code.
• Timing spikes: Several leads arriving in short bursts, forms submitted immediately after landing page load, or conversions concentrated at unusual hours.
• Session behavior anomalies: No scrolling, no field corrections, uniform click paths, input speed faster than 1 millisecond (faster than a human can type or click), or unnaturally uniform session durations.
• Campaign-level pattern shifts: A sharp drop in lead quality tied to a specific ad placement, creative, audience segment, or landing page.
• CRM outcome mismatches: A high reported lead count paired with no connected calls, booked demos, qualified opportunities, or repeat engagement.

As BotRefund notes, a single anomaly is not a bot verdict. Privacy tools, corporate networks, or unusual devices can create odd behavior for real users, so all signals are cross-checked against 105 other independent data points before a session is flagged.

Prerequisites Before You Start Monitoring Suspicious Patterns

You only need three things to use BotRefund for pattern monitoring, no infrastructure overhauls required:

1. Access to your website’s codebase or tag management system to install the BotRefund tracking script.
2. Access to your Google Ads and Meta Ads Manager accounts to link click IDs and campaign attribution data.
3. Access to your CRM to sync lead outcomes and cross-reference suspicious sessions with real conversion results.

You do not need to replace your existing edge protection tools (like Cloudflare) if you already use them. BotRefund works as a marketing-layer evidence tool that sits on top of your existing stack to monitor ad traffic patterns specifically.

Step-by-Step Process to Monitor Suspicious Patterns with BotRefund

Follow these ordered steps to set up pattern monitoring and start identifying invalid traffic:

1. Create a BotRefund account and generate your unique, lightweight tracking script. The script is optimized to not slow down your site’s load speed.
2. Install the script on your site, prioritizing ad landing pages and lead capture forms. You can add it via Google Tag Manager, a CMS plugin (like WordPress), or direct code injection. BotRefund’s support team can assist with setup if needed.
3. Link your ad accounts to BotRefund to automatically capture click IDs, campaign details, placement data, and timestamps for every paid visit. This ties suspicious sessions directly to the ad spend that drove them.
4. Connect your CRM to sync lead outcomes (call connects, demo bookings, qualification status) so you can match flagged sessions to real business results.
5. Run the script for 7–14 days to build a baseline of normal visitor behavior for your site. This helps you spot repeatable patterns instead of one-off anomalies.
6. Review flagged sessions in the BotRefund dashboard. Filter by campaign, placement, or date to identify clusters of suspicious activity. You can view full session replays for any flagged visit to confirm non-human behavior.
7. Export evidence for claims or suppression. Download session recordings, signal-by-signal reasoning, and click ID data for any suspicious traffic cluster to use for refund claims or to suppress invalid traffic from your ad targeting.

How to Verify Flagged Patterns Are Legitimate Bot Traffic

BotRefund’s 99% confidence rating comes from cross-referencing every signal against 105 other independent checks, not just single red flags. To verify a pattern is real:

• Confirm the flagged sessions have multiple supporting signals (e.g., superhuman input speed + no scrolling + uniform click path, not just one odd behavior).
• Cross-reference with your CRM: do the leads from these sessions have disconnected numbers, no follow-up engagement, or other red flags?
• Check if the suspicious sessions are concentrated on a specific ad placement, creative, or audience segment, which is a common sign of invalid traffic from a bad publisher or click farm.
• Review full session replays to rule out legitimate reasons for odd behavior, like a user on a corporate network with strict privacy tools.

Using Monitored Patterns to Recover Wasted Ad Spend

Once you have a verified cluster of suspicious sessions, you can use BotRefund’s refund-ready reports to claim invalid ad spend from Google and Meta. These reports are structured exactly to the format platform review teams require, and include click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning for every flagged visit. BotRefund’s team has experience with 2,500+ audits and can help you file the claim and negotiate with platform reviewers, with an 83% success rate for clients. You do not need to pause your campaigns to collect evidence, as BotRefund preserves session data even after a campaign ends.

Key Facts About BotRefund Pattern Monitoring

Key Limitations of BotRefund Pattern Monitoring

BotRefund’s pattern monitoring is designed for ad traffic investigation, not generic site security. Keep these limitations in mind:

• It monitors visitor behavior after a user lands on your site, so it will not catch bot traffic that never reaches your landing pages (e.g., server-level click fraud that is filtered before page load).
• It does not guarantee a refund from Google or Meta, as final claim decisions are made by platform review teams. It only provides the evidence and support to improve your odds of a successful claim.
• The free bot audit only samples a portion of your traffic, so full pattern monitoring requires a paid plan. Enterprise plans start at under $10,000 per month.
• It is optimized for paid ad traffic monitoring, so it may not catch all types of non-ad related bot traffic (like content scrapers) unless they interact with your lead capture forms.

Frequently Asked Questions

1. How long does it take to start seeing suspicious pattern data after installing BotRefund?
   You will start seeing flagged sessions within 24 hours of installation. We recommend letting the tool run for 7–14 days to build a baseline of normal behavior for your site and spot repeatable patterns instead of one-off anomalies.
2. Will BotRefund slow down my website?
   No, the tracking script is lightweight and optimized for performance, so it does not impact page load speed or user experience for real visitors.
3. Can I use BotRefund to monitor suspicious patterns on non-ad landing pages?
   Yes, you can install the script on any page of your site. It is most valuable on ad landing pages and lead capture forms, where invalid traffic directly wastes ad spend and poisons conversion data.
4. Do I need technical skills to set up BotRefund for pattern monitoring?
   No, you can install the script via Google Tag Manager, a CMS plugin, or direct code injection. BotRefund’s support team is available to help with setup if needed.
5. What’s the difference between BotRefund’s pattern monitoring and server-side bot detection?
   Server-side tools only check IP addresses and user-agent data, which misses advanced bots that use real IPs and spoofed user agents. BotRefund uses client-side behavioral signals (like mouse movement, input speed, and scroll behavior) that are almost impossible for bots to fake, so it catches far more sophisticated invalid traffic.
6. How much does BotRefund’s pattern monitoring cost?
   BotRefund offers a free bot audit to sample your current traffic. Paid enterprise plans start at under $10,000 per month, and you can request full pricing via the “Click here for pricing” link on the BotRefund homepage.

To optimize for verified leads with BotRefund, start by installing the client-side tracking script on your landing pages. The script captures browser, device, network, and behavioral signals for every session that follows a paid click. BotRefund's AI evaluates the complete pattern across 110+ independent checks — such as scrollbar width leaks, clean-context iframe mismatches, robotic mouse movements, and superhuman input speed — and flags sessions with 99% confidence when the evidence supports it. Each flagged session comes with a session-by-session explanation, click IDs, timestamps, and campaign details formatted for Google and Meta review teams.

Next, connect the flagged sessions to your conversion pixels and CRM. BotRefund can suppress conversion events for automated traffic in real time, preventing pixel poisoning that would otherwise train Meta and Google bidding algorithms on fake leads. Export the refund-ready reports and submit them through the platforms' invalid-activity claim processes; BotRefund's team has negotiated successful refunds for 83% of clients across 2,500+ audits. Finally, feed the cleaned lead data back into your audience targeting and lookalike models so future spend reaches genuine prospects.

Prerequisites Before You Start

• Active Meta or Google Ads campaigns driving traffic to pages you control
• Access to add a JavaScript snippet to your landing page or tag manager
• Conversion pixels (Meta Pixel, Google Ads conversion tag) firing on lead events
• CRM or lead-management system where you can review contact outcomes
• Admin access to Google Ads and Meta Ads Manager for refund submissions

Step-by-Step Implementation

1. Create a BotRefund account and get the tracking script. The script loads asynchronously and begins collecting behavioral, browser, hardware, network, and attribution signals immediately.
2. Deploy the script on every landing page that receives paid traffic. Use Google Tag Manager, a header/footer injection, or direct template placement. Verify the script fires by checking the BotRefund dashboard for live sessions.
3. Map click identifiers (GCLID, FBCLID) to sessions. BotRefund automatically captures these parameters so each flagged session ties back to a specific campaign, ad set, creative, and placement.
4. Enable conversion-signal protection. In the BotRefund dashboard, select which conversion events to suppress when a session is classified as automated. This stops bot conversions from poisoning your pixel data.
5. Run a baseline audit (7–14 days). Let traffic accumulate. The dashboard will show bot-rate by campaign, placement, device, and audience. Look for sharp quality differences — e.g., a placement with 30% bot clicks while others sit under 2%.
6. Review flagged sessions manually. Each finding includes a session recording, signal-by-signal reasoning, and a plain-language explanation. Confirm the classifications match your CRM outcomes (disconnected numbers, copied messages, no engagement).
7. Generate refund-ready reports. BotRefund packages click IDs, campaign metadata, timestamps, session recordings, and signal evidence in the format Google and Meta reviewers expect.
8. Submit invalid-activity claims. File through Google Ads' invalid activity credit process and Meta's refund request flow. BotRefund's team can assist with documentation and negotiation.
9. Feed cleaned data back into targeting. Exclude high-bot placements, adjust audience expansions, and rebuild lookalike audiences using only verified converters.

How BotRefund Detects Automated Traffic

BotRefund does not rely on a single heuristic. It runs 110+ independent checks across five categories and feeds every signal into an AI model that weighs the complete pattern. The result is a 99% confidence classification when the evidence supports it, not a raw rule trigger.

Behavioral & Biometric Signals

• Pointer behavior: Robotic linear mouse movements and absence of humanlike micro-tremor.
• Speed behavior: Superhuman input speed (under 1 ms) between interactions.
• Path behavior: Grid-aligned movement that snaps to precise lines instead of natural curves.
• Engagement behavior: Absence of clicks, scrolling, or field corrections.
• Session behavior: Unnatural durations — too short, too long, or too uniform.

Browser & Environment Signals

• Scrollbar Width Leak: Detects mismatches between reported and actual scrollbar dimensions that automation tools struggle to replicate.
• Clean Context Iframe: Checks whether standard browser APIs behave consistently when probed from an isolated iframe context; automation patches often break here.
• Ghost Click Detection: Catches click activity that occurs without the natural sequence of human intent.
• Honeypot Trap Interactions: Watches for bots that respond to hidden or deceptive page elements.

Network & Attribution Signals

• Data-center IP ranges, VPN exit nodes, and known proxy signatures
• Click ID (GCLID/FBCLID) presence and consistency
• Campaign, ad set, creative, placement, and device attribution preserved per session

Each signal is kept as evidence, not a verdict. Privacy tools, corporate networks, and unusual devices can produce anomalies for real people. BotRefund cross-checks every signal against independent browser, network, device, and behavior data before the AI assigns a classification.

Using Refund-Ready Reports to Recover Spend

Google and Meta both offer credits for invalid activity, but their automated systems catch only a fraction. BotRefund's reports are structured in the format platform review teams use: click IDs, campaign hierarchy, timestamps, session recordings, and signal-by-signal reasoning. Across 2,500+ audits, 83% of clients recovered funds from Google and Meta. The high approval rate comes from three factors: 99% detection confidence, reports built for reviewer workflows, and experience negotiating claims with both platforms.

For Google Ads, file through the Invalid Activity Credit process in the billing section. For Meta, use the Ads Manager refund request form. Attach the BotRefund report and reference the specific click IDs. BotRefund's team can review your draft claim and suggest adjustments before submission.

Protecting Conversion Pixels from Poisoning

Pixel poisoning happens when bot conversions train bidding algorithms to optimize for automated traffic. BotRefund prevents this by suppressing conversion events in real time for sessions classified as automated. The suppression works at the pixel level: when a flagged session reaches a conversion event, BotRefund blocks the pixel fire before it reaches Meta or Google. Your CRM still receives the lead record (so sales can review), but the ad platforms never see the conversion.

This keeps your cost-per-lead and ROAS metrics honest. It also improves lookalike audience quality because the seed audience contains only verified human converters. In the FinTrust case study, suppressing bot registrations on search landing pages led to a 14% average bot click rate detection, $140,000 in refunded ad spend, and an 18% conversion rate increase after the bidding algorithms retrained on clean data.

Integrating Verified Leads Into Your Sales Workflow

• Tag leads in your CRM: Add a "BotRefund verified" flag to contacts that passed the behavioral audit. Sales can prioritize these.
• Build exclusion audiences: Export high-bot placement IDs and audience segments to Meta and Google as exclusions.
• Retrain lookalikes: Create new lookalike/seed audiences from verified converters only. Refresh monthly.
• Monitor contactability metrics: Track connected-call rate, demo-booked rate, and opportunity-created rate by traffic source. A divergence between platform-reported leads and CRM outcomes signals residual bot traffic.
• Set up recurring audits: Bot traffic patterns shift. Schedule quarterly full audits and weekly dashboard reviews.

Key Facts

Limitations and When This Advice Does Not Apply

• Requires client-side script execution. If your landing pages block third-party JavaScript or visitors use aggressive script blockers, detection coverage drops.
• Not a WAF or DDoS layer. BotRefund operates at the marketing layer after the click reaches the page. It does not replace Cloudflare, Akamai, or edge infrastructure for infrastructure protection.
• Refunds are not guaranteed. Google and Meta make final credit decisions. BotRefund's 83% success rate reflects historical outcomes, not a promise.
• Lead-quality issues beyond bots. Low-intent human traffic, mismatched offers, and poor landing pages also produce bad leads. BotRefund only addresses automated and invalid traffic.
• Enterprise pricing above $10,000/month spend. The source pack indicates tiered plans; verify current pricing for your volume.

FAQ

How long before I see results?

Baseline audit takes 7–14 days for meaningful placement-level data. Refund claims typically process in 2–6 weeks depending on platform review queues.

Does BotRefund work on TikTok, LinkedIn, or other platforms?

The source pack documents Google and Meta support. Check with the vendor for other platforms.

Can I use BotRefund without submitting refund claims?

Yes. The conversion-signal protection and audience-exclusion features work independently of refund workflows.

What happens to leads flagged as bots in my CRM?

They remain in your CRM with a flag. Sales can still review them, but they are excluded from pixel fires and lookalike seeds.

How does BotRefund differ from server-side log analysis?

Server-side logs see IP, headers, and user-agent only. BotRefund adds client-side behavioral, browser, and device signals that catch advanced botnets that mimic legitimate headers.

Is there a free trial or audit?

The homepage and blog pages reference a "free bot audit" option. Visit the site for current terms.

What if my team lacks bandwidth to manage claims?

BotRefund's team formats reports, writes claims, and supports negotiations with Google and Meta reviewers as part of the service.

BotRefund organizes evidence by automatically collecting 110+ independent signals per visit — including click behavior, pointer movement, scroll patterns, browser consistency, and network context — then cross-checking them through an AI model that reaches 99% confidence before packaging everything into a report format that Google and Meta review teams use to evaluate invalid-traffic claims.

To use it, you add the BotRefund script to your landing pages, let it run during your ad campaigns, then download the audit-ready report that ties each flagged session to its click ID (GCLID or fbclid), campaign, placement, timestamp, and the specific behavioral anomalies detected. The report is structured so platform reviewers can verify the evidence without translating raw logs.

What BotRefund evidence organization actually does

BotRefund sits on your website and observes every visitor session that arrives from paid clicks. It does not rely on IP lists or server logs alone. Instead, it runs 106+ client-side checks — such as scrollbar width consistency, clean context iframe behavior, ghost click detection, honeypot trap interactions, robotic mouse movements, superhuman input speed, grid-aligned paths, and absence of humanlike tremor — to build a per-session evidence record.

Each signal is kept as independent evidence, not a verdict. The system cross-checks signals across browser, network, device, and behavior layers, then feeds the complete pattern into a prediction model that classifies the visit as bot or human with 99% accuracy. The output is a session-by-session explanation that includes the click ID, campaign metadata, timestamps, and a signal-by-signal breakdown.

Prerequisites before you start

• Active Google Ads or Meta Ads campaigns sending traffic to pages you control.
• Ability to add a JavaScript snippet to your landing pages or tag manager.
• Access to your ad account click IDs (GCLID for Google, fbclid for Meta) for the periods you want audited.
• A clear goal: either a refund claim, a suppression list for conversion signals, or both.

Step-by-step process to organize evidence with BotRefund

1. Install the tracking script. Add the BotRefund snippet to every landing page that receives paid traffic. The script loads asynchronously and begins capturing behavioral, browser, hardware, network, and attribution signals immediately.
2. Run campaigns normally. Let the script collect data across your active campaigns. It preserves attribution data (campaign, ad set, creative, placement, click identifier) before any changes are made, which is critical for refund claims.
3. Review the audit dashboard. After sufficient traffic volume, open the BotRefund dashboard. You will see flagged sessions grouped by campaign, placement, device, and signal clusters. Each session shows the click ID, timestamp, and the specific anomalies detected (e.g., ghost clicks, honeypot triggers, superhuman speed).
4. Export the refund-ready report. Select the date range and campaigns you want to claim. The export produces a structured document containing: click IDs, campaign details, timestamps, session recordings or replays, and signal-by-signal reasoning for each flagged visit. This format matches what Google and Meta reviewers expect.
5. File the claim with the platform. Submit the report through Google Ads invalid activity credit request or Meta's invalid traffic appeal process. BotRefund's team can assist with claim formatting and negotiation based on experience from 2,500+ audits.
6. Suppress conversion signals (optional). While the claim is pending, you can use BotRefund's conversion protection to stop flagged bot events from feeding back into Google or Meta bidding algorithms, preventing pixel poisoning.

Key evidence types BotRefund captures and organizes

The platform groups evidence into categories that platform reviewers recognize:

• Click behavior: Ghost clicks (activity without human intent sequence), honeypot trap interactions (bots hitting hidden elements), and duplicate click signatures.
• Pointer behavior: Robotic linear movements, absence of humanlike tremor, grid-aligned snapping, and superhuman input speed (<1ms).
• Engagement behavior: Absence of scrolling, no field corrections, uniform click paths, and no meaningful time on offer pages.
• Session behavior: Unnatural durations (too short, too long, or too uniform), missing navigation flow, and rendering anomalies like scrollbar width leaks or clean context iframe mismatches.
• Network and device context: Data center IP ranges, VPN signatures, browser automation framework fingerprints, and hardware consistency checks.
• Attribution linkage: Every session is tied to its GCLID or fbclid, campaign, ad set, creative, placement, and timestamp so the evidence maps directly to billed clicks.

How to verify your evidence package is refund-ready

Before submitting, confirm three things:

1. Click ID coverage: Every flagged session in the report includes a valid GCLID or fbclid that matches your ad account billing data for the claim period.
2. Signal corroboration: No session is flagged on a single anomaly. The report should show multiple independent signals converging (e.g., ghost click + honeypot + superhuman speed + grid-aligned movement).
3. Format compliance: The export uses the structure Google and Meta reviewers use — click ID tables, campaign metadata, session timelines, and signal explanations — not raw JSON or security logs.

If any flagged session lacks a click ID or relies on only one signal, remove it from the claim package. Platform reviewers reject claims built on incomplete attribution or single-rule triggers.

Common mistakes that weaken evidence

Limitations and when this approach does not apply

• Organic or direct traffic: BotRefund only organizes evidence for sessions that carry a paid click ID. It cannot build refund cases for non-paid channels.
• Platforms without invalid-traffic credit programs: The report format is tailored to Google Ads and Meta Ads. Other ad platforms may not accept the same evidence structure.
• Historical claims beyond platform lookback windows: Google and Meta limit how far back you can claim credits. Evidence older than their window (typically 60-90 days) will not be accepted regardless of quality.
• Sites that cannot run client-side scripts: If your landing pages block third-party JavaScript or use strict CSP policies that prevent behavioral data collection, the evidence layer cannot be built.

Key facts

FAQ

How long does it take to collect enough evidence for a claim?

Depends on traffic volume. Most advertisers see actionable clusters within 7-14 days of installation. High-spend campaigns may produce a claim-ready report in 3-5 days.

Can I use BotRefund evidence for a claim I already filed and lost?

Only if the platform allows re-opening with new evidence. BotRefund's report format is designed for first-time submissions; retrospective claims depend on each platform's appeal policy.

Does BotRefund automatically file the refund request?

No. It prepares the evidence package and can guide the submission. You or your agency files the claim through Google Ads or Meta's support channels.

What if my site uses a strict Content Security Policy?

You must allow the BotRefund script domain in your CSP directives. Without client-side execution, behavioral signals cannot be captured and evidence cannot be organized.

How does this differ from Google's automatic invalid activity credits?

Google's automatic system catches server-level patterns (rapid clicking, known bad IPs). BotRefund adds client-side behavioral proof — mouse movement, scroll behavior, browser consistency — that server logs miss, enabling claims for activity Google's automation did not flag.

Can I use the evidence to build exclusion audiences?

Yes. The placement, audience, and device breakdowns in the report let you create suppression lists in Google Ads and Meta to stop bidding on traffic sources with high bot concentrations.

What happens to the evidence after the claim is resolved?

You retain the full report. It can be reused for future claims, shared with auditors, or referenced when adjusting targeting. BotRefund does not delete your session data unless you request it.

Preserving identifiers with BotRefund means capturing and retaining all critical ad attribution data—including click IDs, GCLIDs, campaign IDs, placement details, and timestamps—before you make any changes to your ad campaigns or pause active ads. This retained data is required to prove that invalid bot traffic originated from a specific paid click, which is a mandatory condition for Google and Meta to approve invalid traffic refund claims. The setup takes 5–10 minutes, and once installed, BotRefund automatically preserves this data for every visitor session without manual work from your team.

If you pause a campaign or adjust targeting before capturing this attribution data, you will lose the link between suspicious bot sessions and the paid clicks that drove them, making refund claims impossible to file. BotRefund’s system ties every behavioral bot signal to the exact ad identifier that brought the visitor to your page, so you never have to manually match session data to campaign records.

What Preserving Identifiers Means for Ad Refund Claims

Ad identifiers are unique strings assigned to every paid click on Google and Meta platforms. For Google Ads, this is typically the GCLID (Google Click Identifier); for Meta, it is the click ID or fbclid parameter. These identifiers let you tie a specific website visit back to the exact ad, ad set, and campaign that generated the click.

When you file an invalid traffic refund claim, both platforms require proof that the suspicious traffic came from a paid click you were charged for. Without preserved identifiers, you cannot draw that line, and reviewers will reject your claim automatically. Preserving these identifiers is not optional for refund eligibility—it is a core requirement of both platforms’ dispute processes.

Why Identifier Preservation Matters for Invalid Traffic Disputes

Bot traffic often looks identical to low-quality human traffic in ad platform reports. You may see a steady cost per lead, but your sales team receives unreachable contacts, copied form submissions, or enquiries that never convert. Without preserved identifiers, you cannot prove these bad leads came from paid clicks you were billed for.

Common scenarios where missing identifiers ruin refund claims include:

• You pause an underperforming campaign before investigating lead quality, losing the link between bot sessions and the clicks that drove them
• Your CRM does not automatically capture click IDs from landing page URLs, so you have no record of which campaign generated a suspicious lead
• You adjust ad targeting or creative before filing a claim, making it impossible to prove the bot traffic occurred while the original ad was active

BotRefund eliminates these gaps by automatically capturing and storing identifiers the moment a visitor lands on your page, even if you later change or pause the campaign.

How BotRefund Captures and Retains Ad Identifiers

BotRefund’s script runs client-side on your landing pages the moment a visitor loads the page. It first extracts all available ad identifiers from the URL parameters, cookies, and referrer data, then ties those identifiers to a unique session ID for the visit.

As the visitor interacts with the page, BotRefund collects 110+ behavioral, browser, hardware, and network signals to determine if the session is automated. If the session is flagged as a bot, the full set of identifiers and behavioral evidence is stored in a refund-ready report that matches the format Google and Meta reviewers require.

This process does not interfere with your existing ad tracking, CRM, or edge protection tools. BotRefund runs alongside tools like Cloudflare, Google Analytics, and Meta Pixel without conflicting with their data collection.

Step-by-Step Setup to Preserve Identifiers with BotRefund

Follow these steps to start preserving ad identifiers for refund claims in 10 minutes or less:

1. Create a BotRefund account: Sign up for a free trial or paid plan on the BotRefund website. No credit card is required for the initial audit.
2. Install the BotRefund script on your landing pages: Copy the unique script snippet from your BotRefund dashboard and add it to the header of every landing page linked to your Google and Meta ad campaigns. The script works with all major website builders, including WordPress, Shopify, Webflow, and custom-coded sites.
3. Verify identifier capture: After installing the script, visit one of your ad landing pages via a test ad click. Check your BotRefund dashboard to confirm the click ID, GCLID, campaign name, and placement data are recorded for the test session.
4. Let the system run automatically: BotRefund will now capture and retain identifiers for every visitor session, flag bot traffic, and generate refund-ready reports when invalid traffic is detected. No further manual action is required unless you want to adjust detection sensitivity or export reports.

The most common mistake here is installing the script only on your homepage instead of all ad-linked landing pages. If a visitor lands on a page without the BotRefund script, no identifiers or session data will be captured for that visit.

Key Facts About BotRefund Identifier Preservation

Common Limitations and Exceptions

Identifier preservation with BotRefund only works for traffic that lands on pages with the installed script. If a bot clicks your ad but bounces before your landing page loads, or if the landing page is on a subdomain without the script, no identifiers will be captured for that visit.

BotRefund also cannot preserve identifiers for traffic that arrives via organic search, email, or direct visits, as these sources do not have paid ad click identifiers tied to them. The tool is designed exclusively for paid ad traffic on Google and Meta platforms.

Finally, while BotRefund’s reports are formatted to meet platform requirements, final refund approval is always at the discretion of Google and Meta review teams. BotRefund supports the claim process with evidence, but cannot guarantee a refund outcome.

Frequently Asked Questions

Do I need to preserve identifiers for every ad campaign?

Yes, if you want to be eligible for invalid traffic refunds. Both Google and Meta require proof that suspicious traffic came from a specific paid click, which is only possible if you have preserved the associated ad identifier.

What happens if I lose ad identifiers before filing a claim?

If you pause a campaign, change targeting, or delete landing page data before capturing identifiers, you will not be able to tie bot sessions to paid clicks, and your refund claim will be rejected. BotRefund’s automatic capture eliminates this risk by storing identifiers as soon as a visitor lands on your page.

Does preserving identifiers affect my ad campaign performance?

No. The BotRefund script is lightweight (less than 10KB) and does not slow page load times or interfere with Meta Pixel, Google Analytics, or other ad tracking tools. It runs silently in the background of your landing pages.

How long does BotRefund store preserved identifiers?

BotRefund stores all captured identifiers and session data for 12 months, which covers the maximum lookback window for Google and Meta invalid traffic refund claims.

Can I use BotRefund to preserve identifiers for non-Meta and non-Google ad platforms?

Currently, BotRefund’s refund reporting is optimized for Google and Meta’s review processes. While the tool can capture identifiers for other ad platforms, the refund-ready reports are only guaranteed to meet Google and Meta’s requirements.

To protect conversion measurement with BotRefund, install the BotRefund script on your landing pages, connect your Meta Pixel and Google Ads conversion IDs in the dashboard, and enable conversion-signal suppression so automated sessions never fire purchase, lead, or custom events. BotRefund then analyzes each visit using 110+ independent signals — including pointer behavior, scroll patterns, input timing, and browser consistency checks — and blocks conversion pixels from firing for sessions it classifies as automated with 99% confidence. The result is cleaner attribution data, unpoisoned bidding algorithms, and evidence packages formatted for Google and Meta refund claims.

Why conversion measurement breaks when bots slip through

Conversion pixels fire on every tracked event — form submit, button click, page view — regardless of whether the visitor is human. When automated traffic completes those actions, the platforms record conversions that never lead to revenue. That pollutes the optimization signals Meta and Google use to find similar users, so your campaigns start bidding more aggressively for traffic that looks like the bots. The cycle compounds: worse targeting brings more bots, which further skews the model.

BotRefund’s approach is to stop the pixel from firing in the first place. By evaluating the visitor’s behavior in the browser before the conversion event reaches the network, it can suppress the event for sessions that show robotic patterns — linear mouse paths, superhuman input speed (<1ms), absence of micro-tremor, grid-aligned movements, or missing scroll engagement — while letting genuine visitors pass through unchanged.

Prerequisites before you start

• Admin access to your website or tag manager to add the BotRefund JavaScript snippet.
• Active Meta Pixel and/or Google Ads conversion IDs you want to protect.
• Access to your Meta Ads Manager and Google Ads accounts to verify pixel/event configuration.
• A list of the conversion events you consider high-value (purchase, lead, add-to-cart, custom events) so you can map them in the BotRefund dashboard.

Step-by-step implementation

1. Create a BotRefund account and get your site key. After signup, the dashboard issues a unique script snippet tied to your domain.
2. Install the snippet on every landing page that receives paid traffic. Place it in the <head> or via Google Tag Manager so it loads before your conversion pixels. The script begins collecting 110+ signals immediately — browser fingerprint, pointer dynamics, scroll behavior, timing, and network context.
3. Connect your ad platforms in the BotRefund dashboard. Enter your Meta Pixel ID and Google Ads conversion IDs. BotRefund uses these to know which events to monitor and suppress.
4. Map your conversion events. For each event (e.g., Purchase, Lead, CompleteRegistration), tell BotRefund the exact event name and trigger conditions. This ensures suppression only hits the events you care about.
5. Enable conversion-signal suppression. Toggle the protection mode for each event. When active, BotRefund intercepts the pixel call in the browser, runs its 99%-confidence classification, and either allows the event through or blocks it and logs the session with full evidence.
6. Preserve attribution before making campaign changes. Keep campaign, ad set, creative, placement, and click identifiers intact while you review the first 7–14 days of data. Changing targeting or pausing ads before you have a clean baseline makes it harder to isolate the bot impact.
7. Review the audit dashboard daily for the first week. Look at the session-by-session breakdown: click IDs, timestamps, signal-by-signal reasoning, and session recordings. Confirm that suppressed events match the patterns described in the signals list (ghost clicks, honeypot interactions, robotic pointer paths, superhuman speed, grid-aligned movement, absent tremor, static sessions, unnatural durations).

Verification step: confirm clean data in your ad platforms

After 7–14 days, open Meta Ads Manager and Google Ads and compare conversion counts before and after suppression. You should see fewer reported conversions but higher downstream quality — more connected calls, booked demos, or qualified opportunities per reported lead. In the BotRefund dashboard, export a refund-ready report for any period where bot traffic was significant; the report includes click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning formatted for Google and Meta review teams.

Key facts

How the detection signals work together

No single signal proves a visit is automated. BotRefund treats each check as independent evidence — for example, the Scrollbar Width Leak detects a mismatch between reported and actual scrollbar dimensions that automation tools often miss, while the Clean Context Iframe check spots patched browser APIs that break under cross-context inspection. The platform feeds all 106+ checks into an AI model that weighs the complete pattern across browser, network, device, and behavior layers. Only when the full picture supports automation does it classify the session as bot and suppress the conversion event.

This corroboration approach avoids false positives from privacy tools, corporate networks, or unusual devices that might trigger one odd signal but behave humanly across the rest.

Common mistakes to avoid

• Installing the script only on the thank-you page. BotRefund needs to observe the full journey from landing page through conversion to build a complete session profile.
• Disabling suppression too early. The first 48–72 hours are a learning window; let the model calibrate on your traffic before judging volume.
• Changing campaign targeting while auditing. Preserve attribution (campaign, ad set, creative, placement, click ID) until you have a clean baseline, or you’ll conflate targeting changes with bot removal.
• Treating every suppressed event as fraud. Some suppressed sessions may be low-intent humans with atypical behavior. Use the session recordings and signal breakdown to distinguish patterns before requesting refunds.

Limitations and when this does not apply

• BotRefund operates client-side in the browser. It cannot detect server-to-server fraud that never loads your page (e.g., API-level click injection).
• It requires JavaScript execution. Visitors with scripts disabled or heavy ad-blockers that strip third-party scripts will not be analyzed.
• Refund approval rests with Google and Meta. BotRefund provides evidence in the format their reviewers expect, but the platforms make the final credit decision.
• The 99% confidence figure applies to sessions where the evidence supports it; not every flagged session reaches that threshold.

FAQ

How long until I see cleaner conversion data?

Most accounts see a measurable drop in reported conversions within 24–48 hours of enabling suppression, with downstream quality metrics (call connect rate, demo book rate) improving over the first 7–14 days as the bidding algorithms retrain on the filtered signal.

Does BotRefund slow down my page?

The script loads asynchronously and is designed to add negligible latency. It collects signals passively during the visit and only intercepts conversion pixel calls at the moment they fire.

Can I use BotRefund alongside Cloudflare or a WAF?

Yes. Edge layers handle infrastructure threats (DDoS, WAF rules). BotRefund adds the marketing-layer evidence — behavioral, browser, and attribution signals tied to paid clicks — that edge providers do not capture. They serve different jobs and can run together.

What if I only run Google Ads, not Meta?

BotRefund protects Google Ads conversion pixels the same way. Connect your Google Ads conversion IDs in the dashboard, map your events, and enable suppression. The refund-ready reports are formatted for Google’s invalid-activity credit process.

How do I request a refund with the evidence?

Export the refund-ready report from the BotRefund dashboard for the date range in question. The report includes click IDs (GCLID/FBCLID), campaign hierarchy, timestamps, session recordings, and signal-by-signal reasoning. Submit it through Google’s or Meta’s invalid-traffic claim flow, or share it with your platform representative. BotRefund’s team has supported 2,500+ such negotiations.

What happens to the suppressed conversion events — are they lost?

They are logged in the BotRefund dashboard with full session evidence. You can review, export, or re-enable them if you determine a suppression was incorrect. They are not sent to Meta or Google while suppression is active.

Is there a minimum spend requirement?

BotRefund offers a free bot audit to quantify the problem first. Paid plans scale with traffic volume; the enterprise tier covers accounts under $10,000/mo in ad spend.

BotRefund protects conversion signals by placing a lightweight script on your landing pages that observes every visitor session after a paid click. The script evaluates 110+ independent signals — pointer movement, scroll behavior, input timing, browser consistency, network context, and attribution identifiers — and scores each session with up to 99% confidence. When a session crosses the bot threshold, BotRefund can suppress the conversion event so it never fires to Meta Pixel or Google Ads tags, keeping your optimization data clean. At the same time, it captures the click ID, timestamp, campaign hierarchy, and a full session recording, then packages that evidence into a report structure that Google and Meta reviewers already expect.

To start, you add the BotRefund snippet to every page that receives paid traffic, connect your ad accounts so the system can match sessions to click IDs, and choose which conversion events to guard (lead forms, purchases, sign-ups, custom events). The dashboard then shows flagged sessions side-by-side with your CRM outcomes, letting you verify that suppressed events match the contacts your sales team cannot reach. Once the evidence pile is large enough, you submit the refund-ready report through the platform's invalid-activity flow or let BotRefund's team negotiate on your behalf — their 2,500+ audits yield an 83% recovery rate.

What conversion signals are at risk

Conversion signals are the events you tell ad platforms to optimize for: form submissions, button clicks, page views tagged as leads, purchase completions, or any custom event fired from your pixel or tag manager. When bots trigger these events, three things happen at once. First, you pay for clicks that cannot become customers. Second, the platform's bidding model learns to chase the same low-quality placements, audiences, and creatives that produced the fake conversions. Third, your CRM fills with unreachable contacts — disconnected numbers, invalid email domains, repeated addresses — wasting sales time and distorting downstream metrics like cost per qualified opportunity.

Meta campaigns are especially exposed because they serve across Facebook, Instagram, and partner inventory at high volume. A lead campaign can receive accidental taps, low-intent traffic, automated browsing, and deliberate fraud from affiliate payouts or publisher scripts. Google Ads faces similar pressure from data-center IPs, VPNs, click farms, and impression-refresh bots. In both cases, the platform's built-in filters catch only a fraction; the rest poisons your pixel and inflates reported performance.

How BotRefund identifies invalid traffic

BotRefund does not rely on IP blocklists or user-agent strings alone. Instead, it runs 106+ client-side checks inside the visitor's browser, each producing an independent piece of evidence. Examples include the Scrollbar Width Leak (detecting mismatches between reported and actual scrollbar dimensions), Clean Context Iframe (spotting patched or hidden browser APIs that automation tools leave behind), ghost-click detection (clicks without the natural human intent sequence), honeypot-trap interactions (bots responding to hidden page elements), robotic linear mouse movements, superhuman input speed under 1 millisecond, grid-aligned movement patterns, absence of human-like mouse tremor, and unnatural session durations.

No single check decides the verdict. Each signal feeds an AI prediction model that weighs the complete pattern across browser, network, device, and behavior dimensions. Privacy tools, corporate networks, travel, and unusual devices can create anomalies for real people, so BotRefund treats every signal as evidence — not a verdict — and cross-checks it against the full context. The outcome is a session-level classification with up to 99% confidence, plus a plain-language explanation of which signals fired and why they matter.

Step-by-step implementation

1. Add the BotRefund snippet to every paid landing page. Place it in the <head> so it loads before your pixel and tag-manager events. The script is asynchronous and does not block page rendering.
2. Connect Meta and Google ad accounts in the BotRefund dashboard. This lets the system match each session to its click ID (fbclid, gclid, wbraid, gbraid), campaign, ad set, creative, and placement.
3. Select the conversion events to protect. Choose from standard events (Lead, Purchase, CompleteRegistration, Contact) or map custom events from your tag manager. BotRefund will intercept the event fire, evaluate the session in real time, and only allow the event through if the session passes the human threshold.
4. Set suppression rules. Decide whether to block the event entirely, send a "null" conversion value, or flag it for review. Most teams start with a shadow mode — logging flagged sessions without suppressing — to verify accuracy against CRM outcomes.
5. Run a shadow-period audit (7–14 days). Compare BotRefund's flagged sessions against your CRM contactability data: disconnected phones, bounced emails, no-show rates, and sales-team feedback. This validates the model before you let it modify live conversion signals.
6. Enable live suppression. Once the shadow audit confirms alignment, switch to active mode. BotRefund now prevents bot sessions from firing conversion pixels in real time.
7. Export refund-ready reports monthly or quarterly. Each report includes click IDs, campaign details, timestamps, session recordings, and signal-by-signal reasoning formatted for Google and Meta invalid-activity review teams.

Protecting Meta conversion signals

Meta's pixel fires on every matched event, and its delivery system optimizes toward the events it sees. If bot leads fire the Lead event, Meta learns to serve more impressions to the placements, audiences, and creatives that produced those leads. BotRefund stops this by evaluating the session before the Lead event reaches the pixel. The script captures the fbclid, matches it to the campaign hierarchy, and runs the 110+ signal checks. If the session is classified as automated, the Lead event is suppressed; the pixel never receives it. Your reported lead count drops, but the remaining leads are contactable — sales teams at FinTrust saw an 18% conversion-rate increase after suppression began.

BotRefund also preserves attribution for the suppressed events. The click ID, timestamp, placement, and device data stay in the audit log, so you can still analyze which campaigns attracted the invalid traffic and adjust targeting without losing the forensic trail. This matters because Meta's invalid-traffic review expects click-level evidence, not aggregate estimates.

Protecting Google Ads conversion signals

Google Ads uses GCLIDs (and newer GBRAID/WBRAID parameters) to tie conversions back to clicks. BotRefund captures these identifiers on landing-page arrival, then monitors the full session. When a conversion event fires — whether from a form submit, button click, or enhanced conversion — BotRefund checks the session score. Automated sessions are blocked from sending the conversion to Google's tag. The result: your conversion column reflects only human actions, Smart Bidding trains on real outcomes, and you avoid the "conversion lag" that occurs when Google's automated filters retroactively remove invalid conversions days later.

Google's invalid-activity credit system reimburses advertisers for clicks it determines are not genuine user interest — repeated manual clicks, automated tools, accidental mobile taps, data-center IPs, impression fraud, and competitor click fraud. However, Google's detection is server-side and misses client-side automation that mimics human behavior. BotRefund's client-side evidence (session recordings, behavioral signals, click IDs) fills that gap. The platform accepts refund claims backed by this evidence format; BotRefund's team has negotiated 2,500+ such claims with an 83% approval rate.

Verification and ongoing monitoring

After live suppression is on, treat the BotRefund dashboard as a quality-control layer, not a set-and-forget filter. Weekly, review the flagged-session list against three CRM signals: contactability rate (calls connected / leads received), qualification rate (SQLs / leads), and sales-cycle velocity. If contactability improves but qualification drops, you may be suppressing borderline sessions — adjust the confidence threshold. If a new campaign shows a sudden spike in flagged sessions, check placement-level breakdowns; audience expansion or new creative formats often attract different bot profiles.

Quarterly, export the refund-ready report and submit it through Google's invalid-activity form or Meta's ad-quality appeal flow. Include the session recordings and signal breakdowns; platform reviewers prioritize claims with click-level, session-level evidence. BotRefund's team can handle the submission and follow-up if you prefer not to manage the negotiation directly.

Key facts

Limitations and when this does not apply

BotRefund protects conversion signals on pages you control. It cannot suppress events that fire server-side (e.g., offline conversion imports, CRM-to-platform APIs) unless you route those through a client-side gate. It does not replace server-side fraud infrastructure — DDoS mitigation, WAF rules, or edge bot management — and works alongside them. The 99% confidence figure applies when the full signal cluster supports it; edge cases (privacy browsers, corporate proxies, unusual devices) may produce lower-confidence sessions that require manual review. Refund approval is ultimately decided by Google and Meta; BotRefund provides evidence and negotiation support, not a guarantee. The 83% recovery rate reflects historical audits, not a promise for every account.

FAQ

How long does the shadow audit take before I can trust live suppression?

Most teams run 7–14 days. Compare BotRefund's flagged sessions against your CRM contactability and qualification data. When the flagged set matches the contacts your sales team cannot reach, you have validation.

Does BotRefund slow down my landing pages?

The snippet loads asynchronously and adds negligible weight. It does not block rendering or interfere with Core Web Vitals.

Can I protect only some conversion events and not others?

Yes. You choose which events to guard in the dashboard — standard events (Lead, Purchase, etc.) or custom events from your tag manager.

What if a real user gets flagged as a bot?

The model treats every signal as evidence, not a verdict, and cross-checks 106+ independent checks. False positives are rare, but the shadow period lets you catch them before live suppression. You can also whitelist known IP ranges or user segments.

Do I need to submit refund claims myself?

You can. BotRefund generates the report in the format Google and Meta expect. Their team can also submit and negotiate on your behalf — they've handled 2,500+ claims.

How does this differ from Cloudflare or other edge bot protection?

Edge tools block traffic before it reaches your server. BotRefund observes the visitor journey after the click, preserves attribution, protects conversion pixels, and builds refund evidence. Many advertisers run both: edge for infrastructure protection, BotRefund for ad-quality evidence.

What happens to the click IDs for suppressed conversions?

They are retained in the audit log with full session context. You can still analyze which campaigns, placements, and creatives attracted invalid traffic without polluting your optimization signals.

Direct Answer: How BotRefund Reduces Fake Leads

Install BotRefund's JavaScript snippet on your landing pages. The script runs 106 independent browser checks — including scrollbar width leaks, clean context iframe tests, pointer movement analysis, and input speed timing — to build a session-level evidence package. Each visit receives a bot-probability score. Sessions that cross the 99% confidence threshold are flagged, documented with click IDs, timestamps, and signal-by-signal reasoning, and exported as a report that Google and Meta accept for invalid-activity credit claims. Simultaneously, you can suppress conversion pixels for flagged sessions so your bidding algorithms stop optimizing toward bot traffic.

Prerequisites Before You Start

• Active paid campaigns on Google Ads or Meta Ads (Facebook/Instagram) with conversion tracking already in place.
• Access to your website's <head> or tag manager to paste the BotRefund snippet.
• Admin rights on the ad accounts to submit invalid-activity claims once reports are generated.
• CRM or lead database access to correlate BotRefund flags with downstream outcomes (calls connected, demos booked, qualified opportunities).

Step-by-Step Implementation

1. Create a BotRefund account and run the free bot audit. The audit scans recent traffic and shows the percentage of sessions flagged as automated. This baseline tells you whether a paid plan is justified.
2. Install the tracking snippet. Paste the provided JavaScript into the <head> of every landing page that receives paid traffic, or deploy via Google Tag Manager with a "All Pages" trigger. The script loads asynchronously and does not block page render.
3. Verify data collection in the dashboard. Within 15–30 minutes, visit your own landing page from a test device. The session should appear in the BotRefund live view with a human score. Confirm that click IDs (GCLID for Google, fbclid for Meta) are captured.
4. Enable conversion-pixel suppression (optional but recommended). In the BotRefund dashboard, toggle "Protect conversion signals." When a session is flagged as bot with ≥99% confidence, BotRefund prevents the Meta Pixel or Google Ads conversion tag from firing for that session. This keeps your optimization algorithms trained on real leads only.
5. Let the system accumulate evidence for 7–14 days. Do not pause campaigns or change targeting during this period. The platform needs a representative sample across placements, creatives, audiences, and devices.
6. Generate a refund-ready report. Navigate to the Reports section, select the date range, and click "Generate Refund Report." The output includes: campaign/ad set/creative breakdown, click IDs, timestamps, session recordings, and a signal-by-signal explanation for every flagged session.
7. Submit the claim to Google or Meta. For Google Ads, use the Invalid Activity Credit form and attach the BotRefund PDF. For Meta, open a Business Support case, reference the report, and request a manual review. BotRefund's 83% success rate across 2,500+ audits comes from formatting evidence exactly as platform reviewers expect.
8. Reconcile CRM outcomes. Export the flagged click IDs and match them against your CRM. Verify that flagged sessions correspond to disconnected numbers, invalid emails, or leads that never progressed. This step closes the loop and proves the system isn't over-flagging.

How BotRefund Detects Fake Leads: The Evidence Layer

BotRefund does not rely on IP blocklists or user-agent strings alone. Instead, it runs 106 independent client-side checks grouped into six categories:

• Biometric & behavioral interactions: Mouse tremor absence, superhuman input speed (<1ms), grid-aligned movement patterns, robotic linear mouse paths.
• Click behavior: Ghost click detection — clicks that fire without the natural sequence of human intent.
• Trap behavior: Honeypot trap interactions — bots that respond to hidden or deceptive page elements.
• Engagement behavior: Absence of clicks or scrolling, sessions that stay too static to match a real browsing journey.
• Session behavior: Unnatural session durations (too short, too long, or too uniform).
• Evasion & anti-stealth traps: Clean Context Iframe checks that expose automation tools patching or hiding browser APIs; Scrollbar Width Leak checks that catch mismatches between reported and actual scrollbar dimensions.

Each check produces an independent evidence point. The AI prediction model weighs the complete pattern across browser, network, device, and behavior data rather than trusting any single rule. This corroboration approach is why BotRefund achieves 99% confidence when the session evidence supports it.

Using the Evidence for Refund Claims

Google and Meta both operate invalid-activity credit systems, but automatic detection catches only a fraction of bot traffic. Google's server-side systems look for rapid clicking, duplicate click signatures, known bad IPs, and abnormal server-level patterns. Meta's filters are similar. Neither sees the client-side behavioral signals that BotRefund captures.

A BotRefund report bridges that gap. It structures the evidence in the format platform reviewers use: click IDs (GCLID/fbclid), campaign hierarchy, timestamps, session recordings, and a signal-by-signal rationale. The FinTrust case study illustrates the result: a neobank recovered $140,000 (14% bot click rate) and saw an 18% conversion-rate increase after suppressing bot conversions from pixel training data.

Integration with Meta and Google Ads Workflows

Meta Ads

• BotRefund captures fbclid parameters and maps each flagged session to the exact campaign, ad set, creative, and placement.
• Placement-level spikes are a key signal: a sudden lead-quality drop on Audience Network or Reels often indicates publisher script fraud.
• Reports can be filtered by placement, creative, or audience expansion setting to isolate the worst offenders before submitting a claim.

Google Ads

• BotRefund captures GCLID and aligns flagged sessions with Search, Display, YouTube, and Performance Max campaigns.
• The report format matches Google's Invalid Activity Credit submission requirements, including the click IDs and behavioral evidence Google's automated systems cannot see.
• For Performance Max, where placement transparency is limited, BotRefund's onsite evidence is often the only way to prove invalid traffic by asset group.

Monitoring and Ongoing Optimization

After the first refund cycle, treat BotRefund as a continuous quality layer:

• Weekly dashboard review: Check the bot-percentage trend. A sudden spike often coincides with a new creative, audience expansion, or placement opt-in.
• Suppression list export: Download flagged click IDs weekly and upload them as excluded audiences in Google Ads (via Customer Match) or Meta (via Custom Audiences) to prevent retargeting bots.
• Pixel retraining: With conversion-pixel suppression active, your bidding algorithms gradually re-optimize toward human traffic. Expect 2–4 weeks for full effect.
• Quarterly re-audit: Run a fresh free audit each quarter. Bot tactics evolve; the 106-check suite updates automatically.

Limitations and When This Advice Does Not Apply

• Low-volume campaigns: If you spend under $1,000/month, the evidence sample may be too small for a successful claim.
• Non-paid traffic: BotRefund is designed for paid-click attribution. Organic, direct, or referral bot traffic is detected but not refundable.
• Sophisticated human fraud: Click farms with real people on real devices will pass behavioral checks. BotRefund flags automation, not low-intent humans.
• Single-page apps with heavy client-side routing: Ensure the snippet fires on every virtual page view; otherwise, sessions may be split and evidence fragmented.
• Strict CSP policies: If your Content Security Policy blocks inline scripts or third-party domains, you must whitelist BotRefund's endpoints.

Key Facts

FAQ

How long before I see results?

Data appears in the dashboard within minutes of installation. Meaningful refund reports typically require 7–14 days of traffic across multiple campaigns.

Does BotRefund block bots in real time?

It does not block at the network edge. Instead, it suppresses conversion pixels for flagged sessions and provides evidence for platform refunds. For real-time blocking, pair it with a WAF or Cloudflare.

What if Google or Meta rejects the claim?

BotRefund's 83% success rate includes negotiation support. If a claim is denied, the team helps refine the evidence and re-submit. There is no guarantee of approval.

Can I use BotRefund without submitting refund claims?

Yes. Many clients use only the conversion-pixel suppression to clean their optimization data. The audit and dashboard remain free for baseline monitoring.

How does this differ from Google's or Meta's built-in invalid traffic filters?

Platform filters operate server-side (IP, user-agent, click patterns). BotRefund operates client-side (browser behavior, device fingerprint, interaction biomechanics). They catch different fraud vectors; using both is complementary.

What does BotRefund cost?

Pricing is not published in the source pack. The homepage references an "Enterprise" tier and a "Under $10,000/mo" selector. Contact sales for a quote based on monthly ad spend.

Will the script slow down my landing pages?

The snippet loads asynchronously and is designed not to block rendering. No performance impact data is provided in the source pack.

BotRefund retains evidence by installing a lightweight script on your landing pages that records every visitor session after a paid click. The script collects over 110 independent signals — including click timing, mouse movement patterns, scroll behavior, browser fingerprint inconsistencies, and network context — and ties each session to its originating campaign, ad set, creative, and click identifier (GCLID or fbclid). This data is stored in a structured report that matches the evidence format Google and Meta require for invalid-activity credit requests.

To preserve evidence, install the script before you launch or continue campaigns, let it run without pausing traffic, and export the audit-ready report when you file a refund claim. The platform keeps session-level detail so you can show exactly which clicks were automated, not just aggregate estimates.

What BotRefund Evidence Looks Like

Each flagged session comes with a session recording, a list of triggered detection signals, and the attribution metadata that connects the visit to your ad spend. The report includes click IDs, campaign names, placement, device, timestamp, and a signal-by-signal explanation of why the visit was classified as automated. This granularity is what platform reviewers look for — they need to see the specific behavior, not a summary score.

BotRefund's detection combines behavioral, browser, hardware, and network signals. Examples include ghost clicks (clicks without human intent sequence), honeypot trap interactions, robotic linear mouse movements, absence of humanlike mouse tremor, superhuman input speed under 1 millisecond, grid-aligned movement patterns, absence of clicks or scrolling, and unnatural session durations. No single signal proves fraud; the system cross-checks all 110+ signals and weighs them through an AI model that reaches 99% confidence when the full pattern supports it.

Prerequisites Before You Start

• Active paid campaigns on Google Ads or Meta Ads — BotRefund tracks traffic that originates from paid clicks with click identifiers.
• Access to add JavaScript to your landing pages — The tracking script must load on every page a paid visitor might reach.
• Admin access to the ad accounts — You need campaign, ad set, and creative names to map evidence to spend.
• No immediate campaign pauses — Preserve attribution by keeping campaigns running while the audit collects a representative sample.

Step-by-Step Evidence Retention Process

1. Create a BotRefund account and add your domain. The platform generates a unique tracking snippet.
2. Install the snippet on all landing pages that receive paid traffic. Place it in the <head> so it loads before user interaction.
3. Verify the script is firing using the BotRefund dashboard's live view. Confirm sessions appear with click IDs (GCLID for Google, fbclid for Meta).
4. Let traffic run for a meaningful period — typically 7–14 days or until you have several hundred paid sessions. Do not pause campaigns during this window.
5. Review the audit dashboard. Filter by campaign, placement, device, or date to see bot-rate breakdowns and flagged sessions.
6. Export the refund-ready report. The report packages click IDs, timestamps, session recordings, and signal reasoning in the format Google and Meta review teams expect.
7. File the invalid-activity claim with the platform using the exported report as evidence. BotRefund's team can assist with claim formatting and negotiation.

Key Signals BotRefund Captures

The system groups signals into categories that map to human vs. automated behavior:

• Click behavior — Ghost click detection catches clicks that lack the natural sequence of human intent.
• Trap behavior — Honeypot interactions reveal bots that respond to hidden page elements.
• Pointer behavior — Robotic linear movements and grid-aligned paths flag scripted navigation.
• Motion behavior — Absence of humanlike mouse tremor (micro-jitter) indicates automation.
• Speed behavior — Superhuman input speed under 1 ms exceeds physical human limits.
• Engagement behavior — Absence of clicks, scrolling, or field corrections suggests non-human sessions.
• Session behavior — Unnatural durations (too short, too long, or too uniform) and missing page engagement.

Each signal is recorded as independent evidence, then cross-checked against browser, network, device, and behavioral context before the AI model assigns a bot/human classification.

How Evidence Maps to Platform Refund Requirements

Google's invalid activity credit system and Meta's traffic quality review both require click-level evidence tied to specific campaigns. Google looks for rapid clicking, duplicate click signatures, known bad IPs, and abnormal server-level patterns. Meta evaluates placement-level quality spikes, conversion events without meaningful page engagement, and contactability signals (disconnected numbers, invalid emails). BotRefund's reports provide the click IDs (GCLID/fbclid), timestamps, and behavioral proof that align with these criteria.

The platform formats reports so reviewers can verify each flagged click without translating security logs. This reduces back-and-forth and increases approval rates — BotRefund cites an 83% recovery rate across 2,500+ audits.

Common Mistakes That Weaken Evidence

• Pausing campaigns before the audit completes. This breaks the attribution chain between click IDs and sessions.
• Installing the script on only some landing pages. Missed pages create gaps in the evidence trail.
• Filtering traffic at the edge (CDN/WAF) before it reaches the page. BotRefund needs to see the full browser session to capture behavioral signals.
• Treating every bad lead as bot traffic. Real people with low intent are not fraud; the system distinguishes lead-quality variation from automation.
• Submitting aggregate estimates instead of session-level reports. Platform reviewers reject summary-only evidence.

Verification: Confirming Your Evidence Is Complete

Before filing a claim, check three things in the BotRefund dashboard:

1. Click ID coverage — Every flagged session should show a GCLID or fbclid. Missing IDs mean the script didn't fire on the landing page or the click came from an untracked source.
2. Signal diversity — Flagged sessions should trigger multiple independent signals, not just one. Single-signal flags are less persuasive to reviewers.
3. Campaign mapping — Verify that flagged sessions map to the correct campaigns, ad sets, and creatives in your ad account. Mismatches suggest tracking-parameter issues.

If any of these checks fail, extend the collection window or troubleshoot the script installation before submitting.

Limitations and When This Doesn't Apply

• Organic and direct traffic — BotRefund focuses on paid-click attribution. Sessions without click IDs are not tied to ad spend.
• Server-side only environments — The script requires client-side execution in the visitor's browser. Pure server-to-server funnels (e.g., API-only conversions) won't generate behavioral evidence.
• Campaigns already paused — You cannot retroactively capture sessions for clicks that happened before installation.
• Platforms beyond Google and Meta — Refund-ready reports are formatted for Google Ads and Meta Ads. Other platforms may accept the evidence but have different claim processes.
• Privacy tools and corporate networks — VPNs, privacy browsers, and managed devices can produce anomalous signals. BotRefund treats these as evidence, not verdicts, and cross-checks them to avoid false positives.

Key Facts

FAQ

How long does evidence collection take?

Most audits need 7–14 days of live traffic to build a representative sample. High-volume campaigns may reach significance faster; low-volume campaigns may need longer.

Can I use BotRefund evidence for a claim I already filed?

Only if the claim is still open and you can supplement it with session-level data. Platforms rarely reopen closed claims.

Does the script slow down my pages?

The snippet is lightweight and loads asynchronously. It does not block rendering or affect Core Web Vitals in typical implementations.

What if my site uses a CDN or WAF like Cloudflare?

BotRefund works alongside edge layers. The script runs in the browser after the request reaches your page, capturing behavioral signals that edge filters cannot see. You do not need to replace your CDN.

How does BotRefund differ from Google's or Meta's automatic invalid-click filters?

Platform filters operate at the server level and catch known patterns (rapid clicks, bad IPs). BotRefund adds client-side behavioral evidence — mouse movement, scroll timing, browser fingerprint — that server logs miss. This catches advanced bots that mimic human IPs and click patterns.

Can I export raw data for my own analysis?

Yes. The dashboard allows session-level export with all signals, recordings, and attribution metadata.

What happens if a real user gets flagged?

BotRefund's 99% confidence threshold requires multiple corroborating signals. Single anomalies (e.g., a privacy tool causing a browser fingerprint mismatch) are kept as evidence but not treated as verdicts. The AI model weighs the full pattern before classifying.