How to Use BotRefund with Call Records – What You Need to Know

What BotRefund Does

BotRefund does not analyze call records. It is a tool that detects invalid traffic from Meta and Google ads using behavioral signals.^[S2] If you need to review call recordings, you must use a telephony or call‑analytics platform.

BotRefund monitors web traffic that comes from paid ads and flags sessions that show automated patterns.^[S2] It does not decide a session is a bot based on one clue; instead it gathers more than 110 independent signals from browser, hardware, network, and behavior.^[S3]

Each signal is treated as evidence, not a verdict.^[S3] The platform cross‑checks every signal against the others and feeds the full pattern into an AI model that weighs the complete picture.^[S3] Only when the combined evidence reaches a high confidence threshold does BotRefund label the traffic as invalid.^[S2]

This approach prevents false positives caused by privacy tools, corporate networks, or unusual devices that can trigger a single anomaly.^[S3] By requiring corroboration, BotRefund reports achieve the 99% confidence cited in its documentation.^[S2]

The output is a refund‑ready report that includes click IDs, campaign details, timestamps, session recordings, and a signal‑by‑signal explanation formatted exactly as Google and Meta expect for invalid‑activity claims.^[S2]

Across more than 2,500 audited brands, 83% of clients recover funds from Google and Meta, showing that the evidence package meets the platforms’ review standards.^[S2]

How BotRefund Detects Invalid Traffic

BotRefund collects over 110 signals grouped into five categories: behavioral, browser, hardware, network, and attribution.^[S3] Examples include scrollbar‑width leak, clean‑context iframe, pointer speed, motion jitter, and click timing.^[S5]

Behavioral signals capture how users interact with forms—speed of field filling, scrolling depth, and mouse movement patterns.^[S4] Browser signals look at properties like user‑agent consistency, plugin enumeration, and canvas fingerprinting.^[S4]

Hardware signals examine screen resolution, color depth, and device orientation.^[S4] Network signals inspect IP reputation, ASN data, and connection latency.^[S4] Attribution signals tie the session to a specific click ID, campaign, placement, and timestamp.^[S4]

Each signal is independent; a single anomaly such as an unusually fast form submit does not automatically mean bot traffic.^[S3] Privacy extensions, travel‑related VPNs, or corporate proxies can produce the same reading for genuine users.^[S3]

BotRefund therefore treats every signal as a piece of evidence.^[S3] It checks whether other signals tell the same story—for instance, a fast submit paired with missing mouse jitter and uniform pointer paths strengthens the automation hypothesis.^[S3]

The AI model weighs the complete pattern, assigning probabilities to each session.^[S3] When the aggregated confidence exceeds the internal threshold, the session is flagged and a detailed explanation is generated for the refund report.^[S2]

The platform also records the raw data so auditors can verify each step.^[S2] This transparency helps advertisers understand why a session was marked invalid and gives Google and Meta reviewers the evidence they need to approve a credit.^[S2]

Why Call Records Are Outside BotRefund’s Scope

BotRefund is built exclusively for web‑based ad traffic.^[S1] It loads a JavaScript snippet on landing pages and reads browser events, never accessing audio files, telephony metadata, or call‑center logs.^[S1]

Because it does not ingest call recordings, it cannot flag automated calls, robocalls, or call‑center fraud.^[S1] Its scope ends at the moment a visitor interacts with a tagged web page.^[S1]

If you need to examine call recordings, you must use a system that captures audio from the phone line or VoIP stream and stores it for playback and analysis.^[S6]

Typical call‑analytics platforms record the call, transcribe speech, and index keywords so supervisors can search for specific phrases or detect script deviations.^[S6]

Telephony providers often bundle call‑logging with their service, giving you access to metadata such as caller ID, call duration, and routing information without extra integration.^[S6]

Some organizations use dedicated QA systems that score agent performance, detect silence, or identify compliance issues; these tools work on the audio stream itself, not on web clicks.^[S6]

In short, BotRefund’s technology stack is orthogonal to voice‑focused solutions; trying to use it for call records would yield no data and therefore no actionable insight.^[S1]

Steps to Use BotRefund for Ad Traffic

1. Add the BotRefund snippet to every landing page that receives paid clicks.^[S1] The snippet loads asynchronously and does not affect page load time.
2. Let the tool collect session data for at least 7‑10 days.^[S1] This baseline period captures normal variation in human behavior and establishes the reference profile against which anomalies are measured.
3. Review the dashboard for sessions flagged as bot traffic.^[S1] The dashboard lists the click ID, campaign name, placement, and a brief reason such as “uniform pointer path + missing mouse jitter”.
4. Export the refund‑ready report from the dashboard.^[S2] The report is delivered in CSV or JSON and contains the click IDs, timestamps, campaign details, and a full explanation formatted to match Google and Meta’s invalid‑activity claim templates.
5. Submit the report to Google Ads Invalid Activity form or Meta’s Advertiser Support channel.^[S2] Include a cover letter that references the BotRefund evidence and cites the 99% confidence level.
6. Monitor the claim status and re‑audit if needed.^[S2] If additional information is requested, you can resend the same report or provide supplemental session replays.

Limitations and Requirements

• Requires insertion of a JavaScript tag on the website.^[S1] The tag must be present on every page that receives paid traffic; otherwise those visits are invisible to the tool.
• Only works for traffic that reaches the tagged pages (no offline or call‑center data).^[S1]
• Does not guarantee a refund; success depends on platform review.^[S2]
• Best suited for advertisers spending under $10,000/mo on Meta/Google ads (as noted in source material).^[S2]
• Users with strict content‑security‑policy (CSP) settings must allow the script’s domain; otherwise the tag will be blocked and no data will be collected.^[S1]
• Platform review times vary; Google may issue credits within a few weeks, while Meta can take longer depending on case volume.^[S2] BotRefund notes an 83% success rate across its audits, but each claim is evaluated individually.

Alternatives for Call Record Analysis

If you need to examine call recordings, consider a call‑analytics platform that captures audio from the phone line or VoIP stream, transcribes it, and makes the text searchable.^[S6] Examples include CallRail, Invoca, and DialogTech, which also provide keyword spotting and sentiment analysis.

Telephony providers such as Twilio, Vonage, and Plivo offer built‑in call logging and recording features.^[S6] Enabling these services gives you access to metadata like caller ID, call duration, and routing without extra integration.

Transcription tools like Otter.ai, Rev.com, and Trint can convert recorded calls into searchable text.^[S6] They are useful when you already have audio files and need quick keyword extraction or compliance checks.

Quality‑assurance (QA) systems such as Nice inContact, Genesys Cloud, and Five9 score agent performance, detect script deviations, and flag compliance issues.^[S6] They work directly on the audio stream and often integrate with CRM platforms.

For robocall or spam‑call mitigation, look at services that implement STIR/SHAKEN caller‑ID verification or provide blacklist filtering.^[S6] Nomorobo, YouMail, and carrier‑level STIR/SHAKEN solutions block known fraudulent numbers before they reach your agents.

When choosing an alternative, match the tool to your workflow: if you need real‑time call scoring, a QA platform is appropriate; if you need post‑call searchable transcripts, a transcription service fits; if you want to prevent fraudulent calls from reaching your center, a STIR/SHAKEN or robocall blocker is best.^[S6]

Remember that BotRefund remains valuable for web‑based ad traffic; using it together with a voice‑focused solution gives you full coverage across both channels.^[S1]

Further reading and comparison sources

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

• How to Automate Refunds and Exchanges with AI in Ecommerce | Retell AI
• callthe.bot – Refund Policy
• How do chatbots handle refund or return requests?

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