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Why is a single anomaly not enough to label a visitor as a bot

Why is a single anomaly not enough to label a visitor as a bot

Direct Answer: Privacy tools travel corporate networks and unusual devices can produce unexpected behavior for genuine people. Relying on one signal would cause many false positives. BotRefund keeps each signal as evidence and requires corroboration before issuing a bot verdict.

Why is a single anomaly not enough to prove my ad clicks are from bots?

Direct Answer: A single anomaly can be caused by privacy tools, travel, corporate networks, or unusual devices. BotRefund keeps each anomaly as evidence rather than treating it as a bot verdict. It cross-checks the signal against independent browser, network, device, and behavior data. This...

Why is a single network mismatch not enough to flag a bot?

Direct Answer: A single network mismatch, like an HTTP Protocol Mismatch, is only one objective fact. Genuine users can create unusual signals through privacy tools, travel, corporate networks, or unusual devices. BotRefund treats this as evidence and cross-checks it against other signals. Only after...

Why is an inconsistent Chrome API a sign of an automated browser?

Direct Answer: A real browser has complete and internally consistent APIs, while automated browsers often expose partial or placeholder versions. BotRefund's Chrome API Stub check detects these inconsistencies. This is useful because a bot developer can patch some APIs but leaves others mismatched.

Why is my Meta cost per lead low but the leads are still junk?

Direct Answer: Automated bots can simulate high-intent browsing and submit forms, which makes the reported cost per lead look healthy even when the contacts are fake. The ad platform sees the conversion event and assumes it was valuable. BotRefund can identify those bot sessions...

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Why is my Meta cost per lead low but the leads are still junk?

Why is the CPU Concurrency Lie signal useful for detecting fake ad clicks?

Direct Answer: Fake ad clicks often come from automated browsers and virtual machines, which can lie about their CPU behavior. The CPU Concurrency Lie check catches that lie by looking for mismatches a real browsing session would not create. BotRefund keeps it as evidence...

Why would a bot have a timezone mismatch

Direct Answer: Automated browsers often reveal themselves through inconsistencies in their environment. A bot might show a timezone that does not match its IP location or language settings because it is running on a virtual machine or using proxy rotation. BotRefund's Timezone Evasion check...

Why would a real user trigger an audio sample rate anomaly?

Direct Answer: Unusual devices, privacy tools, travel, or corporate networks can make a real browser report inconsistent details. BotRefund accounts for that by not treating an anomaly as a verdict. It cross-checks the signal with other independent browser, network, and behavior data. A real...

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Why would a real user trigger an audio sample rate anomaly?

Will a bot detection tool flag my visitors who use VPNs or corporate networks?

Direct Answer: It can see unusual behavior from those setups, but that does not automatically make the visit a bot verdict. BotRefund checks whether other signals support the same conclusion before flagging. A real user with a VPN or corporate network may have one...

Will adding a bot detection script interfere with my Google Tag Manager or Meta Pixel setup

Direct Answer: BotRefund's script integrates with existing Google Tag Manager Meta Pixel and TikTok Pixel setups by dynamically suppressing pixel execution only when automated behavior is detected. The lightweight engine does not interfere with legitimate user tracking or conversion attribution for human visitors. Installation...

Will privacy tools or corporate VPNs cause false positives in bot detection?

Direct Answer: Privacy tools, VPNs and corporate networks can produce unusual timing that looks bot‑like. BotRefund treats such anomalies as evidence rather than an automatic verdict. The system compares the signal with other data points before labeling a visit. This reduces the chance of...