Direct Answer: It looks at browser capabilities and whether they are complete and internally consistent. For example, History Evasion checks for missing, simplified, or inconsistent details that a real browsing session would not normally show. BotRefund uses this as one of 106 independent checks,...

Direct Answer: A duplicate campaign can fail immediately if bots contaminate it during the first 48 to 72 hours, while the original happened to collect human conversions early. The ad algorithm assigns heavy weight to those first recorded interactions, so a bot-heavy start can...

Direct Answer: They often build partial or placeholder implementations that do not hold up when checked from multiple angles. BotRefund's Background Navigation check looks for these internal inconsistencies. Then it cross-checks the anomaly with independent browser, network, device, and behavior data. That is why...

Direct Answer: Automated browsers often patch or hide browser APIs to look more like a real user. But those patches can be detected when the same APIs are checked from another angle. BotRefund's toString Patch Shadow check is designed to catch that mismatch. It...

Direct Answer: Automated browsers often patch or stub browser APIs to hide their automation, which can leave incomplete or inconsistent navigation timing data. BotRefund's check looks beyond the surface to find these stubs. Even sophisticated bots may miss this detail. The signal then becomes...

Direct Answer: Automation tools often patch only the surface APIs and leave other parts incomplete. When BotRefund checks beyond the surface, it finds missing or simplified capabilities that a real browser would expose consistently. This mismatch is reflected in the Chrome API Stub signal.

Direct Answer: Automation tools often patch browser APIs to hide, but those patches do not always hold up under a different kind of check. The Iframe Webdriver Leak check in BotRefund is designed to spot that kind of break. Because it is one of...

Direct Answer: Automation tools often patch browser APIs to hide, but those patches can break when the browser is checked from another angle. The Error Stack Proxy check specifically looks for these mismatches. BotRefund then cross-checks with other signals to confirm the visit is...

Direct Answer: Because a single browser tell can be caused by a real user. Privacy tools, corporate networks, travel, and unusual devices can all create unexpected behavior. BotRefund uses 106 independent checks to build a reliable picture. The AI model only makes a decision...

Direct Answer: Inconsistency often stems from bot traffic that varies day to day. When bots are active, they pollute your conversion data and cause the algorithm to shift budget. BotRefund provides real-time detection and pixel suppression, smoothing out performance by ensuring the algorithm only...

Direct Answer: Privacy tools, corporate networks, and unusual devices can change browser fingerprints in ways that mimic automation. BotRefund records these anomalies as evidence but does not label them as bots without corroborating signals. This reduces false positives while still flagging suspicious activity.

Direct Answer: When you duplicate a campaign, the new campaign enters its learning phase and is highly vulnerable to bot contamination. If the first 20–50 interactions are from bots on low-quality publisher networks like Google Search Partners, the algorithm will optimize for more bot...

Direct Answer: Meta's automated filters catch general invalid traffic like known bots and data center IPs. Sophisticated invalid traffic uses residential proxies, real devices, and human emulation to pass server-side checks. BotRefund uses client-side behavioral signals to catch these bots after Meta has already...

Direct Answer: Automated browsers often expose partial or placeholder browser capabilities that fail when checked deeply. BotRefund's Background Navigation check looks for those inconsistent details that a real browsing session would not produce. That evidence is cross-checked with browser, network, device, and behavior signals....

Direct Answer: BotRefund says accuracy comes from corroboration, not one browser tell. It sends each signal like HTTP Protocol Mismatch into a prediction AI that weighs the complete picture across browser, network, device, and behavior evidence. By seeing how all signals fit together, it...

Direct Answer: Because a real browsing session usually has connection, location, language, and timing that fit together. Automated browsers often break that coherence through proxy rotation or location masking. BotRefund uses this mismatch as one piece of evidence, not as the sole reason to...

Direct Answer: Because genuine people can produce unexpected behavior for many valid reasons. Travel, privacy tools, corporate networks, and unusual devices can all cause an anomaly in a browser check. BotRefund keeps each signal as objective evidence and cross-checks it against independent data. Only...

Direct Answer: A single anomaly, like an audio mismatch, is not a bot verdict because legitimate users can have unexpected behavior due to privacy tools, travel, or unusual devices. BotRefund keeps this signal as evidence and cross-checks it against independent browser, network, device, and...

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...

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...