Direct Answer: Rule-based detection trusts a raw signal by itself, while AI-based detection weighs the complete pattern. BotRefund sends all 106 signals into a prediction AI that evaluates browser, network, device, and behavior evidence together. This approach is what supports the 99 percent accuracy...

Direct Answer: The page recommends preserving attribution first, then comparing Meta reporting with web analytics, server logs, call records, email verification, and CRM stages before you touch targeting or budgets. Keep campaign, ad set, creative, placement, click identifier, landing-page URL, and timestamp with each...

Direct Answer: The free Starter tier allows up to three hundred bot detections per month. It includes the full verification dashboard and self‑service refund report generation. If you exceed the limit, you can upgrade to a paid plan for unlimited coverage.

Direct Answer: The Headless UA Evader check looks for mismatches that a real browsing session does not normally create, such as tool-specific shortcuts or automation remnants. BotRefund uses this as one of 106 independent checks to build a reliable picture of whether a visit...

Direct Answer: The Keyboard Layout Leak check looks for a mismatch that a real browsing session does not normally create. Virtual machines and spoofed profiles can claim one device while their graphics, fonts, audio, or processor behavior tells another story. This signal adds objective...

Direct Answer: Corroboration means several independent signals point to the same conclusion instead of one tell being enough. BotRefund uses 106 independent checks and evaluates them with an AI model. The model weighs the complete pattern across browser, network, device, and behavior data. That...

Direct Answer: Independent evidence adds objective facts about a visit. BotRefund collects 106 such facts, including the Error Stack Proxy check. Each fact is cross-checked against others. This corroboration is what allows the tool to reach 99% accuracy instead of relying on a single...

Direct Answer: The ‘Visited History’ check compares the browser’s reported history state with what a real user would have after navigating the web. Automated browsers often expose missing or placeholder history entries. BotRefund flags these inconsistencies as part of its evidence. It’s a strong...

Direct Answer: Bot detectors look at hardware, graphics, fonts, audio, and operating-system details to see if they naturally fit together. A real browser usually reports details that match the device, while an automated browser may claim one device but reveal another through its processor...

Direct Answer: You need detailed forensic evidence that proves the clicks were automated. BotRefund provides verified GCLID/FBCLID click IDs, millisecond timestamps, campaign names, session replays, and explanations of why the session was automated. This is the exact format that Google and Meta's review teams...

Direct Answer: It collects objective facts from browser, network, device, and behavior checks. For example, the Fast Reading Scraper check looks at whether clicks and scrolls match human reading behavior. BotRefund labels this as independent evidence. It then uses cross-checked context and AI prediction...

Direct Answer: Advanced tools use a wide range of signals beyond IP addresses, including browser API consistency, device hardware details, network telemetry, and behavioral patterns like scroll timing and mouse movement. BotRefund uses 106 independent checks across all these categories, cross-referencing them to avoid...

Direct Answer: BotRefund analyzes more than 110 behavioral and technical signals. It looks at mouse movement patterns, sub‑millisecond click timing, lack of tremor, grid‑aligned paths, and session duration anomalies. It also checks browser integrity, hardware fingerprints and network attributes to build a forensic case.

Direct Answer: It should keep the anomaly as evidence and investigate the rest of the visit before deciding. Privacy tools, travel, corporate networks, and unusual devices can produce false alarms. BotRefund cross-checks the anomaly with independent data and only calls it a bot when...

Direct Answer: You should look at the complete evidence pattern rather than the one anomaly. A real visitor can appear unusual because of privacy tools, travel, corporate networks, or accessibility devices. BotRefund avoids making a verdict from a single signal and only flags a...

Direct Answer: Sub-second form completions are a red flag for automated bot behavior. The page recommends verifying conversion timestamps and comparing platform conversions against actual orders. BotRefund can help document these anomalies and suppress pixels on suspicious sessions.

Direct Answer: Duplicated campaigns often fail because the original happened to acquire human conversions early while the duplicate was contaminated by bots in its opening hours on Search Partners or Audience Network. BotRefund prevents this inconsistency by suppressing pixels on bot sessions from installation...

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...