What is the Facebook ad refund process step by step?

Direct Answer: First, log FBCLIDs server-side on every landing page visit. Then deploy client-side behavioral analysis to capture bot signals. Next, build an evidence package with FBCLIDs, timestamps, anomalies, and charge amounts. Finally, submit the dispute through Meta Business Help Center. BotRefund automates most...

Direct Answer: It is used to spot automated browsers that try to behave like people reading a page. A real visitor shows pauses and decision-making while scrolling, while a scraper often sends interactions more quickly and uniformly. BotRefund treats this mismatch as one objective...

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: Start by excluding high-risk display placements, narrowing your geographic targeting to people physically in your service area, and adding hidden honeypot fields to your forms. Then install a real-time behavioral firewall like BotRefund to block bots before they trigger your pixels. These...

Direct Answer: The check compares the operating‑system identifier with the set of fonts reported by the browser. Spoofed or virtual browsers often present a mismatch because they cannot perfectly emulate a real device’s font library. When a mismatch is found it becomes a strong...

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 Iframe Webdriver Leak check is one of 106 independent signals BotRefund uses to evaluate a visit. It looks for a mismatch that automation tools often create when they patch or hide browser APIs. A real browsing session normally does not produce...

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: It is looking for a mismatch between how a normal browser runs standard APIs and what an automated browser reveals. Automation tools often patch browser APIs to hide themselves, but those patches can break when checked from another angle. BotRefund uses this...

Direct Answer: It is one of 106 independent checks BotRefund uses to distinguish human visitors from automated browsers. The check looks for a mismatch that often appears when automation tools patch browser APIs. A normal browser usually shows consistent built-in properties and rendering contexts....

Direct Answer: Meta's standard review window is 14 to 30 business days. Disputes with complete evidence packages are processed faster than incomplete ones. BotRefund generates a structured report with FBCLIDs, timestamps, behavioral anomalies, and charge amounts. That helps Meta locate the billing records and...

Direct Answer: The Mobile Menu Probe is one of the 106 independent checks BotRefund uses to spot automated browsing. It looks for a mismatch that a real browsing session does not normally create. Scripts can send clicks and scrolls, but they struggle to reproduce...

Direct Answer: The Permission Lie check looks for a mismatch in browser APIs that a real browsing session does not normally create. Automated browsers often patch or hide APIs, but those changes can break when inspected from another angle. BotRefund uses it as one...

Direct Answer: It is one of 106 independent checks BotRefund uses to spot automated browsers. It looks for a mismatch that a normal browser session does not create, often caused by automation tools patching or hiding APIs. BotRefund treats this as evidence and cross-checks...

Direct Answer: AI models weigh the complete pattern of all detection signals instead of following rigid raw rules, which reduces false positives from normal user variation. BotRefund's AI evaluates how its 106 independent checks align across browser, network, device, and behavior data to make...

Direct Answer: AI prediction allows the system to evaluate the full constellation of signals rather than relying on a single rule. BotRefund model takes all 106 independent checks and determines the likelihood that a visit is automated. This approach adapts to new evasion techniques...

Direct Answer: BotRefund's AI prediction model weighs the complete pattern of signals, including rapid tab blurs, mouse movements, scrolling, and browser fingerprints. Instead of relying on a single rule, the AI evaluates how all the evidence fits together. This allows it to identify sophisticated...

Direct Answer: AI prediction weighs the complete pattern of evidence instead of trusting a raw rule. A mismatch like History Evasion becomes one input into a model that evaluates browser, network, device, and behavior data together. This is how BotRefund reaches high accuracy without...

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...