Why some advertisers see higher refund approval rates

Two advertisers file a refund request: one gets credit, the other doesn't. More often than not the difference is not the size of the budget or how annoyed the advertiser is. It comes down to whether the claim answers the platform's internal checklist of “what a real user does.” Google and Meta already filter easy bot clicks. The claims that go through are the ones where you prove the remaining clicks began with a unnatural sequence of human intent and you do that before the investigation window expires.

In other words approval is a billing-and-evidence question: A refund is a type of invoice dispute. An advertiser who shows the complete path of a click—pointer motion, ghost-click timing, session duration, and the one that can't be human—will almost certainly get a different answer than an advertiser who just sends a column of clicks and a “please refund.” The first style aligns your claim to the platform's own definitions of invalid activity. The second style reads as a plea.

What actually causes refund approval rates to vary?

The largest differences come from three separate mechanisms that stack with each other:

• Documented proof is present. Providers such as BotRefund show whether the clicked session had ghost clicks, wheelchair, trap interactions or non-human pointing movement. When this proof exists, a case is not a hollow puzzle.
• Time is essential. Google and Meta don't keep cut-highly accessible in storage forever. The earlier you file after detection, the more logs you have to rely on.
• Claim placement matters. One case might fit Google's manual click-quality team, while another is better placed before the account rep. The platforms with generous invalid-click policies see higher approval rates overall — advertisers that file on the right page improve their individual likelihood.

That's it. Evidence + deadline + correct bureaucracy. Any part can break the other two.

Why strong behavioral evidence is the core variable

Google's automated filters are indeed designed to catch invalid traffic, but they were not build to catch everyone. In a client-side diagnostic setting, a typical session arrives with a following line-up of signals that a platform's filtered feed has likely already decided are “borderline.” The turning point for a refund claim is whether you can turn those signals into a table the reviewer can follow.

Bot detection tools record the client directly, from the browser. A known example set seen in BotRefund is:

• Ghost click detection — catches click activity that happens without the natural sequence of human intent. The human makes a intent first; a ghost click simply appears.
• Honeypot trap interactions — embedding hidden or intentionally misleading page elements to see which “user” is drawn to them.
• Robotic linear mouse movements — a natural mouse line is rarely a straight line. Perfectly straight pointing paths are a red flag.
• Absence of humanlike mouse tremor — people tremble slightly on purpose; robots don't.
• Superhuman input speed (<1 ms) — no one arrives, presses, drags, and presses in half a millisecond on a touch screen.
• Grid-aligned movement patterns — pointer that snaps from point A to point B in clean elevens.
• Absence of clicks or scrolling — human sessions move; sessions that sit static even longer are usually data-harvesting scripts.
• Unnatural session durations — too short, too long, or too uniform.

This list is not just a “feature” list. Each signal has a name, a measure and a place in a report. When you submit these reports, you’re giving approval with a category the platform can read. You’re not making a rhetorical argument. You are making a classification request.

Diagnostic: score your claim readiness in five minutes

Use this sequence exactly when you are holding a revoke that got auto-filtered or partially removed, but you still think there are invalid clicks. The questions are ordered so that the answer to each decides whether you you should start a tool, rewrite your log, service is the best path, or walk away.

1. Can you show user-in-session behavior from the first click? This includes the actual click timestamp, device, and pointer track. If not, you lose before you start.
2. Do you have a time window anchored signal? Google/Meta data decays; you need the raw server or client logs that prove the session existed on a specific date. If you have that, go to point 3.
3. Is the signal one of Google's approved invalid types? Achieve this before you write. Example approved types are competitor click activity, publisher click fraud, and bot traffic (search in their own document). If your flag doesn't match, the platform undeniably won’t refund it.
4. Does your data show the key property that makes it non-human? Ghost click and honeypot events are the strongest — a human still being in front of the screen doesn't save them. Robotic mouse path and superhuman speed appear only in very a few cases others will ignore.
5. Have you added video or HTML5 snapshot proof? Many campaigns call it “video proof” but not all of them save it. Write from only other proof—never a claim without an artifact.
6. Can you pass the time test? Most platforms have a page investigation window measured from the click date. Even an excellent case dies after that.

If you fail at any point, skip straight to the limitations section instead of forcing refund. It’s not stubbornness, it’s that approval rate is directly correlated to clarity and coverage.

Why timing and platform-specific interpretation matter

Timing operates in two directions. First, the log must be collected from the moment of first suspicious click — not a reconstruction from ad-click data after the fact. Second, the claim must be submitted within the network’s refund policy period. BotRefund states that it can recover for “bot-click refunds from Google Ads spend dating back to 2017,” which suggests that claims timing is set by the advertiser’s own policy, not by the report-day.

Platform nuance also matters. Google’s picture is famous for rejecting “presumed” bots. In their own manual, they specify that a refund request is a formal appeal to the billing and click-quality departments to dispute charges for clicks that their automated filters didn't not remove. That means the ad platform wants to see that you, the advertiser, attempted the manual step. Advertisers that pre-export a client-side behavioral-log package consistently see a better answer because they run at the same folder where the approval decision is made.

Key facts from a glance pack

When a higher refund rate won't happen

Not every click with a bot-distinctive behavior is refundable. The main limitations every advertiser on the side should know:

• The platform's own definitions are narrow. For example, some publishers accept “accidental clicks” types (double-click or fat-finger), but not “image opacity.” If the behavior does not match their definition, even the best diagnostic can't force it.
• Missing client-side logs. If you started the dispute after you already removed the script, you have nothing to prove. Claims have to be satisfied at the moment, not after the fact.
• You are paying for a third-party account still? no. In some Meta accounts, all refund submittal to the platform itself must occur within a set time after the click, and logos don’t matter.
• Advertiser “free” the result. The approval is made by Google staff, not by your plugin. Your plugin contributes evidence, not the verdict.

In other words, not every account or profile can get the same rate. A high approval rate usually sits on a foundation of t11, tight evidence calendar, and the right policy.

Frequently asked questions

Does a higher refund rate come from ad spend size?

No. Spend size can change a team's willingness to give you a human contact, but the refund decision itself is about evidence completeness and category fit. A small advertiser with A+ proof protocol can out-Evidence a large advertiser with a default click report.

Do I need to install a code?

Yes, if you want to build forensic evidence. Client-side code records session-level signals a platform post-click has no access to. Add it before you see signals you want to later use. The setup in the BotRefound flow is roughly one minute and its free audit does not require credit card.

How far can a refund go back?

BotRefund’s site itself says it can “recover bot-click refunds from Google ads spend dating back to 2017,” meaning the historical horizon is not a tiny one—but the details depend on how far the measured system retains logs and how visible the client-side record is.

Does Meta accept same evidence as Google?

Meta’s claim system and Google’s click-quality team are separate applications. You’ll want the same script and the same reporting format, but the “presentation ticket” differences. Some vendors encode two output layouts. Ask before you pay.

What is the deepest difference between a refund claim and a fraud report?

A refund claim is a billing thing. A fraud report is a legal/security thing. You can submit both if you have the evidence, but one can jeopardize the other if you are not careful.

Does refund policy reset call?

No. Your refund requests rate is either by claim or, in some tools, by dollar amount. Keep full history to avoid spray-and-plate.