Why AI Ad Fraud Refund Claims Get Denied: 7 Mistakes That Kill Your Refund

Insufficient traffic logs, missing timestamps, and filing after the platform's deadline are the top reasons AI ad fraud refund claims get denied. Most advertisers do not lose because the fraud did not happen. They lose because the evidence does not meet the platform's standard.

Google, Meta, TikTok, and Reddit expect session-level proof of invalid traffic. When your claim shows weak logs, no clear timestamps, or arrives late, the reviewer rejects the entire filing. This article lists the most common mistakes in the order they usually appear in a claim, then gives you a checklist to make your next filing harder to refuse.

The denial pattern: what reviewers actually check

Ad platforms do not tell you exactly why they deny every claim. But the pattern is consistent across refund workflows. Reviewers look for three things: proof that each session existed, proof that the traffic was invalid, and proof that you filed on time.

When any of those three is missing, the claim falls apart. Here is how the process usually goes wrong.

The symptom. You submitted a refund request for 1,200 clicks. The platform replied with a one-line denial. You have no idea which part failed.

The diagnosis order. Check, in this order: Did I file within the window? Do my timestamps match the platform's records? Do I have per-session evidence, or only totals? Each question points to a different fix.

Mistake 1: Evidence that cannot stand alone

Ad platforms want to see sessions, not summaries. A spreadsheet with total clicks and total spend proves nothing about any single visitor. Reviewers need to open a record that shows: when the session happened, where it came from, what the visitor did, and why that behavior is not human.

Weak evidence looks like this:

• A screenshot of a dashboard total
• A list of IP addresses with no timestamps
• An export from an analytics tool that the platform cannot verify

Strong evidence looks like this:

• Session ID, timestamp, duration, mouse movement, scroll depth, and clicked elements
• User agent, device, and IP address for each session
• A clear statement of why the session is not human (sub-second clicks, zero dwell time, or scripted patterns)

Fix: Build each claim around individual sessions. If you cannot reproduce a single session record from your logs, start there before you file.

Hypothetical example: one advertiser filed a claim for 800 sessions with a PDF summary of total spend and clicks. The platform denied it within 48 hours. A month later, the same advertiser filed again with per-session CSV records showing timestamps, IPs, dwell times, and movement patterns. The second claim was accepted for most of the sessions. The traffic had not changed. The evidence had.

Mistake 2: Missing timestamps and session detail

A timestamp is not a nice extra. It is the anchor that lets the platform match your evidence to its own records. Without it, a reviewer cannot verify that the click you flagged actually happened in their system.

Three timestamp errors kill claims:

1. No timestamp at all. You list an IP address without the time. The platform cannot connect it to a click.
2. Wrong timezone. Your logs are in UTC but the platform's reports use your account timezone. Every record looks shifted, and the reviewer dismisses the mismatch.
3. Rounded or approximate times. You say "sometime between 10:00 and 11:00." The platform needs the exact second.

Session detail matters for the same reason. Clicking behavior, dwell time, and navigation path are the evidence that separates AI-driven bots from human users. Without those, your claim reads like guesswork.

Fix: Export timestamps in the platform's timezone, to the second, with a session ID that can be matched to the platform's click ID.

Mistake 3: Filing after the platform deadline

Google and Meta both set a window for refund requests, typically measured in days after the invalid traffic occurs. Miss that window and the platform will not even review your evidence. The claim is dead before it starts.

This mistake is the easiest to avoid and the most common reason claims never reach the reviewer. It happens because ads run continuously, fraud is discovered weeks later, and the filing process sits at the bottom of a team's to-do list.

Hypothetical example: a retail team noticed a spike in bot clicks on a Tuesday morning. They flagged it internally, planned to file Friday, but a product launch pushed the task to the following week. By the time the claim was submitted, the window had closed. No amount of session evidence could open it again.

Fix: Set a recurring task that checks for suspicious traffic weekly, not monthly. If you spot a cluster of bot clicks, file within days, not weeks. Also, check the deadline for the specific platform you are filing against—they are not all identical, and the page might change without notice.

Mistake 4: Labeling every anomaly as a bot

A high bounce rate is not proof of bot traffic. A page that takes four seconds to load can create sessions that look short and unengaged. Users who hit the back button after a slow load are not bots. Flag them, and your claim loses credibility.

Refund reviewers see false positives all the time. When you mix genuine bot sessions with ordinary human behavior, the entire claim becomes harder to accept. The reviewer cannot tell which sessions you flagged correctly.

Fix: Only include sessions with a repeatable, documented pattern. Two or three examples of identical behavior (same dwell time to the millisecond, identical navigation order, no mouse movement) are stronger than thirty loose guesses.

Mistake 5: Aggregated numbers instead of individual sessions

This is the summary trap. You show the platform your total invalid clicks, total spend, and total impressions lost. None of that helps the reviewer make a decision.

Platforms do not refund on aggregate figures. They refund on identified invalid sessions. Each session must carry enough detail to stand alone: a click ID or session ID, the timestamp, the behavior pattern, and the rationale for classifying it as a bot.

Fix: Structure every claim as a list of sessions. If your evidence does not identify specific sessions, you have not built the case yet.

Mistake 6: Ignoring platform-specific rules

Google, Meta, TikTok, and Reddit each run their own refund workflows. The evidence that works for Google may not work for Meta. The same file that Meta accepts may be rejected by TikTok.

Each platform publishes its own invalid-traffic policy and filing channel. Some want CSV exports, some want a form, some want a support ticket. Reviewers automatically deny submissions sent in the wrong format, through the wrong channel, or referencing the wrong policy. This is a procedural issue, not a factual one, so your evidence never gets read.

Fix: Read the platform's refund guide before you file. Confirm the file format, the channel, and the deadline for the specific platform you are filing against. If you are not sure, contact platform support first, then build your report to match their request.

Diagnosis order: check your claim before you file

Use this checklist. If you answer "no" to any item, fix it before you press submit.

1. Did this traffic occur inside the platform's refund window?
2. Do I have a session ID or click ID for every session in the claim?
3. Does every record include a precise timestamp in the platform's timezone?
4. Do I have per-session behavioral evidence (duration, clicks, scroll, movement)?
5. Have I explained why each session is invalid, not just unusual?
6. Am I filing through the platform's official channel with the format it expects?
7. Did I separate genuine bot sessions from ordinary poor performance?

If all seven answers are yes, the claim has a real chance. If not, the denial probably started inside your own evidence. Run the checklist after you prepare the report but before you submit it. Also run it weekly if you are tracking ongoing bot traffic, so you file little by little within each window instead of waiting to build a huge claim that misses the deadline.

Key facts about AI ad fraud refund claims

These facts come from Seatext's documentation and public product pages. They describe what the Bot Refund Agent detects and what kind of evidence it prepares.

When even a clean claim fails

Even with perfect session evidence, some claims get denied. Platforms reserve the right to define what counts as invalid traffic. A session you classify as a bot may be classified as "low-quality human" by the platform, and that category is rarely refundable.

Claims also fail because of internal policy changes, or because the platform's own data does not match your logs. That does not mean the evidence was wrong. It means the platform made a different call.

For that reason, treat the 87% acceptance figure as a strong signal, not a guarantee. Build the best evidence you can, and expect a minority of filings to be rejected through no fault of your own. Do not let that stop you from filing the next one. Each denial teaches you something—what the platform wants from your logs, what window it enforces, and how it classifies edge cases—and that knowledge improves every future claim.

Terms you will see in refund workflows

Invalid traffic (IVT). Clicks or impressions that a platform determines are not from a genuine, interested user. Bots, crawlers, and some click farms fall here.

Session evidence. A record of what happened in one visit, including timestamps, actions, and device data.

Refund-ready report. A document formatted so an ad platform can review and accept it without extra work on your side.

Pixels poisoning. When bot sessions fire your tracking pixel, your retargeting audience fills with fake visitors and your conversion data gets distorted.

FAQ

What counts as "session evidence" for a refund claim?

Session evidence is a record of a single visit that includes the click or session ID, timestamp, duration, actions taken, and device data. It must be detailed enough for the platform to match it to its own logs and decide whether the traffic was invalid.

How early should I file a claim after spotting bot traffic?

File as soon as you have verified the sessions are invalid. The sooner you file, the more likely your evidence still matches the platform's data, and the less risk you take on missing the platform's deadline window.

Should I file one large claim or several small ones?

Smaller, focused claims are usually easier to review and less likely to be rejected because of a single weak entry. Separate genuine bot clusters from each other, and file each cluster with its own session evidence.

If I use automated bot detection, do I still need manual proof?

Automated detection gives you the raw material, but you still need to file through the platform's official channel with the format it expects. The platform does not accept "my tool said so." It accepts session records that stand on their own.

Can I request refunds for Google, Meta, TikTok, and Reddit with the same evidence?

The same detection system can create evidence for all of those platforms. But each platform has its own filing form and rules, so you may need to adjust the report to match each platform's expectations. The underlying session data transfers; the packaging does not.

Does bot traffic harm my campaigns beyond wasted spend?

Yes. Bot sessions can fire your tracking pixels and poison retargeting audiences, which means future ads get shown to fake users and your conversion data becomes unreliable. Bot filtering deals with that damage before it compounds.