Which Metrics Should I Track to Prove AI-Detected Fraud for a Refund Claim?

To win a refund for AI-detected ad fraud, you need four metrics above all others: invalid click rate, bot traffic percentage, IP reputation scores, and conversion drop-off after click. Platforms like Google and Meta ask for evidence that shows suspicious activity, not just a hunch. These metrics give you that proof because they quantify behavior that humans and bots clearly separate.

When you file a refund claim, the platform’s review team looks for a clear pattern. A single data point rarely convinces them. They want to see a consistent story across multiple signals. The four metrics listed here appear in most successful claims because they directly measure what platforms already monitor internally. Without them, your request looks like an unverified guess. With them, you provide a timestamped, verifiable trail that matches the platform’s own fraud detection logic.

Why These Metrics Matter for Refund Claims

Ad platforms review refund requests with automated systems and human analysts. They look for patterns that match known fraud signatures. The four metrics below are the ones that appear in most accepted claims because they directly measure what platforms already monitor.

Google Ads, for example, automatically filters invalid clicks. If you see a sudden spike in your invalid click rate, that often means the platform itself has detected something unusual. Meta, on the other hand, focuses more on session quality and conversion behavior. TikTok and Reddit are newer but follow similar logic. By aligning your evidence with what each platform already tracks, you make it easier for them to approve your claim.

Ignoring these metrics means your refund request looks weak. You might say “we had a lot of bot traffic,” but without numbers, the platform has no reason to act. Metrics create a timestamped, verifiable trail. They show the exact scope of the problem and allow the review team to cross-check your data against their own logs. This is why the four metrics are the backbone of any strong refund case.

The Four Core Metrics Explained

Each metric tells a different part of the fraud story. Together, they form a complete picture that is hard to dismiss. Below we break down each one, why it matters, and how to measure it correctly.

Invalid Click Rate

This is the percentage of clicks that the ad platform already flags as invalid. It includes accidental clicks, clicks from known bots, and other non-genuine interactions. The platform calculates this from its own detection systems, so it carries significant weight in a refund request.

Track it daily per campaign. A sudden spike—say from 1% to 10%—is a red flag. When you see that spike, capture the exact date, time, and campaign. Platforms often look for a coinciding event, such as a bot attack or a spike in data center traffic. Your documented invalid click rate can help you point to that moment.

To get this number, log into your ad platform and view the “invalid clicks” column for each campaign. Divide the invalid clicks by total clicks and multiply by 100. If you use Google Ads, this data is under the “Campaigns” report. Meta provides similar data in its ad reporting. If you don’t see it, request it from your account manager or use a third-party tool that pulls it.

Bot Traffic Percentage

This is your own measurement of traffic that comes from automated scripts, data center IPs, or known bot signatures. Unlike invalid click rate, which the platform reports, bot traffic percentage comes from your own analytics or a bot-detection tool. It gives you independent proof that the platform might not see directly.

Use a bot-detection tool to count sessions that never move a mouse, load pages too fast, or fail JavaScript challenges. For example, a real human takes time to read a page, while a bot may click through in milliseconds. Also, bots often come from data center IPs that are not typical residential addresses. Tools like Seatext’s Bot Refund Agent scan paid traffic for these patterns and document suspicious sessions.

The higher this percentage, the stronger your case. A normal bot traffic percentage is under 2%. Above 5% is suspicious. Above 10% is a strong refund trigger. When you collect this data, make sure you exclude your own internal traffic and any known crawlers like Googlebot. Otherwise, you will inflate the numbers and weaken your credibility.

IP Reputation Scores

Each IP address has a reputation score based on past abuse. Services like Spamhaus or SORBS classify IPs. When a large share of your clicks come from low-reputation IPs, it supports your fraud claim. Save screenshots of these scores for your evidence file.

To find this, use a tool that looks up the reputation of each IP that clicked your ad. You can batch-check IPs from your server logs or ad platform data. Focus on the IPs that generated the most clicks without any conversions. Those are usually the bot IPs.

Low-reputation IPs often come from known botnet ranges, open proxies, or hosting providers. When you show that a significant portion of your traffic originates from these IPs, the platform cannot easily ignore it. Pair this with bot traffic percentage to show a consistent pattern.

Conversion Drop-Off After Click

Genuine visitors sometimes convert. Bots almost never do. If hundreds of clicks land on your page but zero of them reach a form, add to cart, or purchase, that gap reveals fraud. Track post-click conversion rate separately for suspicious traffic versus clean traffic.

To measure this, tag your traffic sources. You can use UTM parameters or a tool that separates bot sessions from humans. Then compare the conversion rate of clicks that look like bots (e.g., high invalid click rate, low IP reputation) against the conversion rate of clean traffic. If the suspicious traffic converts at near zero, that is powerful evidence.

For example, if your normal conversion rate is 2% but the bot traffic converts at 0.01%, you have a clear signal. Include a table in your refund claim showing the differences. Platforms understand that bots do not buy. This metric often becomes the most persuasive part of your case because it ties the fraud directly to wasted spend.

How to Track and Store This Evidence

Collecting the metrics is only half the battle. You also need to store them in a way that is organized and easy to present. Here is how to set up a reliable evidence collection process.

First, use a consistent time zone for all your reports. Mixing time zones confuses the review team and can undermine your credibility. Pick one time zone, usually the one where your ad account is based, and stick to it across all logs.

Second, exclude your own internal traffic. If you or your team click your own ads, those clicks will skew the bot traffic percentage. Use IP exclusions in your analytics and ad platform to filter out your office IPs. Also exclude known partner IPs if they visit for testing.

Third, take screenshots of every key dashboard view. Platforms change their interfaces, and you want to preserve the exact data you based your claim on. Save screenshots of the invalid click rate, bot traffic percentage, IP reputation scores, and conversion drop-off charts. Name the files with dates and campaign names so you can find them quickly.

Fourth, export raw data whenever possible. CSV exports from your ad platform and analytics tool are easy to verify. Keep these exports in a folder per month. When you file a refund claim, you can include the exports or offer to share them on request.

Finally, use a tool that automates the collection. Manual tracking is error-prone. Tools like Seatext’s Bot Refund Agent automatically scan paid traffic, document suspicious sessions, and generate refund-ready reports. They also filter bots before they poison your retargeting audiences. Automation saves time and improves the credibility of your evidence because it is consistent.

How to Choose the Right Metrics for Your Platform

Google and Meta have different expectations. Google Ads accepts bot traffic and invalid click data from third-party tools. Meta focuses on session quality and conversion signals. TikTok and Reddit are newer but follow similar logic.

Your decision rule: use the metric that matches the platform’s stated refund policy. If the policy mentions “invalid clicks” or “fraudulent activity,” lead with invalid click rate. If it mentions “low-quality traffic,” show bot traffic percentage and IP scores.

For Google Ads, start with invalid click rate because Google already tracks it. Then add bot traffic percentage to show the problem is widespread. Google’s automated systems may pick up on a spike, but your independent data reinforces the claim.

For Meta, focus on session quality. Meta looks at how users interact with your site after clicking. A high bot traffic percentage that leads to zero conversions is compelling. Also include IP reputation scores if you have them, because Meta’s review team may not have that data.

For TikTok and Reddit, check their refund policies. They are less mature than Google and Meta. Usually they ask for screenshots of suspicious activity. Use the same four metrics, but be prepared to provide more context, such as session recordings, to prove the clicks are automated.

If you are using a tool like Seatext, it creates evidence specifically for Google, Meta, TikTok, Reddit, and other ad refund workflows. This means the reports are formatted to match what each platform expects. That can save you time and increase your approval rate.

Building a Refund Evidence Dashboard

Create a simple dashboard that updates daily. Include these columns:

• Date and time range
• Campaign and ad group
• Total clicks
• Invalid click rate (platform-reported)
• Bot traffic percentage (your tool)
• Average IP reputation score
• Conversions from clean traffic
• Conversions from suspicious traffic

Set threshold alerts. For example, trigger an alert when invalid click rate exceeds 3% or bot traffic percentage exceeds 5%. These alerts help you capture evidence while it is fresh. They also help you catch a bot attack mid-campaign so you can stop it early.

Your dashboard should be visible to your whole team, not just the person filing claims. That way, everyone can spot anomalies early. If you work with an agency, give them access so they can flag issues before you lose too much spend.

Automate the alerts via email or Slack. When a threshold is crossed, you want an immediate notification. Time is critical. Bot attacks often occur in bursts. If you wait until the end of the week, you might miss the exact window of the attack.

Consider using a tool that provides refund-ready reports automatically. Seatext’s Bot Refund Agent, for example, scans traffic for bots, documents sessions, and prepares evidence you can submit directly to the platform. That reduces the manual work of building a dashboard from scratch.

Common Mistakes When Tracking Fraud Metrics

1. Mixing metrics from different time zones without normalizing.
2. Forgetting to exclude your own internal traffic.
3. Only reporting one metric. Platforms want a pattern, not a single anomaly.
4. Using vague labels like “suspicious” without a definition.
5. Ignoring the conversion drop-off metric—this is often the most persuasive.
6. Not saving raw data or screenshots. If you lose the evidence, you cannot prove anything.
7. Waiting too long to file. Some platforms have a time limit for refund requests. Act within 30 days of the fraud.
8. Relying only on platform-reported numbers. Your independent data adds credibility.
9. Not checking IP reputation scores before filing. A single batch of low-reputation IPs can support your claim.
10. Using a tool that does not generate platform-ready reports. You want a clean export, not a messy PDF.

Avoid these mistakes to keep your claim strong. The review team has seen hundreds of claims. You need to show that you understand the data properly.

Limitations of Metric-Based Fraud Proof

These metrics are not silver bullets. Some legitimate traffic will look like bots—for example, a user with a strict firewall or a privacy browser. Also, sophisticated bots hide by mimicking human behavior. Metrics can prove a pattern, but they cannot guarantee a refund. Each platform has its own approval process, and some reject even strong evidence.

False positives are a real concern. A visitor using a company VPN might come from a data center IP, which lowers their IP reputation score. If that visitor converts, they are clearly human, but they might still be flagged by your bot detection. To avoid this, always combine multiple metrics. If the conversion rate on that IP is normal, it is probably not a bot.

Sophisticated bots can simulate mouse movements and fill out forms. They may even make small conversions to avoid detection. In those cases, your metrics might not catch them. But that is rare. Most bots are simple scripts, and the four metrics work well against them.

Platforms have final discretion. Even if you have perfect evidence, they might deny the refund. This is frustrating, but it is part of the system. You can appeal with more details, but you cannot force approval. The best you can do is make your case as airtight as possible.

Recovery rates vary. Seatext claims that clients can recover up to 20% of Google and Meta spend with bot protection. That is not a guarantee, but it shows the potential when you track fraud correctly.

Key Facts

These facts come from the Seatext product pages. They show what a dedicated bot refund tool can offer.

Frequently Asked Questions

How do I calculate invalid click rate?

Divide the number of clicks marked invalid by your ad platform by the total number of clicks. Multiply by 100. For example, 50 invalid clicks out of 1,000 total clicks gives an invalid click rate of 5%.

What is a good threshold for bot traffic percentage?

Under 2% is normal. Above 5% is suspicious. Above 10% is a strong refund trigger. Use these as guides, but also consider the volume. A small campaign might see more relative variance.

Can I use these metrics for all ad platforms?

Yes, but check each platform’s refund policy. Some want additional evidence like session recordings or IP logs. Google and Meta are the most standardized. TikTok and Reddit may require more context.

How often should I track these metrics?

Daily. Weekly data is too late to capture precise evidence for a refund claim. Alerts should fire in real time when thresholds are crossed.

Do I need a specialist tool to track them?

Not necessarily, but manual tracking is error-prone. Tools that auto-generate reports save time and improve credibility. Tools like Seatext also filter bots before they poison your retargeting audiences.

What if my platform rejects my claim despite clear metrics?

Appeal with more detail. Add screenshots of IP reputation scores and a breakdown of conversion drop-off by hour. Include session recordings if you have them. Sometimes a personal contact at the platform can help.

How long should I keep evidence?

Keep at least six months of data. Some platforms review claims retroactively. If a new bot attack pattern emerges, you may need past data to show a trend.

Can I claim a refund for clicks from the past week only?

Yes, but you need the evidence for that exact week. That is why daily tracking is important. If you wait a month, you might not have the granular data needed.

What if my conversion drop-off is not dramatic?

Even a small gap can help. Compare suspicious traffic to clean traffic. If clean traffic converts at 2% and suspicious at 0.5%, that is still a meaningful difference. Present the comparison clearly.

Decision Rule for Using Metrics in a Refund Claim

Compile your evidence when at least two of the four metrics align. For example, invalid click rate above 5% and bot traffic percentage above 7% is a strong combination. If only one metric is elevated, keep collecting data for a few days before filing.

Here is a simple decision table:

Always include a clear narrative. Explain what happened, when it started, and how your metrics prove it. Attach the evidence dashboard and raw exports. If you use a tool like Seatext, its reports already contain this narrative.

By following these decision rules, you avoid wasting time on weak claims and focus on cases with a real chance of approval.