Seatext library / BotRefund evidence
Which Google Ads Settings Help Prevent Bot Clicks?
Google Ads provides several native settings to reduce bot traffic: IP exclusions, automated rules for pausing campaigns during click spikes, frequency capping, and Google's built-in invalid click filters. These tools catch basic invalid traffic...
✓ Built for advertisers who need clear, refund-ready traffic evidence.
Google Ads gives you four main native levers to reduce bot clicks: IP exclusions to block known bad addresses, automated rules that pause campaigns when clicks spike unnaturally, frequency capping to limit how often the same user sees your ads, and Google's automatic invalid-click filters that run in the background. These settings help, but they only catch the most obvious invalid traffic. Google's own filters catch less than 50% of invalid traffic, leaving the rest classified as sophisticated invalid traffic (SIVT) that requires manual evidence submission.
What Google Ads Native Settings Actually Do
Native settings operate at the network level. They look at IP addresses, click timing, and impression frequency. They do not see what happens after the click — mouse movement, scroll depth, form interaction, or whether the visitor is a real person. That blind spot is why sophisticated bots slip through.
Google's invalid-click filters run automatically on every campaign. They analyze patterns across the network and remove clicks they deem invalid before you're billed. You can see the volume they caught in your Google Ads reports under "Invalid clicks." But the filters are conservative by design: they only remove traffic Google is highly confident is fraudulent, to avoid accidentally blocking real customers.
The Core Settings You Can Configure
IP Exclusions
You can exclude up to 500 IP addresses or ranges per campaign. This blocks clicks from known VPN endpoints, data centers, office networks where click fraud originates, or specific competitors' offices. The limitation: modern botnets rotate through residential IPs that look like normal home connections. Blocking one IP does nothing when the next click comes from a different household.
Automated Rules for Click Spikes
Set rules that pause a campaign, ad group, or keyword when clicks exceed a threshold in a given time window — for example, "pause if clicks increase 300% compared to same day last week." This stops budget bleed while you investigate. The trade-off: legitimate traffic spikes (a viral post, a PR hit) also trigger the pause, costing you real conversions.
Frequency Capping
Limit how many times the same user sees your ad per day, week, or month. This reduces waste from bots that repeatedly click the same ad. It also protects against accidental repeated clicks. The downside: determined fraudsters clear cookies or rotate device IDs, resetting the cap.
Placement and Network Exclusions
Opt out of the Display Network, YouTube, or specific placement categories (games, parked domains, mobile apps) where invalid click rates run higher. Search-only campaigns generally see lower bot rates than Display or Video. The cost: you lose legitimate reach on those networks.
How Each Setting Works (and Where It Falls Short)
| Setting | What It Blocks | What It Misses | Setup Effort |
|---|---|---|---|
| IP Exclusions | Known data-center IPs, VPN endpoints, office networks | Residential proxy botnets, device farms, rotating IPs | Low — manual list maintenance |
| Automated Rules | Sudden volume spikes from basic scripts | Low-and-slow bots that mimic human pacing | Medium — requires threshold tuning |
| Frequency Capping | Repeated clicks from same cookie/device ID | Bots that rotate cookies, use incognito, or reset device IDs | Low — one-time config |
| Network/Placement Exclusions | High-fraud inventory (parked domains, low-quality apps) | Fraud on Search and premium placements | Low — checkbox toggles |
| Google's Auto Filters | Obvious invalid patterns (click farms, known bot signatures) | Sophisticated invalid traffic (SIVT) — human-like behavior, residential IPs | Zero — runs automatically |
Each setting addresses a different layer of obvious fraud. Together they form a baseline. None of them analyze post-click behavior — mouse tremor, scroll patterns, form completion speed, or session depth. That's where sophisticated bots operate.
Decision Criteria: Choosing the Right Mix
Use this framework to decide which native settings to enable and when to add third-party detection.
- Campaign type: Search campaigns benefit most from IP exclusions and automated rules. Display and Video campaigns need placement exclusions first.
- Budget scale: Under $10K/month, native settings plus weekly manual review of invalid-click reports may suffice. Above $10K/month, the absolute dollar loss from missed SIVT justifies a detection layer.
- Vertical risk: Legal, insurance, B2B SaaS, and finance see invalid click rates of 20–35% on high-CPC keywords. These verticals need behavioral detection.
- Refund goals: If you want to recover past spend, you need client-side behavioral evidence (GCLID capture, mouse paths, session recordings). Native settings don't generate that evidence.
- Team capacity: Automated rules require tuning. IP lists need updating. If no one owns this weekly, the settings decay.
Decision rule: Enable all four native settings as a baseline. If your invalid-click report shows >5% invalid rate, or your CRM shows <20% lead-to-opportunity conversion on paid traffic, add a client-side detection tool that captures behavioral evidence for refund claims.
Key Facts
| Metric | Value | Source |
|---|---|---|
| Global digital ad fraud (2026 projection) | Over $100 billion | S1 |
| Average invalid click rate across Google Ads campaigns | 11%–14% | S1 |
| Google's automated filters catch rate | Less than 50% of invalid traffic | S1 |
| Non-human share of internet traffic | 43% | S6 |
| Invalid click rate range by protection level | 4% (well-protected) to 35%+ (high-CPC) | S6 |
| BotRefund refund success rate (high-volume advertisers) | 83% | S2 |
| Bot click budget share estimate | Up to 20% of Google and Meta ad budget | S2 |
| Historical refund recovery window | Back to 2017 | S2 |
Limitations of Native Settings
Native settings cannot detect bots that:
- Use residential proxy networks (real household IPs)
- Simulate human mouse movement, scroll, and dwell time
- Rotate device fingerprints and cookies per session
- Operate low-and-slow to avoid spike triggers
- Click only on Search campaigns where placement exclusions don't apply
Google classifies this as Sophisticated Invalid Traffic (SIVT). The platform's filters catch General Invalid Traffic (GIVT) — known crawlers, data-center IPs, obvious click patterns. SIVT requires evidence you must collect yourself: GCLIDs tied to behavioral fingerprints, session recordings, and interaction timelines.
Native settings also don't protect your conversion pixels. When bots land and trigger conversion events (form fills, button clicks, page views), they poison your pixel data. Google's optimization algorithms then learn to target more bots. This feedback loop compounds waste over time.
When to Add Third-Party Detection
Add a client-side detection layer when:
- You spend >$10K/month on Google Ads and see >5% invalid clicks in reports
- Your CRM shows high lead volume but low sales qualification rates
- You want to file refund claims for past spend (Google allows disputes with evidence)
- You run high-CPC campaigns where each invalid click costs $50–$300+
- You need to protect Meta Pixel or Google Ads conversion pixels from poisoning
Client-side tools (like BotRefund) run in the browser. They capture mouse tremor, pointer velocity, scroll behavior, form interaction timing, and session depth. They tie each session to its GCLID or FBCLID. This evidence package is what Google and Meta require for manual refund approval. Native settings don't produce this data.
BotRefund's detection covers ghost clicks (clicks without human intent sequence), honeypot trap interactions, robotic linear mouse movements, absence of human tremor, superhuman input speed (<1ms), grid-aligned movement patterns, and unnatural session durations. It captures GCLIDs with behavioral evidence and generates audit-ready refund dispute reports. The platform reports an 83% refund success rate for high-volume advertisers and can recover spend dating back to 2017.
FAQ
Does enabling IP exclusions hurt legitimate traffic?
Only if you block ranges too broadly. Exclude specific IPs identified in your invalid-click reports or server logs. Avoid blocking entire ISP ranges unless you have clear evidence.
How often should I review automated rule thresholds?
Weekly for the first month, then monthly. Seasonal traffic changes (holidays, sales events) require temporary threshold adjustments.
Can frequency capping stop click fraud completely?
No. It only limits repeat clicks from the same cookie/device. Sophisticated bots rotate identities per click.
What's the difference between GIVT and SIVT?
General Invalid Traffic (GIVT) is easily identifiable: known crawlers, data-center IPs, non-human user agents. Sophisticated Invalid Traffic (SIVT) mimics human behavior, uses residential IPs, and requires behavioral analysis to detect.
How far back can I claim refunds for invalid clicks?
Google and Meta accept disputes with evidence for spend going back several years. BotRefund recovers spend dating back to 2017.
Do I need coding skills to add client-side detection?
Most tools install via a single JavaScript snippet or Google Tag Manager. No backend changes required.
Will third-party detection slow my site?
Modern scripts load asynchronously and add <50ms. The behavioral analysis runs in the browser without blocking page render.
Next Steps
Start by enabling all four native settings in your Google Ads account. Pull the invalid-click report for the last 30 days. If the rate exceeds 5%, or if your lead quality metrics don't match your click volume, install a client-side detection script to capture the evidence Google requires for refunds. The baseline settings are free and take minutes. The detection layer pays for itself when it recovers even a single month of wasted spend.
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