Does Google not already do this?

Google's automated filter catches part of the spectrum, particularly known bots and data-centre traffic. The IAS 2025 Media Quality Report measured fraud rates of 10.9 percent on campaigns without anti-fraud technology, fifteen times higher than campaigns with protection. The gap is the long tail Google is not built to catch on a per-account basis.

Will it block real customers?

Any prevention system will occasionally block a real visitor. A well-tuned tool keeps the false-positive rate well below one in ten thousand, gives you per-campaign visibility into what was blocked and why, and lets you tune thresholds. ClickGuardian surfaces both metrics in your dashboard so you can sanity-check them.

How fast can I see savings?

Most accounts see invalid-click rates change within the first week as exclusion lists fill up with the worst offenders. The full picture, including cleaner cost-per-conversion and improved smart-bidding signal, takes thirty to sixty days because the auction needs time to react to the cleaner conversion data.

Does it work on Performance Max?

Yes. PMax is harder than Search because Google takes more of the placement decision, but ad-server-level signals are still available. ClickGuardian scores PMax visits the same way it scores Search visits and adds offenders to the campaign-level exclusion list, which PMax respects.

How does prevention differ from Google's invalid-traffic credits?

Credits are reactive and partial. You absorb the bad click into your daily budget on the day, then submit for a refund. Prevention is real-time. The click is blocked before your budget moves, so the budget stays available for a real customer in the same daily window.

Pillar Guide

Click Fraud Prevention

A 2026 guide to click fraud prevention: how to stop fraudulent clicks on Google Ads and Microsoft Advertising before they cost you a sale.

If you run Google or Microsoft Ads, you are paying for clicks. Some of those clicks come from real customers. Many do not. Bots, click farms, and competitors all click on paid ads with no intention of becoming a customer, and each of those clicks costs you the same as a real one. Click fraud prevention is the discipline of stopping the bad clicks before your card is charged. This guide covers what prevention actually means in 2026, the five techniques that do the heavy lifting, and a two-week playbook any SMB can run, even without paying for a tool.

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What is click fraud prevention?

Click fraud prevention is the practice of identifying and blocking fraudulent clicks at the moment they happen, before the ad platform charges you. It scores every visitor on IP reputation, device fingerprint, behavioural signals, and click velocity, then blocks suspicious clicks at the campaign exclusion-list level. The crucial distinction is between prevention (real time) and detection (after the fact).

Detection happens after the fact. You look at your campaign data, spot a wave of suspicious clicks, and submit a refund request. Google might credit some of them. You absorb the rest.

Prevention happens before the fact. Every visit is scored in real time. Suspicious sources are added to the platform's IP exclusion list, or the click is intercepted at the ad-server level, before your daily budget moves at all.

The difference matters for cash flow and for campaign signal. A click that is detected and credited a week later still ate into your daily budget cap on the day it happened, which probably stopped your ads from showing to a real customer. It also distorted the optimisation signal that Google and Microsoft use to bid on future auctions. A click that is prevented does neither.

If you are new to the topic, our complete guide to click fraud covers what fraudulent clicks actually are and the major categories. The rest of this page assumes you already know what you are dealing with and want to know how to stop it.

For the technical detail on how dedicated click fraud protection software scores and blocks each suspicious visitor in real time, the feature overview covers the full detection stack: IP reputation, device fingerprinting, behavioural analysis, and click velocity signals.

Why prevention beats refunds

Google's invalid-click filter is real. According to Google Ads Help, the platform automatically removes some invalid clicks from your bill, and credits others retroactively. Microsoft Advertising runs a similar process. Both are real, both are useful, and neither is enough on its own.

The numbers tell the story. The IAS 20th Media Quality Report (published 2025) found that campaigns running without anti-fraud technology hit a four-year-high fraud rate of 10.9 percent, fifteen times higher than campaigns with protection. The platforms catch a lot. They do not catch everything.

Run the maths on your own account. Take a campaign spending £3,000 a month with a fraud rate of 18 percent (in line with what competitive verticals like locksmiths, legal, and HVAC report). That is £540 of fraudulent traffic. If Google's filter catches and refunds 5 percent of that, you save £150. The remaining £390 a month is yours to absorb, every month, until something changes.

That is the prevention case in two paragraphs. Refunds are partial. They arrive after the fact. They do not protect the daily budget that put you in front of a real customer in the first place. Prevention stops the click going through, which means the budget stays available, the campaign signal stays clean, and the refund process becomes the safety net it should have been all along.

Techniques

The five techniques real prevention uses

Each addresses a different signal class. Together they catch the long tail Google's filter misses.

1. IP and device fingerprinting

Every visit to your landing page leaves a footprint. The IP address tells you which network the request came from. The device fingerprint, a hash built from screen size, fonts, browser configuration, time zone, and dozens of other signals, tells you which device. The combination is far more identifying than either signal alone. A residential IP that hits twelve different advertisers' landing pages in ninety seconds, all with the same browser fingerprint, is not a real customer. Neither is a data-centre IP using a Chrome configuration that has never appeared in any real-user data set. Prevention works by maintaining a live reputation score for both IPs and fingerprints, then blocking the click when both signals are bad.

2. Behavioural signals

Bots have got better at faking IPs. They have got worse, relatively speaking, at faking what humans do on a page. Real visitors move the mouse in a way that follows visual attention. They scroll. They pause on the headline. They take, on average, two to three seconds before clicking the first interactive element. Bots either skip these signals entirely or perform a flat, mechanical version of them. Modern prevention tools record a rolling window of behavioural signals, dwell time, scroll depth, mouse trajectory, time-to-first-input, and score the visit against a baseline of confirmed human traffic.

3. VPN and proxy detection

VPNs are no longer the hallmark of a privacy-minded power user. They are how organised click fraud routes around IP-based blocking. A single fraud network might rotate through twenty thousand residential proxies in a day, each one looking like a real household connection. Detecting this requires either an up-to-date list of known VPN exit nodes (Imperva and DoubleVerify both publish these as part of their data feeds) or behavioural inference (a household connection that originates a thousand clicks an hour is not a household). Prevention layers both.

4. Click-velocity rules

Velocity rules are the simplest technique on this list and the easiest to underestimate. The principle is that a real customer rarely clicks the same advertiser's ad five times in an hour, ten times in a day, or thirty times in a week. A bored competitor and a misconfigured bot both look exactly like that. A velocity rule blocks repeat clicks from the same fingerprint or IP after a configurable threshold. Decent tools let you tune the thresholds per campaign because the right number depends on your spend, your average customer journey, and your tolerance for false positives. A high-CPC legal campaign benefits from tighter rules than a low-CPC ecommerce campaign where genuine customers might click twice while comparison shopping.

5. Placement and publisher exclusions for Display and PMax

On Search, fraud comes in through clicks. On Display and Performance Max, it comes in through publishers. A campaign running on the Display Network places ads on hundreds of third-party sites, some of which exist primarily to generate ad revenue from non-human traffic. Performance Max takes this further by automating placement entirely, which is convenient and also means you have less visibility into where your ads are being shown. Prevention here looks like a maintained exclusion list of low-quality publishers, automatic exclusion of new placements that show fraud-pattern symptoms (high CTR, zero conversions, traffic outside your geography), and regular review of the placement report. Google added full Search Partner placement reports in August 2025, which made this part easier.

Native protection vs dedicated tool

Native platform protection covers the obvious end of every signal above (known bots, data-centre traffic, basic velocity). A dedicated tool covers the long tail (rotating residential proxies, AI-driven behaviour mimicry, slow-drip fraud designed to stay under the velocity threshold). The difference is roughly the gap between Google's reported invalid-click rate and the IAS-measured fraud rate of 10.9 percent on unprotected campaigns. See the full numbers on the click fraud statistics page.

What you cannot prevent (and why that is fine)

Click fraud prevention solves a specific problem. It does not solve everything that gets called "ad fraud". Three categories sit outside its scope, and it pays to be clear about that before you buy a tool.

Brand safety is the first. If your ads are placed next to objectionable content, that is a placement quality problem, not a click fraud problem. Tools like DoubleVerify and IAS specialise in this. ClickGuardian does not.

Attribution fraud is the second. This is the practice of injecting fake conversion events into ad networks so that another network gets credit for a sale you actually drove. It is mostly an affiliate-marketing and mobile-app-install problem. SMB Search and PMax advertisers are rarely the target.

Ad stacking is the third. This is the practice of layering multiple ads on top of each other in a single placement so the publisher gets paid for impressions no human could possibly see. Again, this is a publisher-side problem and a viewability problem, not a click fraud one.

The honest scoping matters. A tool that claims to do everything ends up doing nothing well. Click fraud prevention focuses on stopping fraudulent clicks before they cost you. That is the lever with the biggest impact on an SMB Search budget. For the wider taxonomy, including impression fraud, attribution fraud, and where each one hits, see the ad fraud protection guide.

Playbook

A two-week click fraud prevention playbook

You can do most of the work in this section yourself, with no tool. The remaining gap is what dedicated software fills. Run this playbook even if you never buy a thing.

1

Week 1, day 1

Audit

Open Google Ads. Add the Invalid Clicks, Invalid Click Rate, and Invalid Interactions Rate columns to your campaign view. Take a screenshot. This is your baseline.
2

Week 1, day 2

Location targeting

For every campaign, switch Location Settings from 'Presence or interest' (the default, and the leaky one) to 'Presence'. Same for exclusions. This single change cuts a meaningful chunk of out-of-area traffic with no other downside.
3

Week 1, day 3

Keyword tightening

Move your highest-spend broad-match keywords to phrase or exact match. Build a starter negative-keyword list (jobs, salary, free, tutorial, DIY, plus competitor brand names if you do not want to bid on them).
4

Week 1, day 5

Search partners

Decide whether to keep them on. If you do, segment your reports by network and watch the next two weeks of conversion data. If Search Partners convert worse, switch them off.
5

Week 2, days 1–3

Weekly monitoring

Set up a recurring 15-minute Monday review of invalid click rate, cost per conversion by campaign, click-to-call ratio, time-of-day click distribution, and geographic distribution. Track in a spreadsheet.
6

Week 2, day 4

Manual IP exclusions

Pull the obvious offenders out of your server logs (or Google Analytics). Add them via Settings → IP Exclusions. You get 500 per campaign and 500 at the account level.
7

Week 2, day 5

Decide on prevention

If your weekly numbers still show a gap between clicks and conversions you cannot explain, automated prevention is the next step. The free playbook only goes so far.

How ClickGuardian handles prevention

ClickGuardian sits between the click and your campaign budget. Every visit to a landing page is scored in real time across the five technique categories above. Suspicious visits are blocked before the platform charges you, and the offending IPs are added to your campaign-level exclusion lists automatically. Lists rotate so you never hit Google's 500-address cap. See click fraud protection for the full feature list.

Three concrete examples of the patterns prevention catches in the wild:

Pattern 1: Competitor scripted clicks via residential VPN

A locksmith spending £4,000 a month sees 20-plus percent of clicks from a residential proxy range another local locksmith is paying for. Prevention picks up the velocity pattern within twelve hours and adds the proxy range to the exclusion list. The pattern stops costing the campaign within a day.

Pattern 2: Bot-driven sub-two-second sessions

A solicitor on a £25 personal-injury CPC sees clicks from inside the service area but with zero scroll and sub-two-second dwell. Behavioural signals flag the visits as bot-driven before conversion data could confirm it. The cleaner signal also lets Google's smart bidding find more genuine customers per pound spent.

Pattern 3: PMax placements bleeding budget

A home-services Performance Max campaign is burning impression share on third-party placements with every fraud-pattern symptom (high CTR, zero conversions, foreign traffic). Placement-exclusion automation clears the worst offenders within a week. Real-customer impressions per pound go up.

Setup runs through the Google Ads protection integration in about five minutes. Microsoft Advertising is the same. Start a free 7-day trial →

FAQ

Frequently asked questions

Yes. Blocking a request from reaching your landing page, or asking the ad platform to exclude an IP from your campaign auctions, is well within the Google Ads and Microsoft Advertising terms of service. Both platforms publish API endpoints specifically for managing exclusion lists programmatically.