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  • 2026 Click Fraud Statistics: 50+ Critical Stats for PPC Marketers

2026 Click Fraud Statistics: 50+ Critical Stats for PPC Marketers

  • January 5, 2026
click fraud statistics
  • Global Ad Fraud Losses: Projected to reach $133 billion by 2026
  • Projected Growth: Losses expected to hit $172 billion by 2028 
  • Average Invalid Click Rate (PPC): 11.5% (Google Ads average)
  • Bot Traffic Share: 37% of all web traffic is malicious bots 
  • Most Vulnerable Vertical: Finance, insurance, and industries with high CPCs

22% of global digital advertising(1) spend is lost to fraud every year, according to our own research. For advertisers spending $10,000 per month, that could mean $2,200 disappearing into fraudulent clicks, fake impressions, and bot traffic.

But the problem doesn’t stop there. In 2024, bad bots accounted for 37% of all web traffic, up from 32% in 2023(2). That means more than a third of the “visitors” interacting with digital ads are actually automated programs designed to drain advertising budgets and scrape data.

For PPC campaigns specifically, the numbers are equally stark. Our analysis of thousands of Google Ads accounts reveals an average invalid click rate of 11.5%(3).

There are also worrying trends within programmatic ads, and even the fraud prevention strategies that ad platforms put in place.

So let’s look at the latest ad fraud and click fraud statistics for 2026, get an overview of the industry, and share the most important numbers advertisers need to know.

Top statistics on the size of the problem

top click fraud statistics
  • $84 billion in ad spend was lost to fraud in 2023 globally(1)
  • 22% of total global digital ad spend is lost to ad fraud(1)
  • Ad fraud losses is projected to reach $172 billion by 2028(1)
  • Fraud losses projected to grow 105% over 5 years (2023-2028)(1)
  • 66% of global advertising spend lost to fraud will come from North America and Europe by 2028(1)
  • $23 billion in ad spend is recoverable with fraud mitigation platforms in 2023(1)
  • $47 billion in ad spend is projected to be recoverable by 2028(1)
  • Businesses using adequate fraud protection solutions see average savings of $475/month(1)
  • Up to 448 Invalid Clicks/month can be blocked with fraud protection solutions(1)
  • 530% average ROI on click fraud protection solutions(1)

Why do click fraud loss estimates differ?

You might find different numbers and estimates when researching ad fraud statistics, and here’s why:

Definition scope matters.

Our research found that about $84 billion was lost to ad fraud in 2023. This narrows on deliberate “ad fraud” (click bots, fake impressions, and clearly fraudulent schemes). But broader estimates can be higher, especially if we include all “invalid traffic,” which lumps in accidental clicks, low-quality placements, and non-human interactions that still waste budget.

Why ad platforms don’t provide adequate click fraud protection

Ad platforms have basic fraud protections, but they don’t have the incentive to aggressively flag invalid clicks since it reduces their revenue. In fact, Reuters reports that Meta’s own internal documents estimate up to $16 billion in 2024 revenue tied to scam activity and ads for banned products(8).

Read more: How does Google Ads prevent click fraud?

Statistics on invalid clicks in PPC ads

click fraud stats - average invalid click rate
  • 11.5% average invalid click rate in Google Ads campaigns(3)
  • Invalid click rates have nearly doubled since 2010, growing at an average annual rate of about 4.5%(3)
  • The top 5 countries most impacted by advertising fraud (accounting for 60% of global losses) are the US, Japan, China, South Korea, and the UK.(7)
  • More than 1 out 10 clicks are fraudulent in Google ads.

Invalid clicks vary widely by industry and campaign type

Not all campaign types face equal fraud exposure. Search campaigns typically see the highest rate of invalid clicks. This is because they target high-intent keywords where click costs are higher, so, they are more attractive targets for competitor clicks and bot networks. Display campaigns will generally have a lower invalid click rate.

There are high-risk industries as well, like the legal, insurance, finance, and healthcare industries. Here, campaigns may see invalid click rates well above the average, without adequate click fraud protection.

Our 11.5% figure was based on 96 million ad clicks across 85,000 accounts and 24,582 active Google Ad campaigns. This includes all campaign types.

How much are invalid clicks costing advertisers?

For a business spending $10,000 per month on Google Ads with an 11.5% invalid click rate wastes $1,380 every month, and $16,560 annually. Scale that to enterprise budgets of $100,000+ per month, and you’re looking at six-figure (at least $138,000) annual losses to fraudulent clicks alone.

Statistics on fake traffic and bots

  • 37% of all web traffic(4) generated by bad bots in 2024, up from 32% in 2023
  • ~50% of all internet traffic now generated by bots (good and bad combined)(4)
  • Only 49% of all traffic is from real humans(4)
  • Good bots account for only 14% of global online traffic activity(4)

The problem with fake traffic

The fake traffic problem can show up in different ways across your digital properties. It could be fake website sessions or fake paid visitors. Fake paid visitors are particularly problematic because you’re directly paying for them. Major advertising platforms regularly see 10% to 25% of paid traffic coming from non-human sources.

The real problem isn’t just your wasted budget (although that’s a huge part of it); it’s also the cascade of problems that it brings, like the following:

  • Corrupted analytics data: If up to 25% of your traffic is fake, every metric becomes unreliable. You think you’re making data-driven decisions, but you’re actually optimizing based on polluted data.
  • Skewed conversion rates and ROAS: If a large portion of your traffic is bots that never convert, your true conversion rate is actually higher than reported. But, you won’t know without filtering fake traffic first.
  • Polluted lookalike audiences: Fake traffic can contaminate your seed data when building custom audiences from website visitors. This means you’ll end up targeting users who resemble bots rather than actual customers.
  • Misleading A/B test results: Bot traffic also skews test results, leading to incorrect conclusions about which variations actually perform better.

Statistics on programmatic ads, MFA sites & ad spend leakage

  • In 2022, roughly 65% of programmatic ad spend reached publishers, about 32% went to known supply-chain fees, and only ~3% remained unattributable.(13)
  • For every $1 spent on programmatic advertising, $0.65 reaches real audiences, $0.32 goes to platform and supply-chain fees, and $0.3 is unattributed.(13)
  • In 2024, 88.2% of all ads in the US were projected to be purchased programmatically.(14)
  • MFA sites deliver 7% less overall attention on display ads and 28% less on video than other media(5)
  • Spending on MFA pages dropped from 15% in 2022 to 4% in 2024 MFA dropped 15% to 4%(6)
  • MFA websites represent 21% of programmatic web advertising impressions(6)

How MFA websites do real damage

Made-for-advertising sites represent one of programmatic’s most persistent problems. These sites drain budgets, deliver extremely low engagement rates, and still manage to look legitimate. Here’s how they operate:

  • Bot-inflated metrics that make placements appear high-traffic and valuable
  • Ad-heavy layouts that maximize revenue per visitor by displaying numerous ad units per page
  • Arbitrage economics allow MFA operators to profit by buying cheap traffic and selling expensive ad impressions

Even when traffic is technically valid, MFA sites and misaligned placements can severely worsen your effective return. A click from a bot farm and a click from someone reading listicles for rewards are both problematic, just in different ways.

Statistics on Connected TV (CTV) and video ad fraud

  • CTV advertising had an 18% global invalid traffic rate in Q1 2025(15)
  • CTV Invalid traffic was 24% during Q4 2024 Holiday season(15)
  • In 2024, 65% of all CTV fraud was attributed to bot fraud(16)
  • Roku devices had the lowest global IVT at 15%(17)
  • Samsung Smart TV devices have the highest rate at 31%(17)
  • 26% of all SSAI used for CTV programmatic advertising is deemed invalid(18)
  • Invalid traffic rates are 140% higher with Server-Side Ad Insertions (SSAI)(20)

The CTV Gold Rush for Fraudsters

Advertisers are shifting budgets to Connected TV, and fraudsters are following. With average CPMs ranging $25-$35(19) (significantly higher than most digital channels), CTV represents one of the most lucrative fraud targets today.

Connected TV lacks standard cookie-based tracking, making it harder to verify that ads reached real viewers. This opacity creates ideal conditions for fraud, and so we see bot fraud accounting for 65% of all CTV fraud.

Findings also suggest that Server-Side Ad Insertion (SSAI) has become the primary attack vector. While SSAI creates smoother viewing experiences, invalid traffic rates jump 140% higher when SSAI is present. Fraudsters spoof SSAI servers to generate fake impressions that appear legitimate, costing unprotected advertisers millions.

Statistics on positive click fraud numbers | What does good look like?

  • Advertisers with ad platform protection typically see around 11.5% invalid click rate (Google Ads)
  • Advertisers with no zero protection can expect much higher average invalid click rates
  • Well below average invalid click rate achievable with dedicated click fraud protection

Is it possible to have a 0% invalid click rate?

Unfortunately, it’s impossible to have 0% invalid click rates. Even with the most sophisticated fraud protection, some invalid traffic will always slip through because not all invalid clicks are malicious. There are accidental mobile taps, curious competitors manually checking your ads, and edge cases of legitimate users exhibiting bot-like behavior.

Additionally, fraudsters constantly develop new evasion techniques that haven’t been cataloged yet, and so, the fraud protection system isn’t yet looking out for them.

The goal of fraud protection is to minimize waste to levels that don’t materially impact your ROAS, not to achieve a theoretically perfect, but practically impossible zero.

Statistics on generative AI's impact on click fraud

generative ai click fraud stats
  • Generative AI-enabled scams rose by 456% between 2024 and 2025(9)
  • In 2024, deepfake attempts occurred every 5 minutes(10)
  • $12.3 billion in generative AI fraud losses in 2023(11)
  • 86% increase in General Invalid Traffic (GIVT) in H2 2024 due to AI crawlers(12)
  • 70% growth in GIVT rates in December 2024 vs. December 2023(12)

Generative AI fraud is bigger than ever

Search volume for “AI ad fraud” is skyrocketing, and the statistics reveal why. Generative AI has changed the fraud landscape, making it easier to power more sophisticated attacks. Even though it’s not marketed as such, fraudsters can basically employ them as a form of fraud-as-a-service and launch fraud on a massive scale, for as little as $20.

With deepfake, for example, attempts powered by the technology occurred every five minutes in 2024.

And beyond malicious deepfakes, AI has triggered an explosion in General Invalid Traffic (GIVT) through AI scrapers like GPTBot, ClaudeBot, and AppleBot. These bots scan the web to train large language models, inflating impression counts without human eyes ever seeing ads. While not inherently malicious like other kinds of fraud, AI scrapers can corrupt analytics data and create measurement challenges for advertisers.

Agentic browsers and fake traffic

A new category of AI-powered traffic is emerging: agentic browsers like Perplexity’s Comet and OpenAI’s ChatGPT agent mode. These AI-first browsers render webpages while interpreting content, executing tasks.

Research from Seer Interactive(21) and MarTech(22) shows that traffic from these agentic browsers often masks its origin, blending with direct traffic in Google Analytics, rather than appearing as a clear referral source.

For these browsers, the measurement challenge becomes identifying them from real users who can convert. The distinction matters for attribution, audience building, and campaign performance analysis.

Prevent click fraud with Fraud Blocker

prevent click fraud with fraud blocker

Screenshot of Fraud Blocker’s dashboard

The data is clear: ad fraud is a massive, growing problem that affects every advertiser regardless of budget size or industry. They represent real money leaking from your campaigns every single day.

The good news is that fraud mitigation platforms can help. 

Fraud Blocker protects over 4,500 websites and analyzes more than 500,000 unique IP behaviors daily, monitoring 60 million+ IPs and 20,000+ domains for fraudulent activity. Our solution offers real-time protection by tracking IP addresses, device and browser fingerprints, VPN/proxy use, click frequency, and a bunch of other signals, and then blocking invalid traffic, where detected, before it wastes your budget.

Start a 7-day free trial to see how much your actual invalid click rate is, and how Fraud Blocker can protect your campaigns.

Frequently asked questions

Estimates vary due to different definitions (narrow ‘ad fraud’ vs broader ‘invalid traffic’), different channels measured (programmatic display vs all digital), and different methodologies and time frames.

Ad fraud refers to intentional deception for financial gain (bots, click farms). Invalid traffic is broader, including accidental clicks, misattributed conversions, and non-human activity that may not be malicious but still wastes spend. Learn more.

Platforms like Google and Meta have built-in protections, but they catch only a portion of invalid activity. Independent studies consistently show additional invalid traffic slips through, which is why third-party tools exist.

Advertisers see an average of 11.5% invalid clicks in Google Ads. The numbers vary by industry, channel, and protection level. Without dedicated fraud protection, advertisers might see much higher invalid click rates.

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