Click fraud reporting and analysis: Proven detection, reporting, and prevention strategies for 2025

Juniper Research forecasts merchant fraud losses will exceed $362 billion globally between 2023 and 2028. Losses in 2028 alone will hit $91 billion.

These figures show why click fraud reporting and analysis are vital to track threats and cut losses.

Online marketing has become one of the most vital ways for businesses to gain new customers.

This guide covers click fraud reporting and analysis, detection, and prevention methods used by top advertisers.

What is click fraud, and why is it costing advertisers billions?

Click fraud is the fake generation of ad clicks. They come from competitors, dishonest publishers, or bots. These clicks hold no value for advertisers.

Significant sources of click fraud:

1. Bots and automated scripts:

These are application pieces programmed to simulate human behaviour in interacting with advertisements.

2. Click farms:

Low-cost operations where individuals receive payment to click on ads repeatedly.

3. Competitor sabotage:

Your competitors may repeatedly click on your ads to drain your PPC budget.

4. Ad fraud networks:

Organized processes typically involve malware or botnets to simulate legitimate traffic.

5. Unethical publishers:

People are clicking on their sites or apps themselves to artificially inflate earnings.

The real-world cost of click fraud

Below are the real-world costs of click fraud

1. Wasted Ad budget

The most immediate impact of click fraud is financial. In 2023, advertisers lost about $84 billion to digital ad fraud.

That was 22% of all online ad spending. For small and medium businesses, even small levels of fraud can significantly impact marketing efforts.

2. Distorted performance metrics

Click fraud inflates CTR, CPC, and impressions without boosting conversions or ROI.

3. Quality score penalties

In systems like Google Ads, when click fraud results in low user interaction, your ad’s Quality Score will suffer.

The result of this is higher costs and lower placement.

4. Brand reputation risks

Scammers may redirect traffic to malware sites, damaging your brand by association.

How click fraud works: A brief breakdown

To understand the behaviour of click fraud, compare their behaviour to genuine user interaction:

1. Session duration:

• Real user: Typically stays for 60–180 seconds.
• Click fraud: Stays for only 1–5 seconds.

2. Pages visited:

• Click fraud: Visits only 1 page (landing page).
• Real user: Visits 2 to 4 pages on average.

3. Scroll/Mouse Movement:

• Click fraud: Has no movement or displays pre-programmed patterns.
• Real user: Displays natural, random scrolling and cursor movement.

4. Conversions:

• Click fraud: May not convert at all.
• Real user: May sign up, purchase, or take another desired action.

5. Geolocation:

• Real user: Comes from targeted regions set in your ad campaign.
• Click fraud: Often originates from high-risk or unexpected zones.

Detecting click fraud

Ways to detect click fraud include:

1. IP Analysis and tracking:

Rapid, repeated clicks from the same IP with no real interaction signal are click fraud.

Tools that enable:

• Google Ads (shows fake clicks)
• ClickPatrol (auto-blocks)
• Server logs via Apache or Nginx

2. Device and browser fingerprinting:

Bots repeatedly use the same device/browser combinations.

Unusual traffic patterns by the same user-agent strings or legacy browsers signal an alarm.

3. Behavioural analytics:

High bounce rates, short visit times, and little engagement are all typical of fake clicks.

Top indicators:

• Bounce rates above 85%
• Time on page is less than 5 seconds
• Clicking ads repeatedly and not visiting other pages

4. Geographical discrepancies:

Suppose your campaign is geo-targeted to London, but 40% of the clicks are from Indonesia; it is click fraud.

5. Heatmaps and session recordings:

Devices, like Hotjar and Crazy Egg, allow you to view user activity.

Click fraud typically does not show scrolling, hovering, or interaction.

Case study

In May 2025, Hyderabad-based beauty brand Old School Rituals (OSR) was hit by fake Google Ads clicks. In just 48 hours, hackers took over their ad account and placed unauthorized ads for American-based brands.

These ads racked up 2.1 million clicks, which charged the company ₹12.7 crore (about USD 1.5 million), 850 times their typical daily ad expense.

Despite this traffic spike, there were no conversions, raising red flags immediately. Their online advertising firm caught wind of the suspicious click activity and reported it.

OSR reported the incident to the Telangana Cyber Security Bureau and cooperated with Google to probe and recover the money.

The experience has since been an example of grand ad fraud and the importance of account safety and click monitoring.

How major Ad platforms detect and refund fraudulent clicks

Learn how to detect and refund click fraud.

Use built-in tools and support channels on Google, Meta, Microsoft, and more.

1. Google:

Google uses filters, anomaly detection, and machine learning.

They spot invalid traffic from bots and click farms before you are billed.

Clicks flagged after billing are reviewed, and credits are applied where appropriate.

Advertisers can request investigations with click IDs, timestamps, and server logs.

2. Meta:

Meta tracks click patterns, pixel events, device IDs, and placement quality to spot fake or accidental clicks.

Many invalid clicks are filtered automatically.

Advertisers can appeal charges with data, logs, and proof of poor placements.

3. Microsoft:

Microsoft runs a dedicated click quality team alongside automated detection tools.

They monitor IP ranges, device fingerprints, and publisher networks to remove fraudulent clicks pre-billing.

Advanced click fraud analysis: AI, Heatmaps, and behavioural tracking

These models adapt quickly, learning from new fraud tactics without waiting for manual rule updates.

1. ClickPatrol’s AI uses machine learning on billions of click patterns.

It identifies anomalies such as fast clicks, mismatched locations, or device fingerprints in real time.

2. Heatmaps reveal exactly where users click on a page.

Genuine visitors interact with buttons, menus, or product images.

Fraudulent clicks cluster in odd spots or follow random, repetitive patterns.

3. Behavioral tracking records time on site, mouse movement, scroll speed, and navigation flow.

This data is cross-checked with click IDs and device details. Advertisers can then flag suspect traffic.

They can also block it before they spend more.

Analyzing click fraud data: A step-by-step guide

Understand how to spot patterns. Identify anomalies.

Analyze click fraud data with this step-by-step guide.

Step 1: Data aggregation

Gather logs from:

a) Ad platforms (e.g., Google Ads, Facebook)

b) Analytics tools (e.g., Google Analytics 4, Mixpanel)

c) Web servers (e.g., Apache, Nginx)

d) Click fraud software APIs

Step 2: Clean the data

a) Remove test/internal IPs

b) Filter known bots (Googlebot, Bingbot)

c) Normalize timestamp and user-agent formats

Step 3: Segment and compare

Segment by:

a) Device

b) Browser

c) Country

d) Session duration

e) Conversion status

Step 4: Apply anomaly detection

Use statistical and machine learning methods:

a) Z-Score Analysis to flag outliers

b) Isolation Forests for anomaly detection

c) K-Means Clustering for traffic grouping.

Preventing and mitigating click fraud

Discover practical strategies and tools to prevent and minimize the impact of click fraud on your digital ad campaigns.

1) Use anti-fraud tools like ClickPatrol.

ClickPatrol offers real-time blocking and detection. Many also auto-sync with Google Ads and WordPress.

2) Geo-target wisely: Avoid targeting high-fraud locations unless unavoidable.

Use Geo-blocking or bid adjustments in Google Ads.

3) Use IP exclusions directly in Google Ads or use server-level firewalls.

4) CAPTCHA Implementation: Use CAPTCHA on key pages to deter bots from emulating conversion behaviour.

5) Conversion-based optimization: Optimize for conversions, not clicks.

Fake traffic rarely converts.

6) Take advantage of retargeting: Use retargeting from known visitors.

It reduces fraud risk since the audience is pre-qualified.

Guarding your Ads against click fraud

Click fraud remains a serious challenge for online advertisers, draining budgets and distorting campaign data. Fraud tactics keep evolving.

Stay ahead with behavioral analysis, trusted detection tools, and quick action on anomalies. Platforms like ClickPatrol, CHEQ, and advanced analytics can help safeguard your campaigns.

Focus on real user engagement, apply IP filters. Optimize for conversions, not just clicks, to boost performance and cut risk.

Protect your ads, act now!

FAQs

Q. 1 How can I tell if click fraud affects my ad campaigns?

Look for extremely high click-through rates with no conversions, brief stays, and visits from strange locations.

Q. 2 What tools are used to detect and filter out click fraud?

Tools like ClickPatrol, CHEQ, TrafficGuard, and Google Ads click fraud reports are used to detect and filter out click fraud.

Q. 3 What do I do once I have detected click fraud?

Report them, block IPs, review logs, pause the campaign when needed, and optimize targeting.

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