This case study walks through how a media buyer tackled a common problem: too much fraudulent traffic eating into their campaign budget. By properly configuring PopTrade's anti-fraud settings, they dramatically improved traffic quality without increasing spend.

The Problem

The buyer was running popunder campaigns targeting US desktop traffic. Despite decent impression volumes, they noticed several red flags:

Unstable conversion rates - CR fluctuated wildly day-to-day
High bounce rates - Many visitors left immediately without any interaction
Suspicious patterns - Clicks happening impossibly fast after page load
Geo mismatches - Traffic claiming to be from the US but behaving like it wasnt

The buyer suspected a significant portion of their traffic was fraudulent - bots, proxied users, or incentivized clicks that would never convert.

What They Did

Instead of simply blacklisting placements, the buyer took a systematic approach using PopTrade's Anti-Fraud Settings:

Step 1: Enabled Core Detection Rules

In the Antifraud Settings panel, they activated several key detection signals:

Time-to-Event (TTE) threshold - Blocked clicks happening faster than 500ms after page load. Real users need time to see and react to content.
Geo mismatch detection - Flagged traffic where the declared country didnt match IP geolocation data.
Device mismatch detection - Caught inconsistencies between reported device type and actual browser fingerprint.

Step 2: Adjusted Strictness Level

The buyer set their strictness to High which meant:

Lower fraud score threshold for blocking (more aggressive filtering)
Multiple signals checked in combination
Suspicious traffic rejected before it could generate billable impressions

Step 3: Added IP Blacklist

After reviewing their logs, they identified IP ranges associated with known data centers and proxy services. These were added to their custom IP blacklist.

Step 4: Enabled External Provider

For additional coverage, they connected IPQualityScore as an external antifraud provider, which added:

Proxy/VPN detection
Bot probability scoring
Device reputation data

The Result

After implementing these changes, the buyer observed significant improvements:

More stable conversion rates - Daily CR variance dropped dramatically, making optimization predictable
Lower bounce rates - Real users were actually engaging with landing pages
Better ROI - Same budget now reached more genuine users
Cleaner data - Analytics became trustworthy for making decisions

Importantly, this was achieved without increasing the campaign budget - the buyer simply stopped paying for worthless traffic.

Key Takeaways

Dont Just Blacklist - Configure

Blacklisting placements is reactive and slow. Proper antifraud configuration catches bad traffic from any source, including new placements you havent tested yet.

Combine Multiple Signals

No single fraud signal catches everything. The combination of TTE, geo mismatch, device mismatch, and external providers creates layered protection.

Start Strict, Then Loosen

Its better to be aggressive initially and miss some traffic than to let fraud through. Once youve established a quality baseline, you can fine-tune thresholds.

Monitor the Blocked Traffic

PopTrade shows you whats being blocked and why. Use this data to validate your settings are working correctly.

When to Use This Approach

This configuration strategy is particularly useful if youre experiencing:

Unexplained conversion rate fluctuations
Suspiciously high click rates with low conversions
Traffic that doesnt match your targeting parameters
Complaints from your affiliate network about traffic quality

PopTrades antifraud system is designed to be configured once and then work automatically. Take the time to set it up properly, and youll see immediate improvements in campaign performance.

Case Study: How a Media Buyer Reduced Fraud Traffic by Tuning Anti-Fraud Settings