Hey everyone!
Wanted to share a real-world case study from my recent experience with traffic arbitrage. Like many in this space, I’ve faced the usual hurdles—low conversion rates, rising ad costs, and ever-lurking fraud. But after some persistent testing and tool-hopping, I found a winning combo that took my ROI to over 50%.
Here’s a full breakdown of what I did and learned along the way.
The core challenge? Getting traffic that converts without bleeding budget on poor-quality sources or fraud. My goal was to test a mix of tools that could improve traffic quality, optimize conversion potential, and reduce the risks associated with shady clicks.
I ended up combining three tools:
After thoroughly comparing offers, payout models, and reviews across CPA networks, I landed on OfferGate. They’ve got a wide catalog and, more importantly, a reliable reputation.
The offer I tested was in the mobile app vertical—specifically a VotTak campaign that had both install-based and engagement-based payout models. This flexibility gave me room to optimize based on the traffic type.
I tested a wide range of ad networks and finally settled on Kadam. I launched a global campaign using the popunder format—cheaper than push, and often just as effective for high-volume arbitrage.
After a few days, some clear GEO winners emerged: IQ, NL, TR, AE, and IR. Iraq (IQ) really stood out for its volume and optimization ease. I cut off underperforming GEOs and focused on platforms bringing a near-positive or break-even ROI, thinking I could swing them with further optimization.
Managing everything in a single stream was getting chaotic, so I segmented my top-performing sources into a separate flow—this made analysis and optimization way smoother.
Next up: pre-landing page tests. Some of the early versions had a disappointing 4% ROI, but after iterations, I identified a few pages pulling over 50% ROI. The boost was immediate and measurable.
Even with a reputable ad network, some traffic platforms had issues. To counter this, I tested out Kaminari’s anti-fraud tool. It helped identify red flags like proxy users, anti-detect browsers, and other shady setups.
Fraud stayed within acceptable limits (under 20%), and Kaminari’s filtering helped me avoid wasting budget on bad clicks. It also allowed for smarter initial testing—running 50–100 clicks per publisher and quickly identifying what was worth scaling.
With a strong pool of profitable platforms, I started optimizing bids and expanding budgets. I also worked with the CPA network to request payout bumps where quality was confirmed—another trick to squeeze 10–20% more ROI without changing the setup.
Ongoing analysis with Kaminari helped refine sources, and traffic volume scaled without a major drop in conversion quality.
This experiment proved that a strategic mix of tools—especially when carefully tested and optimized—can produce serious results in arbitrage. With the right CPA offer, a solid ad network, and proactive fraud management, I was able to take a basic campaign and turn it into a profitable machine.
If you’re struggling to hit consistent ROI, my advice: don’t underestimate the power of pre-landers, proper segmentation, and fraud filtering. The devil’s in the details, and the details do pay off.
Happy optimizing!
Wanted to share a real-world case study from my recent experience with traffic arbitrage. Like many in this space, I’ve faced the usual hurdles—low conversion rates, rising ad costs, and ever-lurking fraud. But after some persistent testing and tool-hopping, I found a winning combo that took my ROI to over 50%.
Here’s a full breakdown of what I did and learned along the way.
Starting Point: The Arbitrager’s Dilemma
The core challenge? Getting traffic that converts without bleeding budget on poor-quality sources or fraud. My goal was to test a mix of tools that could improve traffic quality, optimize conversion potential, and reduce the risks associated with shady clicks.
I ended up combining three tools:
- A solid CPA network
- A high-performing ad network
- A smart anti-fraud solution
CPA Network Pick: OfferGate
After thoroughly comparing offers, payout models, and reviews across CPA networks, I landed on OfferGate. They’ve got a wide catalog and, more importantly, a reliable reputation.
The offer I tested was in the mobile app vertical—specifically a VotTak campaign that had both install-based and engagement-based payout models. This flexibility gave me room to optimize based on the traffic type.
Ad Network: Kadam in Action
I tested a wide range of ad networks and finally settled on Kadam. I launched a global campaign using the popunder format—cheaper than push, and often just as effective for high-volume arbitrage.
After a few days, some clear GEO winners emerged: IQ, NL, TR, AE, and IR. Iraq (IQ) really stood out for its volume and optimization ease. I cut off underperforming GEOs and focused on platforms bringing a near-positive or break-even ROI, thinking I could swing them with further optimization.
Streamlining & Pre-Lander Testing
Managing everything in a single stream was getting chaotic, so I segmented my top-performing sources into a separate flow—this made analysis and optimization way smoother.
Next up: pre-landing page tests. Some of the early versions had a disappointing 4% ROI, but after iterations, I identified a few pages pulling over 50% ROI. The boost was immediate and measurable.
Tackling Fraud with Kaminari
Even with a reputable ad network, some traffic platforms had issues. To counter this, I tested out Kaminari’s anti-fraud tool. It helped identify red flags like proxy users, anti-detect browsers, and other shady setups.
Fraud stayed within acceptable limits (under 20%), and Kaminari’s filtering helped me avoid wasting budget on bad clicks. It also allowed for smarter initial testing—running 50–100 clicks per publisher and quickly identifying what was worth scaling.
Scaling the Success
With a strong pool of profitable platforms, I started optimizing bids and expanding budgets. I also worked with the CPA network to request payout bumps where quality was confirmed—another trick to squeeze 10–20% more ROI without changing the setup.
Ongoing analysis with Kaminari helped refine sources, and traffic volume scaled without a major drop in conversion quality.
Final Thoughts
This experiment proved that a strategic mix of tools—especially when carefully tested and optimized—can produce serious results in arbitrage. With the right CPA offer, a solid ad network, and proactive fraud management, I was able to take a basic campaign and turn it into a profitable machine.
If you’re struggling to hit consistent ROI, my advice: don’t underestimate the power of pre-landers, proper segmentation, and fraud filtering. The devil’s in the details, and the details do pay off.
Happy optimizing!