Hey fellow marketers,
Wanted to share one of my recent experiences in traffic arbitrage that delivered great results — thanks to smart tool selection, methodical testing, and consistent optimization.
Like many in this game, I’ve often battled two major pain points: low conversion rates and soaring ad costs. These can quickly eat into your ROI if you're not careful. I set out to build a better strategy using a combination of an ad network, CPA network, and a solid anti-fraud tool.
After reviewing several CPA networks, I settled on OfferGate — they’ve been reliable in terms of payments and offer variety. I chose a mobile app offer called VotTak, which had two payout models: one for app installs, and one for users who watch videos inside the app. This flexibility helped me fine-tune monetization for different traffic streams.
For traffic, I tested several networks but eventually chose Kadam, a well-rated source that supports global reach. I ran a popunder campaign worldwide to identify the best-performing GEOs without limiting myself upfront.
Within the first few days, some strong performers emerged: Iraq (IQ), Netherlands (NL), Turkey (TR), UAE (AE), and Iran (IR). IQ gave me the most volume and was relatively easy to optimize.
I paused low-performers (below -20% ROI), and let borderline ones (around -10% to -20%) continue while testing new landing pages.
As the campaign scaled, managing everything in one stream became messy. I split performing platforms into a dedicated flow and started running deeper tests.
I also introduced pre-landing pages. One of the best-performing pre-landers gave me 50%+ ROI, compared to the original one which only brought 4%. So yes — pre-landers made a huge difference.
Even with premium ad networks, fraud is inevitable. That’s where Kaminari (a fraud protection tool I tested) came in. It helped flag suspicious traffic sources — proxies, bots, users with spoofed devices, etc.
With the demo version, I was able to cut bad traffic early by running 50-100 clicks per publisher and evaluating traffic health before scaling. In most cases, fraud stayed under 20%, which is acceptable, but this tool definitely helped save budget.
Now that I’ve filtered the traffic and identified profitable segments, I’m scaling slowly — increasing bids and budgets by 10–20%. I also review traffic quality with the affiliate manager and request payout bumps on strong GEOs, which can add an extra 10–20% ROI.
This case proves that choosing the right stack — CPA network, traffic source, and anti-fraud tool — can dramatically impact your results. Testing patiently and optimizing based on data is what got me to over 50% ROI.
If you’re doing arbitrage, don’t just chase cheap clicks. Focus on the quality of offers, traffic, and tools — that’s where the real profit lies.
Hope this helps someone refine their own workflow!
Wanted to share one of my recent experiences in traffic arbitrage that delivered great results — thanks to smart tool selection, methodical testing, and consistent optimization.
Background
Like many in this game, I’ve often battled two major pain points: low conversion rates and soaring ad costs. These can quickly eat into your ROI if you're not careful. I set out to build a better strategy using a combination of an ad network, CPA network, and a solid anti-fraud tool.
Step 1: Finding the Right Offer
After reviewing several CPA networks, I settled on OfferGate — they’ve been reliable in terms of payments and offer variety. I chose a mobile app offer called VotTak, which had two payout models: one for app installs, and one for users who watch videos inside the app. This flexibility helped me fine-tune monetization for different traffic streams.
Step 2: Traffic Source Selection
For traffic, I tested several networks but eventually chose Kadam, a well-rated source that supports global reach. I ran a popunder campaign worldwide to identify the best-performing GEOs without limiting myself upfront.
Within the first few days, some strong performers emerged: Iraq (IQ), Netherlands (NL), Turkey (TR), UAE (AE), and Iran (IR). IQ gave me the most volume and was relatively easy to optimize.
I paused low-performers (below -20% ROI), and let borderline ones (around -10% to -20%) continue while testing new landing pages.
Optimization Process
As the campaign scaled, managing everything in one stream became messy. I split performing platforms into a dedicated flow and started running deeper tests.
I also introduced pre-landing pages. One of the best-performing pre-landers gave me 50%+ ROI, compared to the original one which only brought 4%. So yes — pre-landers made a huge difference.
Tackling Fraud
Even with premium ad networks, fraud is inevitable. That’s where Kaminari (a fraud protection tool I tested) came in. It helped flag suspicious traffic sources — proxies, bots, users with spoofed devices, etc.
With the demo version, I was able to cut bad traffic early by running 50-100 clicks per publisher and evaluating traffic health before scaling. In most cases, fraud stayed under 20%, which is acceptable, but this tool definitely helped save budget.
Next Steps and Scaling
Now that I’ve filtered the traffic and identified profitable segments, I’m scaling slowly — increasing bids and budgets by 10–20%. I also review traffic quality with the affiliate manager and request payout bumps on strong GEOs, which can add an extra 10–20% ROI.
Conclusion
This case proves that choosing the right stack — CPA network, traffic source, and anti-fraud tool — can dramatically impact your results. Testing patiently and optimizing based on data is what got me to over 50% ROI.
If you’re doing arbitrage, don’t just chase cheap clicks. Focus on the quality of offers, traffic, and tools — that’s where the real profit lies.
Hope this helps someone refine their own workflow!