Hello everyone, OfferGate here! We've launched the "$500 for a Case" campaign and are sharing our users' experiences on our blog. Below, you'll read a first-person story.
How It All Began
As someone actively earning from traffic arbitrage, I'm always on the lookout for new tools that can improve my results. Recently, I decided to conduct research to find new ad networks, CPA networks, and other tools for arbitrage. As a result, I decided to test a combination of three tools.
Almost every arbitrager faces the problem of low conversion rates and high advertising costs, which negatively impact profitability. Therefore, I set out to find a solution that would allow me to attract higher-quality traffic, monetize it effectively, and minimize fraud risks. Here’s what I discovered.
CPA Network — OfferGate
I thoroughly analyzed various CPA networks, compared offers, rates, and conditions, and chose OfferGate for this test. They've been in the market for 6 years, have plenty of offers, and I found no bad reviews about their payouts.
In their catalog, I selected VotTak from the mobile applications vertical. It turned out to be a good offer with decent rates. I also liked that it had two payment models: for installs and for video views in the app. This allowed me to choose the most suitable model depending on the traffic.
Ad Network — Kadam
After researching a plethora of ad networks, I chose the well-known and highly-rated Kadam network. I decided not to limit myself to a specific geo and launched an ad campaign worldwide to assess the potential. I chose the popunder ad format, as it's cheaper than in-app push.
After the first days of running the campaign and analyzing the statistics, clear winners emerged: IQ, NL, TR, AE, IR, and a few other geos. IQ particularly caught my interest as it provided the highest traffic volume and was relatively easy to optimize.
I immediately disabled platforms that were running at a clear loss (with an ROI below -20%). Platforms with slight losses of -10-20% ROI I decided to keep for now, thinking they might balance out later when we start experimenting with pre-landers.
I performed the same actions for other geos.
At some point, it became inconvenient to optimize everything in one stream, so I decided to separate the selected platforms into a distinct path. Thus, the path named Only VT was created. The screenshot shows where the general flow is and where the selected platforms are.
The screenshot also shows how the ROI fluctuates on different days, but the main thing is that we are in the black. This is important to consider when evaluating results, as you might disable a perfectly good platform in the heat of the moment. My personal recommendation is to evaluate based on larger data sets. We will increase ROI through pre-landers and further platform refinement.
Next, I tested landing pages. At the time of writing, some pre-landers were still being tested, but there were a few clear leaders with 50%+ ROI compared to the initial pre-lander with 4% ROI.
As a result, I expect further growth in ROI on positive platforms and a turnaround for platforms with negative ROI within reasonable limits.
Fraud Protection — Kaminari
Despite all the efforts of ad networks to combat fraud, I still encountered this issue in my campaigns. The problem lies not with the ad networks but with the platforms within them. Low-quality traffic sources affect the networks as much as they affect us. Here, I decided to use the demo of Kaminari, which provided protection and saved me budget on traffic acquisition. Using anti-fraud products is often overlooked by newbies but is crucial for success.
As for the fraud rate, it varies by platform, and rates up to 20% are normal. The screenshot shows that our rate does not exceed 20%. Kaminari also has a block for suspicious users that the system may consider fraudulent, depending on internal settings. For example, users with various proxies, anti-detect browsers, AdBlock, and other settings that can negatively impact traffic evaluation.
