Previous practical analysis has mentioned that the initial deposit is always the core indicator determining the quality of deployment. Compared to registration or click volume, deposit is more directly related to platform revenue and player value, and is key to assessing whether traffic is truly effective.
In mature markets, the user decision cycle is longer, and there are more brand choices. In such an environment, the focus of deployment must be on improving conversion quality, optimizing around user behavior and traffic structure.
The following case is from the Portuguese market, promoting 22Bet through Popunder traffic. With an unchanged budget, it achieved an increase in net profit, which has certain reference value.
📱 Designing deployment around user decision behavior
In the early stages of the project, the pitcher promoted 22Bet on the localized site in Portugal. The platform has completed a comprehensive local adaptation, including Portuguese interface, sports betting categories, and a clear welcome bonus (100% welcome bonus).
In the pre-deployment data judgment, the Portuguese iGaming market is still in the growth stage, with both user scale and activity rising, and the brand also has a certain search and recognition foundation locally. These factors together constitute the basic conditions for deployment.
Under this premise, the first phase of deployment consumed $1,839, brought in $5,060 in revenue, and ultimately achieved a net profit of $3,221, with an ROI of 175.15%, showing stable overall performance.
Popunder, as the core form of deployment, was chosen based on user behavior judgment: iGaming users do not make a deposit immediately after clicking, but rather it is a decision-making process that takes time. Users usually browse the page, check the bonus, assess the platform's credibility, and then decide whether to deposit. Therefore, in this conversion context, Pop traffic can provide more sustained reach.
In terms of landing methods, the brand's official website was used directly, without adding a pre-landing page. When the brand already has local recognition, reducing the jump path can reduce loss, while strengthening users' trust in the platform, thereby improving conversion efficiency.
🔴 Choosing CPM over CPC in the billing model is essentially to adapt to this delayed conversion behavior. Compared to CPC, CPM is more conducive to controlling test costs and can extend the observation period, thus more completely assessing the real value of the traffic. Meanwhile, the deployment focused on mobile devices, as mobile devices are the main source of traffic in this market.
In the deployment execution phase, the initial bid was set at $1 CPM, and a complete data tracking system was established using Keitaro's self-hosted ad tracker. Through tracking parameters, it is possible to clearly break down each piece of traffic's source, ad placement, and conversion performance. From the backend data, there are clear differences between different scenarios, which also provides direction for subsequent optimization.
In terms of budget control, a daily limit of $150 was set, rather than concentrating consumption in a short period. This practice allows traffic to continue entering throughout the entire cycle, giving users enough time to complete decisions, and also makes the data more continuous and stable.
As data gradually accumulated, the project entered the optimization phase. From the backend, it is clear that although some ad placements generated consumption, they did not bring conversions, while others continued to contribute deposits.
Specifically, after a period of time, it is possible to block ad placements that continue without conversions, reduce the weight of poorly performing traffic, and increase the bid for ad placements that have been proven effective. Through Custom Bid, the bid for quality traffic was raised to $0.2–$0.4, thus obtaining more stable display opportunities.
After this round of optimization, the project accumulated 97 registrations and 23 deposits, and conversions began to stabilize gradually.
📱 Identifying high-value users from the data
After the first phase ended, the pitcher did not continue to expand the original deployment, but further broke down the data. In the analysis process, it was found that the average player value of iOS users was significantly higher than other devices, exceeding $600. This difference became a key basis for subsequent optimization.
Based on this discovery, the pitcher communicated with the alliance, ➡️ raising the payout for iOS from $220 to $320, while establishing a separate iOS deployment activity and excluding iOS traffic from the original activity to avoid interference between different devices. The core of this adjustment is to separate high-value users from the overall traffic and focus on amplifying them.
🔴 In the iOS-exclusive deployment, the bid was raised to $1.2 CPM, and Tablet traffic was introduced to expand the volume. The overall optimization method remained consistent, continuing to monitor data, filter, and clean up inefficient ad placements.
Ultimately, this phase achieved 16 registrations and 9 deposits. Compared to others, iOS users in this market showed significantly stronger deposit performance, further verifying the effectiveness of the device separation strategy.
Overall, the key to the 22Bet case lies in the continuous optimization of the deployment structure. With no significant increase in budget, the first phase achieved a net profit of $3,221, and the second phase further enhanced user value.
It has been proven that through device separation and traffic stratification, mature market deployment can also be transformed into stable revenue. In the current iGaming deployment environment, optimizing around user value has also become a more certain growth method.
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