In the iGaming industry, the First Time Deposit (FTD) has always been a core indicator determining the quality of platform revenue. Compared to frontend data such as registration volume and click-through rate, FTD is directly linked to the platform's cash flow and user Lifetime Value (LTV), and is key in assessing the efficiency of ad placements and product reception.
As competition in the iGaming industry market intensifies and traffic costs continue to rise, in many mature or semi-mature markets, strategies solely relying on "buying large volumes to gain registrations" are no longer sustainable for profitability. More platforms are shifting their focus towards optimizing "registration to deposit" conversions, fine-tuning strategies around user behavior, traffic structure, and placement tactics.
The following case study is from a long-term marketing manager responsible for the European market, who achieved a doubling in the number of first-time deposits in the Romanian market through systematic optimization, offering valuable insights.
💵 Limited budget, data analysis under conversion delays
Maria Casino (https://www.mariacasino.com/) primarily targets local players in Romania, often using Popunder ads (a type of ad that opens a new window in the background when a user clicks on a page, which the user sees only after switching or closing the current page), deployed through CPM traffic. The overall budget is controlled at $3,000 per month, with a target CPA ceiling of $72, ideally within $40, and a minimum deposit threshold for players set at $100.
In the initial phase, the project had about 42 first-time depositors per month, stable but lacking growth momentum. Meanwhile, fierce competition in the market, rising ad space prices, and long data feedback cycles (about 28–30 days), lacking real-time S2S tracking capabilities, resulted in significantly delayed optimization decisions.
The project faced triple pressures: 🔴 limited budget, incomplete data, and long conversion cycles.
Data analysis showed that only a few ad spaces generated registrations, while the rest of the traffic, despite having clicks, did not result in effective conversions. From a traditional advertising effectiveness perspective, such traffic usually needs to be quickly eliminated.
➡️ However, in the iGaming industry, this cannot be generalized. In the actual scenario of online casinos, user behavior generally shows significant delay characteristics.
Because many players, after registering, will first enter an observation phase, including browsing casino content, evaluating the platform, etc., which can last for days or even weeks.
Many public data in the industry also support this conclusion, especially in the European market, where some platforms have a median conversion cycle from registration to first deposit between 3–7 days, with long-tail users extending to more than 14 days. Short-cycle data is insufficient to fully reflect the true value of traffic.
Based on this understanding, the project did not adopt an aggressive traffic cleaning approach in its optimization strategy, but instead focused on "delayed conversion behavior" for strategic optimization.
💵 Filtering traffic and optimizing placement structure
Initially, there was a clear budget front-loading issue, such as spending too quickly in the first few days, resulting in a lack of continuous exposure later. 🔴 After optimization, a "full-cycle even distribution" strategy was adopted, splitting the budget into hourly settings each day to ensure a steady supply of traffic throughout the month.
The core value of the adjustment lies in providing a time window for delayed conversion data, which also enhances data continuity, making subsequent data analysis more meaningful.
Then, by cross-analyzing click and deposit times, it was found that the early morning hours had higher click volumes, but deposit behavior was lower compared to some specific periods, a phenomenon evident in multiple markets.
Therefore, in the optimization strategy, 🔴 try to reduce the exposure weight of low-click and low-payment intention periods, focusing the budget on evenings or weekends with high activity. After adjustment, the overall conversion rate showed significant improvement.
Subsequently, a tiered bidding strategy was introduced, using price as a tool for filtering traffic, 🔴 reducing the budget for ads with high clicks but low registrations, maintaining them in a test state; increasing bids for ad spaces that had generated registrations and deposits; keeping the middle layer of traffic unchanged, continuously observing conversion potential.
This strategy avoids the limitations of "binary filtering," making the traffic structure flexible. In later data, some low-cost traffic gradually converted into effective users after a delay.
🔴 Finally, the traffic cleaning cycle was extended to four weeks, only eliminating ad spaces that had long-term no registrations or deposits. Compared to short-cycle optimization, this retains potential users more effectively.
After a complete optimization cycle, the project's core indicators showed significant improvement: with the same budget of $3,000, the number of first-time depositors per month increased from 42 to 93; CPA decreased to $32.5; monthly profit from $5,700 to $11,100.
The case of Maria Casino reflects an important trend in iGaming placements—➡️ optimizing based on user behavior is more effective than simply filtering by time periods and channel paths.
In an environment of continuous industry saturation, single-dimensional optimization is no longer sufficient to support traffic development. Only by matching placement strategies with users' actual behavior, grasping different market user first deposit behaviors supplemented by targeted testing and optimization strategies, can the platform's traffic operation capabilities be gradually enhanced.
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