By Eberhard Dürrschmid, CEO, Golden Whale
Incentives have always been one of the most powerful tools in iGaming. Bonuses, free spins, loyalty rewards; they’re the mechanisms that attract players, sustain engagement and build loyalty over time. But they’ve also been one of the most resource-intensive parts of an operator’s business. Campaigns take time to plan, test, and refine, and results often depend as much on instinct as they do on insight. That’s now changing.
What was previously only available as part of complex, high-cost enterprise systems is now accessible to operators of all sizes, ready to integrate directly into modern iGaming tech stacks with minimal overhead. As a result, the next generation of machine learning models is reshaping how incentives are created and deployed. These models allow operators to move beyond static, broad-brush campaigns toward personalised, adaptive systems that learn continuously from real-time behaviour.
But this shift goes far beyond operational efficiency. As AI and ML become embedded within live operations, they are fundamentally changing how operators engage players: with greater relevance, more sustainable incentives and a more responsible, player-aligned approach to retention.
From reactive to proactive incentives
For years, operators relied on a scattershot strategy: test many offers, track short-term results and scale what works. While workable, this approach is inefficient and often inconsistent. Incentives are issued broadly, costs escalate quickly and player responses vary widely.
Machine learning changes that equation. Modern models can interpret vast amounts of behavioural data, from game activity and deposit history to session timing and past responses and identify the precise moment and type of incentive most likely to motivate a player. What was once a multi-dimensional optimisation problem far too complex for manual CRM teams is now handled with speed and accuracy by learning systems.
Real-time incentive intelligence
This approach is central to BonusPilot, a recently added feature within Golden Whale’s Foundation platform. BonusPilot is designed to sit on top of any system configuration and provide real-time, individualised incentive recommendations powered by continuous learning.
Rather than relying on historical averages or static segments, it analyses the full breadth of live behavioural data across games, campaigns and CRM activity. With this insight, it determines when to start, stop, increase or reduce incentives – and importantly – which type of reward will have the greatest impact.
Whether that’s bonus funds, free spins, loyalty coins or another incentive within an operator’s inventory, BonusPilot adapts recommendations to each player’s lifecycle and engagement style.
Continuous learning
One of the most powerful aspects of BonusPilot is its integration with Golden Whale’s proprietary LOOPS architecture: a continuous feedback system that recalculates and refines decisions based on the most recent data. Every incentive interaction generates new insight, which immediately informs the next recommendation.
This creates a self-sustaining learning cycle: new incentives drive new behaviour, which produces new data, which then refines future incentives. BonusPilot’s guidance modules can also identify signs of bonus abuse, automatically limiting or halting offers to protect operational integrity.
Responsible engagement
A key part of Golden Whale’s development philosophy is ensuring that AI-driven tools support responsible play. BonusPilot incorporates multiple guardrails, both within Foundation and at operator level, to ensure incentives remain aligned with the engagement methods an operator defines. Operators therefore retain high retention levels, without compromising their duty of care.
Smarter incentives, less work
By automating much of the complexity behind incentive management, BonusPilot allows CRM and data teams to focus on strategy rather than repetitive execution. Campaigns can be created and adjusted with far greater speed, and operators maintain full transparency over how and why incentives are being distributed.
The results are clear: increased operational efficiency, more relevant player experiences, and incentive strategies that adapt as behaviour changes. Early operator deployments show that dynamic, data-driven incentives consistently outperform fixed, scheduled campaigns – not only in participation rates, but in sustained activity and long-term value.
Effective engagement isn’t about issuing more offers; it’s about issuing the right offers. BonusPilot enables operators to do exactly that – using real-time intelligence to improve performance at scale without adding operational pressure.
