About Client
The client is a globally recognized iGaming operator headquartered in the United Kingdom, with a strong presence across Europe, Asia, and other regulated markets. Their portfolio spans sportsbook, casino, and digital gaming channels, supported by both online and offline touchpoints. With millions of active players and high competitive pressure, even marginal improvements in retention have a meaningful impact on revenue and profitability.
Background
Player acquisition in the iGaming industry is expensive and increasingly competitive. Operators must navigate regulatory requirements, ensure seamless KYC and payment verification, and deliver a consistently engaging experience across devices and channels. Despite these efforts, a large percentage of players drop off at various stages—during onboarding, after initial deposits, or following short periods of inactivity.
Retaining players is therefore a critical business metric. However, effective retention requires more than generic bonuses or mass campaigns. It depends on understanding individual player behavior, identifying early churn signals, and delivering personalized interventions at the right time.
Modern iGaming analytics enables operators to analyze behavioral, transactional, and engagement data at scale. When combined with machine learning, this data can reveal patterns that are not visible through traditional reporting. For the client, the goal was to move beyond descriptive analytics and adopt a predictive approach that could actively guide retention and CRM strategies.
Challenge
The client faced several interconnected challenges:
- High player churn rates: A significant portion of players disengaged shortly after onboarding or during early stages of activity, reducing lifetime value and increasing reliance on costly acquisition.
- Limited early visibility into player value: The organization lacked reliable methods to identify high-potential and VIP players early in their lifecycle, resulting in missed opportunities for targeted retention.
- Siloed analytics and CRM execution: While player data existed across systems, insights were not seamlessly integrated into CRM workflows. This made it difficult to run effective campaigns or measure marketing efficiency.
- Need for scalable personalization: With millions of players across markets, manual segmentation and rule-based targeting were no longer sufficient.
The client required a solution that combined predictive analytics iGaming CRM integration with operational usability for marketing and retention teams.
