Player Segmentation: How to Reduce Bonus Waste in iGaming

Player segmentation is presented as the most effective method for reducing unnecessary expenditure on bonuses within iGaming. According to Ihor Sudak, CRM Operation Team Lead at GR8_TECH, segmenting the user base allows for promotions to be directed only at players with real potential for return, thereby decreasing exposure to fraud or abandonment. Utilizing advanced models like RFM(D) and integrated CRM tools supports this approach, optimizing every euro spent on marketing.

Player Segmentation in iGaming: Models and Approaches

Segmentation in the iGaming sector involves grouping players based on their activity, spending, gaming frequency, and demographic data. Platforms that include segmentation in their core system or CRM solution allow for the identification of groups with distinct needs and behaviors. According to Sudak, having segmentation, communication tools, and bonus management within a single platform accelerates responsiveness to behavioral changes, which is essential during intensive events like the World Cup.

Oleh Savka, Head of Product Retention & Engagement, points out that some operators still manage campaigns, messaging, and segmentation in separate systems—slowing operations down and complicating analysis. The integration of these processes provides a comprehensive view of the player and enables the triggering of relevant mechanics in real-time, keeping CRM, product, and risk teams aligned.

Benefits of Segmentation for Operators

Advanced segmentation is often not among the most visible selling points for platform providers, but its effect can be directly impactful on operating margins. The main benefits for casino and sports betting operators include:

• Brand Affinity: Tailoring recommendations, content, and marketing to detected preferences strengthens long-term relationships.
• Budget Optimization: Directing incentives only to valuable segments avoids low-return investments, enhancing campaign spending efficiency.
• Increased Retention and LTV: Identifying each user's activity status facilitates timely interventions and extends the player lifespan.
• Effective Cross-Selling: Identifying disinterested sportsbook players allows for the offering of simpler and more entertaining casino content.
• Fraud Reduction: Restrictions and verifications are assigned to high-risk users without penalizing valuable segments.

Practical Models: RFM(D), Risk Profiles, and Actionable Segmentation

The RFM(D) methodology, which evaluates Recency, Frequency, Monetary value, and Duration, helps isolate segments such as big spenders, players at risk of abandonment, and inactive users.

Examples of segments and recommended activities include:

• New Player: Offer onboarding and initial promotions.
• Active Spender: Maintain current-level retention actions.
• Active Loyal: Incentivize ascending to a higher segment.
• Active Engaged/Active: Suggest bonuses or related products to increase betting.
• Early Churner: Launch personalized reactivation campaigns.
• Churn/Lost: Analyze exit reasons and cease marketing to the irrecoverable.

Regarding risk, each user receives a status (Negative, Neutral, Positive, Premium) independently for casino and betting, defining bonus conditions, payments, and rules. Modern tools identify suspicious behavior before fraud occurs, allowing teams to apply personalized logic by vertical and adjust CRM and anti-fraud management.

"Without robust segmentation of crypto players, you could end up incentivizing fraudsters instead of legitimate users." — Artem Kolodyazhnyy, Head of Risk and Anti-Fraud Operations

Challenges: Data Quality, Updates, and Over-Segmentation

Despite the advantages, segmentation loses efficiency if:

• Data is incomplete or inconsistent, affecting the accuracy of insights.
• Player patterns change and the model takes time to update.
• Technology does not process real-time analyses or large volumes of data.
• Too many segments are created, complicating campaign activation and maintenance.

Recommended solutions include:

• Platforms that automatically clean and verify data, supported by machine learning and regular audits.
• Dynamic models that continuously recalculate segments based on changing deposits or interests.
• Integrated CRM tools that automate communication, bonuses, and analysis from a single interface.
• Focusing on broad and actionable segments by uniting groups with similar behaviors if they receive the same treatment.

Measuring Effectiveness: Operational and Engagement Metrics

Monitoring bonus expenditure is not enough; the most successful brands track results by segment and adjust their tactics based on data. Key metrics include:

• Open, click, and unsubscribe rates for messages.
• Relationship between total bonus amounts and deposits, number of active users with bonuses, and redemption rates per player.
• Percentage of users participating in gamification (stickers, achievements, quests), activations for giveaways or promotional pages.
• Retention, reactivation, and evolution of DAU/WAU/MAU.
• Finally, GGR, NGR, deposits, and withdrawals as indicators of the overall impact on the business.

"A profitable product can retain around 30% of its monthly base, while the rest are new sign-ups." — Ihor Sudak, CRM Operation Team Lead

Conclusion: Segment Before Overspending

High retention does not always depend on large investments but rather on allocating resources where they have the most effect. Segmentation, supported by reliable tools and continuous analysis, allows for maximizing the value of each player regardless of operator size. Advances in CRM platforms and leveraging models like RFM(D) make a difference, especially in markets where immediate ROI is necessary.

For updates on technology and CRM strategy, check the b2b section and sector news at news.