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Protect 60-80% of revenue. Predict churn. Personalize retention. Increase LTV by 30-50%.
Real-time modeling of VIP churn propensity using spending, engagement, behavioral trends
AI recommends tailored bonuses, comps, and experiences aligned with VIP preferences
Augments human managers with data, insights, and recommended actions for each VIP
Continuous tracking of activity, satisfaction signals, and competitive threats
Multi-touch orchestrated outreach to lapsed VIPs with compelling re-engagement offers
Continuous measurement of VIP relationship strength and intervention effectiveness
Segment high-value players by LTV, behavior, tier classification
Continuous engagement tracking, satisfaction signals, competitive threats
Real-time churn risk scoring; identify players at critical risk
Recommend tailored offers, events, messaging aligned with preferences
Proactive outreach at optimal timing with compelling retention offers
Measure retention effectiveness; retrain on outcomes; improve strategies
Orchestrated campaigns for lapsed VIPs with re-engagement incentives
Increase LTV through exclusive experiences, events, personalized recommendations
Rapid drop in deposit frequency, bet size, or total spend vs. baseline
Decreased login frequency, session duration, or game activity
Shift to competitor platforms detected via competitive intelligence
Support complaints, dispute escalations, or complaint frequency
Lack of response to personalized offers vs. historical responsiveness
Mention of competitors, comparison of odds, or explicit switching signals
Define VIP segments; analyze churn patterns; map satisfaction drivers
Build churn prediction models; validate against historical data
Deploy on pilot VIP segment; measure churn reduction & LTV impact
Full deployment; integrate with CRM, account management; train managers
Monitor churn rates; retrain quarterly; expand to new segments
Predict churn. Personalize retention. Increase LTV by 30-50%. Defend against competitive poaching.
Schedule a Demo →Our models achieve 85-95% AUC on VIP churn prediction. Accuracy varies by VIP segment: high-value whales are most predictable (90%+ AUC), newer VIPs less so. We focus on ranking VIPs by risk rather than binary churn/no-churn.
We use historical propensity modeling: analyzing VIPs past responsiveness to specific offer types, game recommendations, events, messaging. Machine learning predicts offer response rates by type and personalization.
Yes. We optimize comp levels to maximize retention while preserving margin. Models balance: VIP risk of churn, profitability impact, comp effectiveness, and competitive positioning.
Competitive intelligence via: signup data, shared players, social listening, forum mentions, and behavioral signals (reduced play, testing competitor platforms). AI flags suspicious behavior suggesting competitive interest.
Win-back campaigns use multi-touch orchestration with compelling re-engagement offers. Models predict optimal timing and messaging. Historical data shows 20-30% of lapsed VIPs can be re-engaged.