CRM, Retention & VIP
Churn Analytics & Prediction
Models that flag players likely to churn early enough for CRM to act, along with the reasons behind the risk

CRM, Retention & VIP · Segmentation & Predictive Models
Uplift models that separate players who return because of an offer from those who would have played anyway
Many bonuses go to players who would have deposited without them. We build uplift models from past campaigns and controlled tests to estimate which players respond to offers, which respond to content and which need no prompt at all. The aim is to cut wasted bonus spend and avoid aiming incentives at players whose play is already high.
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CRM, Retention & VIP
Models that flag players likely to churn early enough for CRM to act, along with the reasons behind the risk
CRM, Retention & VIP
Recency, frequency and value segmentation adapted to gaming, with product mix and risk indicators layered on top
CRM, Retention & VIP
Early predictions of player lifetime value that help CRM, VIP and acquisition teams decide where effort is worth spending
CRM, Retention & VIP
Decision logic that chooses the most useful message for each player, including the option of sending nothing at all
CRM, Retention & VIP
Recommendation models that suggest slots and table games each player is likely to enjoy, across email, push and the lobby
CRM, Retention & VIP
Profiles of each bettor's sports, leagues, teams and bet types that power relevant fixture and odds content in CRM