Predictive intent and value
Score likely conversion, bounce risk, and potential value while the session is live.
Decisioning
Convertive Decisioning
Move from static rule priority to ranked in-session decisions. Convertive combines predictive modeling, context signals, and learning loops to select the next best action moment by moment.
Action ranking layer
Choose one best action among competing options to reduce noise and improve conversion quality.
Continuous learning loop
Use outcomes to update policy and improve intervention quality over time.
Where teams apply the models
- Propensity-based intervention timing
- Offer aggressiveness by risk and value segment
- Recommendation relevance weighting by in-session context
- Holdout-aware policy evaluation for incremental lift
- Journey-safe suppression and fallback logic
- Adaptive strategy updates from observed outcomes