Decisioning Engine
The Decisioning Engine is where Appice determines what should happen for each customer signal. It evaluates rules, segments, propensity scores, and context — and outputs a next best action in real time.
What this enables
The Decisioning Engine allows you to move from manual, scheduled decisions to real-time, signal-driven decisions. Instead of building a campaign for a segment and firing it on a date, you configure logic that runs automatically the moment relevant signals arrive.
Outcomes you can achieve:
- Respond to fraud signals, churn signals, and conversion signals within milliseconds
- Surface the right offer to the right customer at the exact moment of intent
- Apply risk rules and compliance guardrails automatically — without manual review
- Ensure every decision is logged, explainable, and auditable
- Run A/B experiments on decisioning logic without rebuilding campaigns
Where it fits: Sense → Decide → Act → Learn
How it works
When a signal arrives, the Decisioning Engine processes it through a decision tree of configured logic:
The event arrives enriched with the customer's golden record — transaction history, segment membership, propensity scores, and recent interactions. The engine has everything it needs immediately.
The engine checks the signal against your configured decision rules. Eligibility conditions, suppression rules, frequency caps, and priority logic are applied in sequence.
If the signal passes all conditions, the engine selects the next best action — which offer, which message, which channel, which timing — based on your configured logic and AI recommendations.
The decision is recorded with full context — why it was made, which rules fired, what the score was. This forms the audit trail. The execution layer then fires the action.
Features
Configure if-then logic that evaluates signals against customer attributes, events, scores, and segment membership. Supports complex boolean conditions and nested logic.
Define dynamic segments based on real-time attributes, behavioural patterns, and predictive scores. Customers move in and out of segments automatically as their signals change.
AI-generated scores for churn risk, conversion likelihood, fraud risk, and next product propensity — applied automatically at decision time without a separate ML pipeline.
When multiple actions are eligible for a customer, the engine selects the highest-priority action using your configured ranking logic or AI optimisation.
Prevent over-communication and conflicting actions. Define per-customer, per-channel, and per-decision-type caps that are enforced automatically at decision time.
Every decision is recorded with: the signal that triggered it, the customer context at that moment, the rules that fired, the action selected, and the outcome. Full regulatory traceability.
Run controlled experiments on your decision logic — test two different rule sets, two different offers, or two different next best actions — with outcome measurement built in.
Configure signal-driven multi-step flows where each subsequent step is triggered by the customer's response to the previous action — not by a timer.
What comes next
Once the Decisioning Engine determines the next best action, it passes the decision to the Execution Layer (Act) — which fires the action across the relevant channels and systems.