decision-trees

name	decision-trees
description	Use when designing branching logic, eligibility rules, and fallback paths.

Personalization Decision Trees Skill

When to Use

• Planning logic for dynamic experiences across web, in-app, email, or sales plays.
• Auditing existing decision flows for complexity, coverage, or compliance gaps.
• Simulating new branches before deploying rule or model updates.

Framework

1. Objective Mapping – tie each node to business KPIs and user intents.
2. Signal Hierarchy – prioritize deterministic signals (consent, account tier, lifecycle) before behavioral or predictive ones.
3. Fallback Design – ensure every branch has a safe default when data is missing or risk flags appear.
4. Experiment Hooks – embed test slots at key decision points with guardrail metrics.
5. Monitoring – log path selections, success rates, and anomaly alerts for continuous tuning.

Templates

• Decision tree canvas (node, condition, action, fallback, owner).
• Signal priority matrix (signal → freshness → reliability → privacy risk).
• Simulation checklist (scenarios, expected path, validation steps).

Tips

• Keep trees shallow where possible; offload complexity to scoring models or external services.
• Version control decision logic alongside content assets for traceability.
• Pair with governance skill to log approvals for high-impact branches.

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