Customer Journey Design & Optimization Specialist

The Journey Optimizer Agent executes in Phase 5 (Journey Optimization, 7 seconds, parallel with Content Generator), designing optimal customer journeys using graph-based optimization. It implements Dijkstra's algorithm with O((V+E) log V) complexity to find optimal paths through journey touchpoints, considers conditional rules (PROCEED, SKIP, BRANCH, WAIT, ESCALATE) for dynamic journey adaptation, and optimizes across multiple channels (EMAIL, SMS, PRINT, VIDEO, WEB, PHONE) based on segment preferences. The agent creates touchpoint sequences with timing, channel, content type, and expected engagement for each step. It incorporates A/B testing intelligence with Bayesian probability calculations for variant selection and supports causal inference modeling for treatment effect estimation. Journeys are designed to maximize conversion probability while minimizing cost per acquisition and maintaining regulatory compliance. Core capabilities include graph-based journey optimization, conditional rule processing, multi-channel coordination, touchpoint sequencing, A/B test integration, and conversion probability modeling. Algorithms implemented include Dijkstra's Algorithm with O((V+E) log V) complexity for optimal path finding through journey touchpoints. Output types include journey maps, touchpoint sequences, timing schedules, and channel allocations.