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journey-design

Design cross-channel journeys as state machines, simulation-tested before build. "map the onboarding journey"

plugins/indranilbanerjee/digital-marketing-pro/skills/journey-design/SKILL.md

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# /digital-marketing-pro:journey-design

> **Script location.** If your host does not set `${CLAUDE_PLUGIN_ROOT}`, the scripts are in this plugin's `scripts/` folder, next to `skills/`. Run them with Python 3.10 or newer: `python`, or `python3` where `python` is not found (macOS, many Linux systems).

## Purpose

Design comprehensive cross-channel customer journeys as state machines. Define journey states (awareness through advocacy), transitions triggered by engagement signals, touchpoints with channel-specific content, branching logic for personalization, and simulate expected outcomes before launch. Turns abstract customer lifecycle stages into concrete, executable journey maps with specific content, timing, and channels at every step — then validates the design with Monte Carlo simulation before committing resources to implementation.

## Input Required

The user must provide (or will be prompted for):

- **Journey objective**: The primary goal this journey serves — acquisition (convert prospects to customers), onboarding (activate new customers to first value), retention (keep existing customers engaged and renewing), win-back (re-engage churned or lapsed customers), upsell (move customers to higher tiers or additional products), advocacy (turn satisfied customers into referrers and promoters), or a custom lifecycle stage
- **Target audience segments**: The specific audience segments entering this journey — defined by demographics, behavior, lifecycle stage, or prior engagement. Multiple segments supported with branching paths based on segment-specific behavior. E.g., "trial users who signed up from blog content", "enterprise accounts with 30+ seats approaching renewal", or "lapsed customers who churned in the last 90 days"