/journey-design

name: journey-design
description: "Design cross-channel customer journeys as state machines — states, transitions, touchpoints, and personalization branches — then validate the design with Monte Carlo simulation via journey-engine.py before any build. Produces the journey map, touchpoint calendar, per-touchpoint content briefs, simulation results with bottleneck analysis, and a per-platform implementation checklist; it designs and simulates, it does not activate anything. Triggers on \"/digital-marketing-pro:journey-design\", \"map the onboarding journey\", \"design a win-back flow across email and ads\", \"plan the touchpoints after signup\", \"build a retention journey with branching\". Reads the brand profile, guidelines, and compliance rules, and flags content gaps needing new creation."

/digital-marketing-pro:journey-design

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"
• **Available channels**: The communication channels available for touchpoints — email, SMS, social media (organic and paid), in-app messaging, push notifications, direct mail, sales outreach, ads (retargeting and prospecting), webinars, or community. Only channels the brand has operational capability for should be included
• **Desired outcomes**: Measurable success criteria for the journey — primary conversion goal (e.g., "60% of trial users reach activation within 7 days"), secondary metrics (engagement rate, time-to-convert, drop-off rate per stage), and guardrails (maximum touches per week, minimum time between messages, unsubscribe rate ceiling)
• **Content assets available**: Existing content that can be used or adapted for touchpoints — blog posts, case studies, product demos, email templates, landing pages, videos, webinars, or documentation. Also note any content gaps that will require new creation
• **Journey duration (optional)**: Expected total timeline from entry to completion — e.g., "14-day onboarding", "90-day retention cycle", "30-day win-back window". If omitted, the system designs based on objective-appropriate defaults
• **Personalization signals (optional)**: Behavioral or demographic signals available for branching — product usage data, email engagement history, website behavior, purchase history, support ticket status, or NPS score. More signals enable more sophisticated branching logic

Process

1. **Load brand context**: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, tone, compliance rules (`skills/context-engine/compliance-rules.md`), industry context, and audience personas to inform journey design. Load guidelines from `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` if present — apply channel restrictions, frequency caps, and content standards. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults. 2. **Design journey state machine**: Define the journey states based on the objective. Each state represents a distinct phase the customer passes through — e.g., for onboarding: Welcome (day 0-1), Activation (day 1-3), First Value (day 3-7), Habit Formation (day 7-14), Advocate (day 14+). For acquisition: Awareness, Interest, Consideration, Intent, Evaluation, Purchase. Each state has entry criteria, exit criteria, and a maximum dwell time before escalation or alternative path triggers. 3. **Define transitions**: For each state-to-state transition, specify the trigger event (what the customer does or doesn't do that causes movement), transition probability (estimated likelihood based on industry benchmarks and brand data), timing window (how long the customer typically stays in the current state before transitioning), and fallback behavior (what happens if the customer doesn't transition within the expected window — escalate, retry, or move to an alternative path). 4. **Map touchpoints**: For each transition, design the specific touchpoint — which channel delivers the message, the content brief (what the message communicates and what action it drives), timing relative to the trigger event (immediate, 1 hour delay, next morning, etc.), and success criteria (what constitutes engagement with this touchpoint). Each touchpoint references available content assets or flags a content gap requiring new creation. 5. **Design branching logic**: Create personalization branches based on available signals. Engagement-based branches split on whether the customer interacted with the prev