--- name: customer-experience-marketing description: "Orchestrate personalized, real-time customer experience marketing across all touchpoints using behavioral triggers, lifecycle stages, and predictive scoring. Use when building journey orchestration, setting up behavioral triggers, creating lifecycle-based messaging, or implementing real-time personalization engines. Triggers on phrases like 'customer journey orchestration', 'behavioral triggers', 'real-time personalization', 'lifecycle marketing', 'cross-channel journeys', 'next best action', 'journey mapping', 'personalization engine', 'trigger-based marketing', 'omnichannel experience'." --- # Customer Experience Marketing Orchestration Design and execute real-time, behaviorally-triggered marketing journeys that adapt to each customer's actions, preferences, and lifecycle stage across all touchpoints. ## Workflow ### Phase 1: Journey Architecture 1. **Map customer lifecycle stages**: - Awareness: first-time visitors, content consumers, social followers - Consideration: trial users, demo bookers, comparison shoppers - Activation: new sign-ups, first-value users, onboarding customers - Retention: active users, subscribers, repeat purchasers - Expansion: upgrade-ready, cross-sell targets, power users - Advocacy: NPS promoters, referral sources, community leaders - At-risk: declining engagement, support escalation, price-sensitive 2. **Define behavioral triggers**: - Website: page views, content downloads, pricing page visits, feature deep-dives - Product: feature adoption, usage frequency, power feature unlock, inactivity - Support: ticket submission, CSAT response, escalation, knowledge base usage - Email: open, click, forward, reply, unsubscribe - Social: engagement, follower, content share, comment - Transactional: payment success/failure, subscription change, contract milestone 3. **Design journey paths**: - Primary journey per lifecycle stage (default path) - Branching logic based on behavior (if X then path A, else path B) - Exit criteria (customer moves to next stage, churns, or becomes advocate) - Max frequency caps (prevent channel fatigue) ### Phase 2: Personalization Engine Configuration 1. **Customer data platform (CDP) integration**: - Unify customer identity across all data sources - Build real-time customer profiles with behavioral history - Calculate dynamic segments and predictive scores - Maintain data quality and consent management 2. **Next Best Action (NBA) engine**: - Machine learning model scoring optimal action per customer - Action types: email, SMS, push notification, in-app message, offer, content recommendation - Constraints: frequency caps, channel preferences, suppression lists, business rules - Real-time decisioning (<100ms response time) 3. **Personalization layers**: - Content personalization: dynamic content blocks based on persona, behavior, industry - Offer personalization: tailored discounts, upgrade paths, feature recommendations - Experience personalization: UI customization, onboarding path, notification preferences ### Phase 3: Execution & Optimization 1. **Journey execution**: - Real-time trigger processing across all channels - A/B testing at every decision point - Journey analytics: conversion rates, drop-off points, time-in-journey - Alert system for journey anomalies (sudden drop-offs, channel failures) 2. **Optimization cycle**: - Weekly review of journey performance metrics - A/B test results analysis and winner adoption - Journey path optimization (remove dead ends, add high-converting branches) - Model retraining for NBA engine (monthly) 3. **Governance & compliance**: - Consent management per channel (opt-in/opt-out tracking) - Frequency capping per customer per channel - Data privacy compliance (GDPR, CCPA) - Journey audit trail and rollback capability ## Templates ### Journey Blueprint Template ``` CUSTOMER JOURNEY BLUEPRINT — Activation → Retention ===================================================== Journey ID: [JRN-ACT-RET-001] | Version: [2.1] | Status: [Active] TARGET SEGMENT: Lifecycle stage: New Sign-Up (0-30 days) Entry criteria: Completed registration AND activated core feature within 7 days Exclusion criteria: Enterprise accounts (manual onboarding), trial-only users JOURNEY STRUCTURE: ┌─────────────────────────────────────────────────────────┐ │ TRIGGER: User completes core feature activation │ │ │ │ ┌── BRANCH: Feature adoption score > 70 ──────────────┐ │ │ │ │ │ │ │ Day 1: Email — "Welcome + Getting Started Guide" │ │ │ │ Day 3: In-app: Feature tip carousel (3 tips) │ │ │ │ Day 5: Email — "Advanced features you'll love" │ │ │ │ Day 7: Push notification — "Join our community" │ │ │ │ Day 14: Email — Case study: Similar company success │ │ │ │ Day 21: Email — "How's it going?" (CSAT survey) │ │ │ │ │ │ │ │ ┌── BRANCH: CSAT ≥ 8 ────────────────────────────┐ │ │ │ │ │ Email: Referral program invite + early reward │ │ │ │ │ │ (Advocacy path) │ │ │ │ │ └────────────────────────────────────────────────┘ │ │ │ │ │ │ │ │ ┌── BRANCH: CSAT < 7 ────────────────────────────┐ │ │ │ │ │ Email: Personalized help offer + CSM intro │ │ │ │ │ │ (Retention intervention path) │ │ │ │ │ └────────────────────────────────────────────────┘ │ │ │ └───────────────────────────────────────────────────┘ │ │ │ │ ┌── BRANCH: Feature adoption score ≤ 70 ─────────────┐ │ │ │ (Low engagement path — more nurturing) │ │ │ │ Day 1: Email — "Getting the most out of [Product]" │ │ │ │ Day 2: In-app: Guided tour of key features │ │ │ │ Day 4: Email — Video tutorial: Top 3 use cases │ │ │ │ Day 7: Push: "Your team at Company X does this..." │ │ │ │ Day 10: Email: "Common mistakes (and how to avoid)" │ │ │ │ Day 14: SMS (opt-in): Free 1-on-1 onboarding call │ │ │ │ Day 21: Email: Product update + new feature highlight│ │ │ │ Day 28: Email: "We miss you" + win-back offer │ │ │ └───────────────────────────────────────────────────┘ │ │ │ │ EXIT CRITERIA: │ │ ✓ Reached 30 days → transition to Retention journey │ │ ✓ Feature adoption > 80 → transition to Expansion │ │ ✗ No activity for 21 days → transition to At-Risk │ │ ✗ Cancellation → journey ends, churn analysis triggered │ └─────────────────────────────────────────────────────────┘ FREQUENCY CAPS: Email: max 2/week | Push: max 3/week | SMS: max 1/week In-app: max 5/week | Total cross-channel: max 8/week PERSONALIZATION: Dynamic content: Industry-specific examples, company name, feature usage data Send time optimization: Based on historical engagement patterns Channel preference: Respect stated and inferred preferences ``` ### Next Best Action Decision Matrix ``` NEXT BEST ACTION ENGINE — Decision Framework ============================================== Model Version: [3.4] | Retraining: [Monthly] | Accuracy: [84.2%] ACTION SCORING INPUTS: Customer signals: • Real-time behavior (page views, clicks, product actions) • Historical engagement (channel preference, content affinity) • Lifecycle stage and progression velocity • Predictive scores (churn risk, upgrade probability, CLV) • Segment membership (persona, industry, company size) Business constraints: • Frequency caps (per channel, per day/week) • Suppression lists (opt-out, bounce, complaint) • Offer eligibility (tier, plan, contract terms) • Business rules (VIP handling, compliance, blackout dates) • Channel availability (technical health, staffing) Action inventory: • Content recommendations (articles, videos, webinars) • Offers (discounts, upgrades, trials, bundles) • Engagement (surveys, check-ins, feedback requests) • Educational (tutorials, guides, best practices) • Community (events, forums, user groups) DECISION OUTPUT: Ranked actions: Top 3 recommended actions with confidence scores Primary action: Highest scored action → execute immediately Backup actions: Next 2 actions → queue for next opportunity Rationale: Explainable AI summary ("Because user viewed pricing page 3x...") EXAMPLE DECISION: Customer: Jane Smith, Acme Corp, Day 18, Adoption Score: 62 Recent behavior: Viewed pricing page (2x), opened 3 of last 5 emails Predictive scores: Churn risk: 23% | Upgrade probability: 14% Top actions: 1. [CONFIDENCE: 87%] Email — "Advanced features matching your use case" Rationale: Moderate adoption + pricing page views = ready for value expansion 2. [CONFIDENCE: 72%] In-app — Feature spotlight: reporting dashboard Rationale: Pricing interest suggests need for ROI visibility 3. [CONFIDENCE: 65%] Content — ROI calculator tool (personalized) Rationale: Build business case for expansion ``` ## Integration Points - **CDP**: Segment, Tealium, mParticle, Adobe Real-Time CDP - **Marketing automation**: HubSpot, Marketo, Braze, Customer.io, Salesforce Marketing Cloud - **Email**: SendGrid, Mailchimp, Postal, Amazon SES - **In-app messaging**: Intercom, Intercom, Pendo, Fullstory - **Push notifications**: OneSignal, Firebase, Urban Airship - **SMS**: Twilio, Bandwidth, MessageBird - **Analytics**: Google Analytics, Mixpanel, Amplitude, Heap - **CRM**: Salesforce, HubSpot, Pipedrive - **A/B testing**: Optimizely, VWO, Google Optimize - **Personalization**: Dynamic Yield, Bloomreach, ContentSquare - **Consent management**: OneTrust, TrustArc, Cookiebot ## Edge Cases | Scenario | Handling | |----------|----------| | Customer triggers multiple journeys simultaneously | Journey conflict resolution: prioritize by lifecycle stage, then business value | | Customer rapidly cycles through journey stages | Enforce minimum stage duration; prevent rapid re-triggering | | Personalization data stale or missing | Fall back to segment-level personalization, then to generic content | | Channel failure during journey execution | Retry once; switch to backup channel; log failure; alert ops team | | Customer opts out mid-journey | Immediate suppression across all channels; remove from active journeys | | Journey causes channel fatigue | Enforce frequency caps; implement cooling-off periods; monitor unsubscribe rate | | Regulatory change affects messaging | Emergency journey pause; compliance review; update templates; resume | | A/B test shows no significant difference | Extend test duration; increase sample size; analyze sub-segments | ## Output ### Journey Orchestration Dashboard ``` JOURNEY ORCHESTRATION DASHBOARD — Live View ============================================= As of: 2025-01-15 14:30 UTC ACTIVE JOURNEYS: 23 | Total customers in journeys: 8,427 JOURNEY PIPELINE: ┌────────────────────────┬────────────┬───────────┬────────────┬──────────────┐ │ Journey │ Active │ Completed │ Converted │ Conv. Rate │ ├────────────────────────┼────────────┼───────────┼────────────┼──────────────┤ │ Activation (New Users) │ 1,247 │ 3,891 │ 2,145 │ 55.1% │ │ Retention (Active) │ 4,523 │ 8,234 │ 6,012 │ 73.0% │ │ Expansion (Upgrade) │ 389 │ 1,567 │ 478 │ 30.5% │ │ Advocacy (Promoters) │ 156 │ 892 │ 623 │ 69.8% │ │ At-Risk (Declining) │ 287 │ 445 │ 134 │ 30.1% │ │ Win-back (Churned) │ 85 │ 178 │ 23 │ 12.9% │ └────────────────────────┴────────────┴───────────┴────────────┴──────────────┘ REAL-TIME TRIGGER ACTIVITY (Last 1 Hour): Triggers fired: 347 Actions executed: 289 (83.3% delivery rate) Failed deliveries: 12 (channel outage: SMS) Suppressed (frequency cap): 34 Suppressed (opt-out): 12 NEXT BEST ACTION STATS: NBA decisions: 289 | Avg confidence score: 76.3% Top recommended actions: 1. Email (personalized content): 89 [30.8%] 2. In-app message: 67 [23.2%] 3. Push notification: 52 [18.0%] 4. SMS (opt-in): 38 [13.2%] 5. Content recommendation: 43 [14.9%] PERFORMANCE TRENDS (Last 30 Days): Overall conversion rate: ↑ 61.2% (+3.1 pts) Journey completion rate: ↑ 74.5% (+2.8 pts) Avg engagement per customer: 4.2 touches (↑ 0.3) Channel fatigue rate: 2.1% (stable) Unsubscribe rate: 0.8% (↓ from 1.1%) ALERTS: ⚠ SMS delivery failure detected (12 messages) — investigating Twilio integration ⚠ At-Risk journey conversion below target (30.1% vs 35% target) ✓ Activation journey conversion exceeds target (55.1% vs 50% target) ```