Circulos AI

Marketing AI Skill

Customer Experience Marketing

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:
  1. Define behavioral triggers:
  1. Design journey paths:

Phase 2: Personalization Engine Configuration

  1. Customer data platform (CDP) integration:
  1. Next Best Action (NBA) engine:
  1. Personalization layers:

Phase 3: Execution & Optimization

  1. Journey execution:
  1. Optimization cycle:
  1. Governance & compliance:

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

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)

Disclaimer: All rights reserved by Circulos AI. These skills are specifically designed for Claude Code, Claude Cowork, Codex, and OpenClaw. When using or referencing any skill, please provide proper attribution to Circulos AI.