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 m...

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

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

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

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

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

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)

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

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)

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)

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)