Agent Skills: Customer Retention System Designer

Design customer retention systems with health scoring, churn prediction, and proactive engagement workflows. Use when reducing churn or maximizing LTV.

UncategorizedID: majesticlabs-dev/majestic-marketplace/retention-system

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plugins/majestic-marketing/skills/retention-system/SKILL.md

Skill Metadata

Name
retention-system
Description
Design customer retention systems with health scoring, churn prediction, and proactive engagement workflows. Use when reducing churn or maximizing LTV.

Customer Retention System Designer

Conversation Starter

Use AskUserQuestion to gather initial context. Begin by asking:

"I'll help you design a customer retention system that reduces churn and maximizes lifetime value.

Please provide:

  1. Business Model: What do you sell? (SaaS, subscription, service, product)
  2. Pricing: What's your pricing structure? (monthly, annual, tiers)
  3. Current Churn: What's your monthly/annual churn rate?
  4. Customer Journey: How long is typical customer relationship?
  5. Team Structure: Do you have customer success? Support?
  6. Data Available: What customer behavior data can you track?"

Research Methodology

Use WebSearch to find:

  • Industry-specific churn benchmarks
  • Customer health score models
  • Onboarding best practices
  • Churn prediction methodologies
  • NPS and CSAT benchmarks

Strategy Framework

1. Customer Lifecycle Stages

| Stage | Entry Criteria | Success Criteria | |-------|----------------|------------------| | Acquisition | Account created | First login | | Activation | First login | Aha moment achieved | | Engagement | Activated | Regular usage | | Expansion | Engaged 90+ days | Upsell/cross-sell | | Advocacy | Expanded OR high NPS | Referral made | | At-Risk | Warning signals | Re-engaged | | Churned | Cancelled/lapsed | Win-back sequence |

2. Health Score Model

Score Components (100 points):

| Category | Weight | Metrics | |----------|--------|---------| | Product Usage | 40% | Login frequency, feature adoption, depth of use | | Engagement | 25% | Email opens, support tickets, event attendance | | Relationship | 20% | NPS score, CSM interactions, executive sponsor | | Business Health | 15% | Payment history, growth rate, expansion potential |

Health Bands:

| Score | Status | Action | |-------|--------|--------| | 80-100 | Healthy (Green) | Monitor, expansion focus | | 60-79 | Stable (Yellow) | Proactive engagement | | 40-59 | At-Risk (Orange) | Intervention required | | 0-39 | Critical (Red) | Immediate escalation |

See references/playbooks.md for detailed scoring criteria.

3. Onboarding System

| Day | Goal | Touchpoints | |-----|------|-------------| | 1 | First value realization | Welcome email, in-app tutorial, quick win | | 2-3 | Core setup complete | Setup reminder, CSM intro (high-touch) | | 7 | Confirm activation | Progress email, feature highlight, check-in call | | 14 | Habit formation | Use case email, advanced feature intro | | 30 | First month success | NPS survey, success celebration, QBR (enterprise) | | 60 | Expansion readiness | ROI report, feature teaser | | 90 | Renewal prep | Renewal reminder, success summary, renewal call |

4. Early Warning Signals

Usage-Based: | Signal | Threshold | Risk | |--------|-----------|------| | Login drop | >50% vs prior month | High | | Feature abandonment | Core feature unused 14+ days | High | | User count drop | Team members removed | Critical |

Engagement-Based: | Signal | Threshold | Risk | |--------|-----------|------| | Email silence | No opens 30 days | Medium | | Support spike | 3+ tickets in 7 days | Medium | | NPS decline | Dropped 2+ points | High |

Business-Based: | Signal | Threshold | Risk | |--------|-----------|------| | Payment failed | Any failed charge | Critical | | Downgrade request | Any inquiry | High | | Competitor mention | In support/conversation | Critical |

5. Intervention Playbooks

See references/playbooks.md for detailed playbooks:

  • Usage Decline (14-day sequence)
  • Support Escalation (72-hour response)
  • Competitor Threat (48-hour response)
  • Payment Failure (30-day dunning)
  • Renewal Risk (90-day cycle)

6. Retention Metrics

Primary KPIs:

| Metric | Formula | Benchmark | |--------|---------|-----------| | Gross Revenue Retention | (Start MRR - Churn) / Start | 85-95% | | Net Revenue Retention | (Start + Expansion - Churn) / Start | 100-120% | | Logo Churn Rate | Churned / Starting | 3-7%/year | | Customer LTV | ARPU × (1 / Monthly Churn) | Varies |

Health Metrics:

| Metric | Target | |--------|--------| | Healthy accounts (>80 score) | >60% | | At-risk accounts (<60 score) | <15% | | NPS | >50 | | CSAT | >85% | | DAU/MAU | >20% | | Activation rate | >80% |

Output Format

# RETENTION SYSTEM BLUEPRINT: [Business Name]

## Executive Summary
[2-3 sentences on churn situation and approach]

## Customer Lifecycle Map
[Stages with criteria]

## Health Score Model
[Customized scoring framework]

## Onboarding System
[Day-by-day touchpoints]

## Early Warning System
[Signals and thresholds]

## Intervention Playbooks
[Playbooks for each risk type]

## Success Tier Model
[Tier definitions and engagement]

## Metrics Dashboard
[KPIs and tracking setup]

## Implementation Roadmap

### Phase 1: Foundation (Weeks 1-2)
- [ ] Define health score components
- [ ] Set up tracking infrastructure

### Phase 2: Onboarding (Weeks 3-4)
- [ ] Build onboarding sequence
- [ ] Create activation metrics

### Phase 3: Monitoring (Weeks 5-6)
- [ ] Deploy health scoring
- [ ] Set up early warning alerts

### Phase 4: Optimization (Ongoing)
- [ ] Weekly metrics review
- [ ] Playbook effectiveness analysis

Quality Standards

  • Research-driven: Use WebSearch for industry benchmarks
  • Customized scoring: Adjust weights based on business model
  • Actionable playbooks: Clear triggers and specific actions
  • Measurable outcomes: Every recommendation tied to metrics
  • Scalable design: Works at current size and 10x scale