# Customer Success

> Customer Success operating system - segmented coverage model, health scoring, risk playbooks, value reviews, and expansion motions tied to net revenue retention. Use when: customer success strategy, CS operating model, health score, risk playbook, EBR / QBR design, churn prevention, net retention, NRR, GRR, success plan, value realization, customer journey post-sale.

- Skill: `varunk130/customer-success` (Agent Skill)
- Install (CLI): `npx skillmds@latest add varunk130/customer-success`
- Raw SKILL.md: https://api.skillmd.com/api/skills/varunk130/customer-success/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: varunk130 (https://skillmd.com/u/varunk130)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/varunk130/customer-success

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# Customer Success (THRIVE Framework)

Design a Customer Success operating system that turns post-sale into a predictable revenue engine. The skill enforces explicit coverage tiering, a health score that actually predicts churn, named risk playbooks, value reviews that earn renewals, and expansion motions that move NRR - instead of a generic "we should do QBRs" plan.

## Core Principle

**Customer Success is a *coverage and signal* problem, not a relationship problem.** Most CS teams over-invest in friendly check-ins with healthy accounts and under-invest in early risk signals and value proof. THRIVE forces tiered coverage, leading indicators, and renewal-defensible value evidence.

## The THRIVE Framework

| Letter | Stage | The Question |
|--------|-------|--------------|
| **T** | Tier the Book | Which accounts get high-touch, tech-touch, or pooled coverage - and why? |
| **H** | Health Scoring | What 4-6 leading signals predict churn 90+ days out? |
| **R** | Risk Playbooks | When a signal trips, what named play runs in what timeframe? |
| **I** | Insight Reviews | What evidence of value gets shown at each review cadence? |
| **V** | Value Realization | How is realized ROI captured and quantified before renewal? |
| **E** | Expansion Motion | Which signals trigger which expansion play, and who owns the handoff? |

## Coverage Tiering

| Tier | ARR Band | Coverage | Cadence | Primary Goal |
|------|----------|----------|---------|--------------|
| **High-touch** | Top 10-20% of ARR | Named CSM, exec sponsor | Monthly check-in + quarterly EBR | NRR > 120% |
| **Mid-touch** | Mid 30-60% | Pooled CSM, named for risks | Quarterly value review | GRR > 92% |
| **Tech-touch** | Long tail | Digital programs, in-product nudges | Automated lifecycle | Self-serve renewal > 80% |

## Health Score Design

A useful health score uses **leading**, not lagging, signals. Lagging scores (NPS, ticket volume, login count) confirm churn after it's already locked in.

| Signal Type | Example | Why It Leads |
|-------------|---------|--------------|
| **Adoption depth** | % of paid seats active weekly on critical workflows | Predicts contract value justification |
| **Outcome attainment** | Customer-defined success metric progress | Predicts renewal defensibility |
| **Stakeholder coverage** | # of named champions + exec sponsor engaged in last 90 days | Predicts survivability of champion change |
| **Support signal velocity** | Critical-severity tickets trend (not count) | Predicts frustration cliff |
| **Commercial signal** | Procurement contact, contract questions, late payment | Predicts negotiation posture |

## Risk Playbooks

Every health-score drop triggers a **named play** with an owner and a deadline:

| Trigger | Play | Owner | SLA |
|---------|------|-------|-----|
| Champion leaves | "Land the new champion" - re-onboarding kit + exec re-intro within 14 days | CSM + AE | 14 days |
| Adoption drop > 20% MoM | Root-cause workshop + adoption sprint | CSM + Solutions | 21 days |
| Outcome miss flagged | Outcome reset + escalation to exec sponsor | CSM + VP CS | 30 days |
| Stakeholder ghosting > 30 days | Multi-thread re-engagement + alternative-stakeholder hunt | CSM + AE | 21 days |

## Output

Save to `outputs/customer-success-[motion]-[YYYY-MM-DD].md`

| Artifact | Description |
|----------|-------------|
| **Coverage Model** | Tier definitions, account assignment rules, CSM ratios |
| **Health Score Spec** | 4-6 signals, weights, thresholds, decay rules |
| **Risk Play Library** | Named plays with owners, SLAs, success criteria |
| **Review Cadence Calendar** | EBR / QBR / value-review template by tier |
| **Renewal Defense Pack** | Value evidence pack template (ROI, adoption proof, outcome attainment) |
| **Expansion Map** | Signals → plays → handoff rules between CSM and AE |
| **CS Operating Metrics** | NRR, GRR, logo retention, time-to-value, expansion ARR |

## Process

1. **Tier the book** with explicit revenue and strategic-fit rationale; cut tiers that don't justify the coverage cost
2. **Define 4-6 health signals** - at least 3 must be leading; document weights and decay
3. **Author named risk plays** for the top 6-8 trigger conditions; every play has an owner + SLA
4. **Design the review cadence** per tier with a fixed agenda; value evidence is non-negotiable
5. **Build the renewal defense pack** template - what gets shown 90 days before renewal
6. **Map expansion signals to plays** and codify the CSM → AE handoff

## Tips

1. **Health scores must be defensible** - every signal needs a "why this leads churn" rationale
2. **Coverage ratios are not industry benchmarks** - they're a function of your motion's complexity
3. **EBR/QBR without value evidence is a relationship tax** - make outcomes the agenda
4. **Don't conflate CS with support** - support resolves issues, CS realizes outcomes
5. **Renewal forecasts come from the health score**, not CSM optimism

## Pairs With

- **growth-loop** - Retention and expansion strategy at the system level
- **journey-architect** - Post-sale journey gates the health signals attach to
- **enablement-forge** - Builds the EBR / value review templates
- **revenue-analytics** - NRR / GRR analysis the playbooks are scored against