customer-success · diff
git:20260516.4225f52 to git:20260522.2e90392
19 added, 19 removed. Audit A to A.
---
name: customer-success
- description: '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.'
+ description: '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.'
---
# 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.
+ 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? |
+ | **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% |
+ | **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 |
+ | 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 |
+ | **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
+ 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
+ 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
+ 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
+ - **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