customer-success

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