* feat: C-Suite expansion — 8 new executive advisory roles Add COO, CPO, CMO, CFO, CRO, CISO, CHRO advisors and Executive Mentor. Expands C-level advisory from 2 to 10 roles with 74 total files. Each role includes: - SKILL.md (lean, <5KB, ~1200 tokens for context efficiency) - Reference docs (loaded on demand, not at startup) - Python analysis scripts (stdlib only, runnable CLI) Executive Mentor features /em: slash commands (challenge, board-prep, hard-call, stress-test, postmortem) with devil's advocate agent. 21 Python tools, 24 reference frameworks, 28,379 total lines. All SKILL.md files combined: ~17K tokens (8.5% of 200K context window). Badge: 88 → 116 skills * feat: C-Suite orchestration layer + 18 complementary skills ORCHESTRATION (new): - cs-onboard: Founder interview → company-context.md - chief-of-staff: Routing, synthesis, inter-agent orchestration - board-meeting: 6-phase multi-agent deliberation protocol - decision-logger: Two-layer memory (raw transcripts + approved decisions) - agent-protocol: Inter-agent invocation with loop prevention - context-engine: Company context loading + anonymization CROSS-CUTTING CAPABILITIES (new): - board-deck-builder: Board/investor update assembly - scenario-war-room: Cascading multi-variable what-if modeling - competitive-intel: Systematic competitor tracking + battlecards - org-health-diagnostic: Cross-functional health scoring (8 dimensions) - ma-playbook: M&A strategy (acquiring + being acquired) - intl-expansion: International market entry frameworks CULTURE & COLLABORATION (new): - culture-architect: Values → behaviors, culture code, health assessment - company-os: EOS/Scaling Up operating system selection + implementation - founder-coach: Founder development, delegation, blind spots - strategic-alignment: Strategy cascade, silo detection, alignment scoring - change-management: ADKAR-based change rollout framework - internal-narrative: One story across employees/investors/customers UPGRADES TO EXISTING ROLES: - All 10 roles get reasoning technique directives - All 10 roles get company-context.md integration - All 10 roles get board meeting isolation rules - CEO gets stage-adaptive temporal horizons (seed→C) Key design decisions: - Two-layer memory prevents hallucinated consensus from rejected ideas - Phase 2 isolation: agents think independently before cross-examination - Executive Mentor (The Critic) sees all perspectives, others don't - 25 Python tools total (stdlib only, no dependencies) 52 new files, 10 modified, 10,862 new lines. Total C-suite ecosystem: 134 files, 39,131 lines. * fix: connect all dots — Chief of Staff routes to all 28 skills - Added complementary skills registry to routing-matrix.md - Chief of Staff SKILL.md now lists all 28 skills in ecosystem - Added integration tables to scenario-war-room and competitive-intel - Badge: 116 → 134 skills - README: C-Level Advisory count 10 → 28 Quality audit passed: ✅ All 10 roles: company-context, reasoning, isolation, invocation ✅ All 6 phases in board meeting ✅ Two-layer memory with DO_NOT_RESURFACE ✅ Loop prevention (no self-invoke, max depth 2, no circular) ✅ All /em: commands present ✅ All complementary skills cross-reference roles ✅ Chief of Staff routes to every skill in ecosystem * refactor: CEO + CTO advisors upgraded to C-suite parity Both roles now match the structural standard of all new roles: - CEO: 11.7KB → 6.8KB SKILL.md (heavy content stays in references) - CTO: 10KB → 7.2KB SKILL.md (heavy content stays in references) Added to both: - Integration table (who they work with and when) - Key diagnostic questions - Structured metrics dashboard table - Consistent section ordering (Keywords → Quick Start → Responsibilities → Questions → Metrics → Red Flags → Integration → Reasoning → Context) CEO additions: - Stage-adaptive temporal horizons (seed=3m/6m/12m → B+=1y/3y/5y) - Cross-references to culture-architect and board-deck-builder CTO additions: - Key Questions section (7 diagnostic questions) - Structured metrics table (DORA + debt + team + architecture + cost) - Cross-references to all peer roles All 10 roles now pass structural parity: ✅ Keywords ✅ QuickStart ✅ Questions ✅ Metrics ✅ RedFlags ✅ Integration * feat: add proactive triggers + output artifacts to all 10 roles Every C-suite role now specifies: - Proactive Triggers: 'surface these without being asked' — context-driven early warnings that make advisors proactive, not reactive - Output Artifacts: concrete deliverables per request type (what you ask → what you get) CEO: runway alerts, board prep triggers, strategy review nudges CTO: deploy frequency monitoring, tech debt thresholds, bus factor flags COO: blocker detection, scaling threshold warnings, cadence gaps CPO: retention curve monitoring, portfolio dog detection, research gaps CMO: CAC trend monitoring, positioning gaps, budget staleness CFO: runway forecasting, burn multiple alerts, scenario planning gaps CRO: NRR monitoring, pipeline coverage, pricing review triggers CISO: audit overdue alerts, compliance gaps, vendor risk CHRO: retention risk, comp band gaps, org scaling thresholds Executive Mentor: board prep triggers, groupthink detection, hard call surfacing This transforms the C-suite from reactive advisors into proactive partners. * feat: User Communication Standard — structured output for all roles Defines 3 output formats in agent-protocol/SKILL.md: 1. Standard Output: Bottom Line → What → Why → How to Act → Risks → Your Decision 2. Proactive Alert: What I Noticed → Why It Matters → Action → Urgency (🔴🟡⚪) 3. Board Meeting: Decision Required → Perspectives → Agree/Disagree → Critic → Action Items 10 non-negotiable rules: - Bottom line first, always - Results and decisions only (no process narration) - What + Why + How for every finding - Actions have owners and deadlines ('we should consider' is banned) - Decisions framed as options with trade-offs - Founder is the highest authority — roles recommend, founder decides - Risks are concrete (if X → Y, costs $Z) - Max 5 bullets per section - No jargon without explanation - Silence over fabricated updates All 10 roles reference this standard. Chief of Staff enforces it as a quality gate. Board meeting Phase 4 uses the Board Meeting Output format. * feat: Internal Quality Loop — verification before delivery No role presents to the founder without passing verification: Step 1: Self-Verification (every role, every time) - Source attribution: where did each data point come from? - Assumption audit: [VERIFIED] vs [ASSUMED] tags on every finding - Confidence scoring: 🟢 high / 🟡 medium / 🔴 low per finding - Contradiction check against company-context + decision log - 'So what?' test: every finding needs a business consequence Step 2: Peer Verification (cross-functional) - Financial claims → CFO validates math - Revenue projections → CRO validates pipeline backing - Technical feasibility → CTO validates - People/hiring impact → CHRO validates - Skip for single-domain, low-stakes questions Step 3: Critic Pre-Screen (high-stakes only) - Irreversible decisions, >20% runway impact, strategy changes - Executive Mentor finds weakest point before founder sees it - Suspicious consensus triggers mandatory pre-screen Step 4: Course Correction (after founder feedback) - Approve → log + assign actions - Modify → re-verify changed parts - Reject → DO_NOT_RESURFACE + learn why - 30/60/90 day post-decision review Board meeting contributions now require self-verified format with confidence tags and source attribution on every finding. * fix: resolve PR review issues 1, 4, and minor observation Issue 1: c-level-advisor/CLAUDE.md — completely rewritten - Was: 2 skills (CEO, CTO only), dated Nov 2025 - Now: full 28-skill ecosystem map with architecture diagram, all roles/orchestration/cross-cutting/culture skills listed, design decisions, integration with other domains Issue 4: Root CLAUDE.md — updated all stale counts - 87 → 134 skills across all 3 references - C-Level: 2 → 33 (10 roles + 5 mentor commands + 18 complementary) - Tool count: 160+ → 185+ - Reference count: 200+ → 250+ Minor observation: Documented plugin.json convention - Explained in c-level-advisor/CLAUDE.md that only executive-mentor has plugin.json because only it has slash commands (/em: namespace) - Other skills are invoked by name through Chief of Staff or directly Also fixed: README.md 88+ → 134 in two places (first line + skills section) * fix: update all plugin/index registrations for 28-skill C-suite 1. c-level-advisor/.claude-plugin/plugin.json — v2.0.0 - Was: 2 skills, generic description - Now: all 28 skills listed with descriptions, all 25 scripts, namespace 'cs', full ecosystem description 2. .codex/skills-index.json — added 18 complementary skills - Was: 10 roles only - Now: 28 total c-level entries (10 roles + 6 orchestration + 6 cross-cutting + 6 culture) - Each with full description for skill discovery 3. .claude-plugin/marketplace.json — updated c-level-skills entry - Was: generic 2-skill description - Now: v2.0.0, full 28-skill ecosystem description, skills_count: 28, scripts_count: 25 * feat: add root SKILL.md for c-level-advisor ClawHub package --------- Co-authored-by: Leo <leo@openclaw.ai>
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NRR Playbook
Net Revenue Retention is the single most important metric for a SaaS company's health and valuation. A company with 120% NRR grows even if it closes zero new deals. A company with 80% NRR is filling a bucket with a hole in it.
NRR Deep Dive
The Fundamental Formula
NRR = (Opening MRR + Expansion MRR - Contraction MRR - Churned MRR) / Opening MRR
Example:
Opening MRR: $1,000,000
Expansion: +$150,000
Contraction: -$30,000
Churn: -$80,000
Closing MRR: $1,040,000
NRR = $1,040,000 / $1,000,000 = 104%
NRR vs. GRR
| Metric | Formula | What It Tells You |
|---|---|---|
| GRR | (Opening - Contraction - Churn) / Opening | Retention floor — how much you keep without any expansion |
| NRR | (Opening + Expansion - Contraction - Churn) / Opening | Net health — expansion offsetting churn |
| Logo Retention | (Customers start - Customers churned) / Customers start | Volume retention, ignores revenue weight |
GRR is the floor. NRR is the ceiling.
If GRR is 80% and NRR is 105%, your expansion is covering 25 points of churn. That's fragile — any expansion slowdown turns NRR negative. The fix is GRR, not more upsell.
Benchmarks by Segment
| Segment | Good GRR | Good NRR | Exceptional NRR |
|---|---|---|---|
| SMB-focused | 80-85% | 95-105% | > 110% |
| Mid-Market | 85-90% | 105-115% | > 120% |
| Enterprise | 90-95% | 115-130% | > 140% |
Enterprise NRR can exceed 140% because large accounts expand substantially and rarely churn entirely — they may downgrade but full logo churn is rare if the product is embedded.
NRR by Cohort
Don't just measure NRR across the full base — measure it by customer cohort (month of acquisition).
Jan 2024 Cohort:
Opening MRR (Jan 2024): $50,000
MRR at Jan 2025: $62,000
12-month NRR: 124%
Feb 2024 Cohort:
Opening MRR (Feb 2024): $45,000
MRR at Feb 2025: $38,000
12-month NRR: 84% ← problem cohort
Cohort analysis reveals:
- Whether a specific acquisition channel brings lower-quality customers
- Whether a product change or pricing shift affected retention
- Whether specific sales reps or time periods created bad-fit deals
Churn Anatomy
Not all churn is equal. Know the breakdown before prescribing solutions.
Churn Types
| Type | Definition | Primary Cause | Fix |
|---|---|---|---|
| Logo churn | Customer cancels entirely | No value, poor fit, champion left, competitor | Root cause analysis, ICP tightening |
| Revenue churn | ARR lost (cancels + downgrades combined) | Same as logo + downgrade triggers | Address both volume and revenue |
| Involuntary churn | Failed payment, expired card | Billing friction | Dunning improvement (quick win: 20-30% recovery) |
| Voluntary churn | Active cancellation decision | Explicit dissatisfaction, competitor win | Exit interview + intervention program |
| Contraction | Downgrade, seat reduction | Overpurchased, budget cut, team reduction | Right-sizing program, annual contracts |
Churn Root Cause Framework
Run this analysis quarterly on all churned accounts:
Step 1: Categorize by reason
- No value realized (never activated or adopted)
- Value realized but budget cut (external, not product)
- Switched to competitor (why? what did they offer?)
- Champion left company (relationship loss, not product failure)
- Company shutdown / acquisition (unavoidable)
Step 2: Look for patterns
- Which ICP signals predict churn? (company size, vertical, acquisition channel)
- Which product behaviors predict churn? (no login in 30 days, never completed onboarding)
- Which time periods have highest churn? (months 3, 6, 12 are typical cliff points)
Step 3: Act on the patterns
- ICP pattern → tighten qualification criteria
- Behavior pattern → build early warning health score
- Time cliff → build intervention playbooks for months 2, 5, 11
Exit Interview Protocol
Talk to every churned customer if ACV > $10K. For smaller, do quarterly batch surveys.
Questions:
- "What was the primary reason for your decision to cancel?"
- "What would have needed to be true for you to stay?"
- "What did you switch to, and what drove that decision?"
- "Was there a specific moment when you decided to leave?"
Rules:
- CSM who owned the account should NOT conduct the exit interview (too much relationship bias)
- Use a neutral party or the VP CS
- Document verbatim, not paraphrased
- Feed patterns back to Product and Sales monthly
Customer Health Scoring
A health score predicts churn 60-90 days before it happens. Without one, you're reactive.
Health Score Components
Score each account 0-100 across weighted signals:
| Signal | Weight | Red (0-33) | Yellow (34-66) | Green (67-100) |
|---|---|---|---|---|
| Product usage (DAU/WAU, feature adoption depth) | 35% | < 20% seats active | 20-60% seats active | > 60% seats active |
| Engagement (QBR attendance, champion responsiveness) | 20% | No response 60+ days | 30-60 days | Active, < 30 days |
| NPS / CSAT | 20% | Score < 6 | Score 6-7 | Score 8-10 |
| Support volume (negative signal: high volume = friction) | 15% | > 10 tickets/month | 3-10/month | < 3/month |
| Contract signals (time to renewal, expansion in motion) | 10% | < 60 days to renewal, no expansion discussion | 60-90 days, passive | > 90 days, expansion active |
Composite score:
- 70-100: Healthy. Renewal confident. Identify expansion opportunity.
- 50-69: At-risk. CSM check-in required. Executive sponsor loop-in if < 60 days to renewal.
- 0-49: Red alert. Immediate intervention. VP CS or CEO call if strategic account.
Health Score Automation
Trigger alerts automatically:
Score drops > 20 points in 30 days → CSM immediate outreach (same day)
No product login in 14 days → Automated email + CSM flag (within 24 hours)
Champion leaves company → Executive outreach (within 24 hours)
Support escalation → CSM loop-in (within 2 hours)
Renewal < 90 days + score < 60 → VP CS review (weekly)
Seat utilization < 30% → Adoption intervention playbook triggered
Leading Indicators vs. Lagging Indicators
| Leading (predict future churn) | Lagging (confirm past churn) |
|---|---|
| Login frequency declining | Cancellation submitted |
| Feature adoption stalling at basic level | Non-renewal at contract end |
| NPS score trend (not just snapshot) | Downgrade executed |
| No QBR scheduled in 90+ days | Champion departure |
| Support escalations increasing | Competitor mentioned in support |
Build your health score from leading indicators. Lagging indicators tell you what already happened.
Expansion Revenue Strategies
Expansion is cheaper than acquisition. CAC for expansion is typically 20-30% of new logo CAC.
Expansion Motion 1: Seat Expansion
Trigger signals:
- Usage by unlicensed users (shared logins, "can you add my colleague?")
- Team growth visible on LinkedIn (company hiring in target department)
- Champion promotes to a new role with bigger team
- Power users at license limit consistently
Playbook:
- Pull monthly usage report showing which features unlicensed users are using
- Frame as: "Your team is getting value from X — you could be capturing that for the full team"
- Offer a team expansion proposal at renewal + 10% volume discount for seat adds
- Never penalize users for sharing logins before the conversation — that's a data asset
Expansion Motion 2: Upsell (Tier Upgrade)
Trigger signals:
- Customer consistently hitting usage/feature limits
- Security or compliance requirement that requires higher tier
- New stakeholder joining who needs admin controls
- API usage growing rapidly (engineering team engagement)
Playbook:
- Build a "value realized" report before the upsell conversation (ROI proof)
- Use QBR as the venue: "You've achieved X. Here's what's possible at the next level."
- Frame the upgrade as unlocking more of what's already working
- Time to renewal: start upsell conversation 90-120 days before renewal
Expansion Motion 3: Cross-sell
Trigger signals:
- Strategic account with adjacent problem your product can solve
- New product launch that complements existing usage
- Customer explicitly asks about a capability in your roadmap or adjacent product
Playbook:
- Land with core product; build relationship and prove value
- Cross-sell only after health score is green and NPS > 7
- Introduce the new product through a champion, not a cold pitch
- Pilot pricing: bundle into renewal at modest uplift vs. separate sale
- Cross-sell owner: CSM or AE (define explicitly — joint ownership = no ownership)
Expansion Sequencing
Don't try all three simultaneously. Sequence matters:
Month 0-3: Activation focus — ensure core value delivered
Month 3-6: Seat expansion — grow usage within existing team
Month 6-9: Upsell conversation — unlock advanced features
Month 9-12: Cross-sell OR renewal + multi-year lock-in
NRR Modeling
Target breakdown for 115% NRR:
GRR: 88% (12% lost to churn/contraction)
Expansion rate: 27% (upsell + cross-sell + seat expansion)
NRR: 88% + 27% = 115%
To reach 120% NRR:
Option A: Improve GRR to 92% (reduce churn), keep expansion at 28%
Option B: Keep GRR at 88%, improve expansion to 32%
Option C: Both, incrementally
Option A is usually easier and more durable. Fix the hole first.
Customer Success Integration
CS and Revenue are not separate functions. NRR lives at their intersection.
CS Team Structure (aligned to NRR)
| CS Model | When to Use | NRR Focus |
|---|---|---|
| High-touch CSM | ACV > $25K | Named accounts, QBRs, executive relationships |
| Tech-touch / pooled | ACV $5K-25K | Automated health scoring, office hours, community |
| Self-serve | ACV < $5K | In-app guidance, knowledge base, email sequences |
CSM coverage ratios:
- High-touch: 1 CSM per $2M-4M ARR managed
- Tech-touch: 1 CSM per $5M-10M ARR managed
- Self-serve: Product and automation (no dedicated CSM)
CS Compensation (aligned to NRR)
Don't pay CSMs a flat salary — align incentive to retention and expansion:
CS compensation structure:
Base: 70% of OTE
Variable: 30% of OTE
Variable tied to:
GRR / NRR vs. target (50% of variable)
Health score improvement (25% of variable)
Expansion ARR facilitated (25% of variable)
Do NOT pay CS commission on expansion ARR the same way AEs earn it.
This creates conflict: CS will push expansion before the customer is ready.
Instead, bonus for expansion milestones — it's a different incentive structure.
QBR (Quarterly Business Review) Framework
QBRs are the primary vehicle for expansion and churn prevention in enterprise accounts.
QBR agenda (60-90 minutes):
- Their goals, our progress — review what they said success looked like at kickoff (10 min)
- Usage and adoption data — product metrics presented in business language, not feature language (15 min)
- Value delivered — ROI proof: time saved, revenue influenced, risk reduced (10 min)
- Challenges and blockers — what's preventing more adoption? (10 min)
- Roadmap preview — upcoming features relevant to their use case (10 min)
- Next 90 days — joint success plan with owner and due dates (10 min)
- Expansion opportunity — if health score is green and timing is right (10 min)
QBR anti-patterns:
- Leading with your product roadmap (they don't care; start with their results)
- Bringing too many people from your side without matching seniority
- Presenting at a VP without bringing the economic buyer
- Skipping QBRs for "healthy" accounts (health can change fast)
- No confirmed next step at the end
Cohort-Based Retention Analysis
Aggregate NRR hides the signal. Cohort analysis reveals it.
Retention Curve Analysis
Plot retention by months since acquisition for each quarterly cohort:
Month 0: 100% (starting revenue)
Month 3: First cliff — early adopters who didn't activate churn here
Month 6: Second cliff — customers who never expanded, running out of runway
Month 12: Renewal cliff — annual contract renewal decision
Month 18: Mature customers — churn rate stabilizes significantly
Healthy curve: Drops sharply in months 1-3, flattens after month 6
Problem curve: Continues declining linearly through month 12+ (no value anchor)
Reading Cohort Data
| Pattern | Interpretation | Action |
|---|---|---|
| Early churn (months 1-3) | Onboarding / activation failure | Fix time-to-value, improve onboarding |
| Mid-cycle churn (months 4-8) | Value not deepening | Adoption program, check product fit |
| Annual renewal churn (month 12) | Buying committee didn't renew | Executive engagement, earlier renewal process |
| Flat after month 6 | Sticky product, low expansion | Increase upsell motion |
| Growing after month 6 | Expansion working | Scale the upsell playbook |
Cohort Segmentation Variables
Slice retention cohorts by:
- Acquisition channel (inbound vs. outbound vs. PLG vs. partner)
- Sales rep (which reps close durable deals vs. churny deals)
- Deal size (SMB churn rate typically 2-3x enterprise)
- Industry vertical (some verticals have structurally higher churn)
- Product tier at signup (self-serve → converted vs. directly contracted)
- Geographic market (international markets often have different retention profiles)
The most actionable finding is usually by acquisition channel or sales rep — both are directly controllable.
Churn Prevention Intervention Playbooks
Playbook 1: Low Activation (no login in first 14 days)
Day 7: Automated email: "Getting started" + specific next step
Day 14: CSM outreach: "I noticed you haven't logged in — can I help?"
Day 21: Escalate to CSM manager if no response
Day 30: Executive outreach for ACV > $25K; flag as at-risk
Playbook 2: Usage Cliff (DAU drops > 50% in 30 days)
Trigger: Automated health score alert
Day 1: CSM reviews usage report, identifies likely cause
Day 2: CSM outreach: "We noticed your team's usage changed — is everything okay?"
Day 7: If no response: schedule 30-min call with champion
Day 14: If unresponsive: VP CS loop-in + executive reach out
Playbook 3: Champion Departure
Trigger: LinkedIn alert or internal report of champion leaving
Day 1: Email to departed champion (warm handoff ask)
Day 1: Email to new stakeholder (introduction from AE or VP CS)
Day 3: Schedule onboarding call for new stakeholder
Day 14: QBR with new stakeholder to establish relationship
Day 30: Health score review — flag if engagement hasn't recovered
Playbook 4: Pre-Renewal (90 days out, health score < 70)
Day -90: CSM completes account health review, escalates if < 70
Day -75: Executive sponsor from vendor side joins renewal call
Day -60: Value delivered report prepared (ROI proof)
Day -45: Renewal proposal sent with expansion option
Day -30: Follow-up on any open objections or requirements
Day -14: Final confirm or escalate to VP Sales