Files
claude-skills-reference/c-level-advisor/cro-advisor/references/nrr_playbook.md
Alireza Rezvani 466aa13a7b feat: C-Suite expansion — 8 new executive advisory roles (2→10) (#264)
* 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>
2026-03-06 01:35:08 +01:00

15 KiB

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:

  1. "What was the primary reason for your decision to cancel?"
  2. "What would have needed to be true for you to stay?"
  3. "What did you switch to, and what drove that decision?"
  4. "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:

  1. Pull monthly usage report showing which features unlicensed users are using
  2. Frame as: "Your team is getting value from X — you could be capturing that for the full team"
  3. Offer a team expansion proposal at renewal + 10% volume discount for seat adds
  4. 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:

  1. Build a "value realized" report before the upsell conversation (ROI proof)
  2. Use QBR as the venue: "You've achieved X. Here's what's possible at the next level."
  3. Frame the upgrade as unlocking more of what's already working
  4. 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:

  1. Land with core product; build relationship and prove value
  2. Cross-sell only after health score is green and NPS > 7
  3. Introduce the new product through a champion, not a cold pitch
  4. Pilot pricing: bundle into renewal at modest uplift vs. separate sale
  5. 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):

  1. Their goals, our progress — review what they said success looked like at kickoff (10 min)
  2. Usage and adoption data — product metrics presented in business language, not feature language (15 min)
  3. Value delivered — ROI proof: time saved, revenue influenced, risk reduced (10 min)
  4. Challenges and blockers — what's preventing more adoption? (10 min)
  5. Roadmap preview — upcoming features relevant to their use case (10 min)
  6. Next 90 days — joint success plan with owner and due dates (10 min)
  7. 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