Cro Advisor

Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when...

Security Scan

The skill's files and runtime instructions are consistent with a CRO/revenue analytics advisor: it runs local Python forecast and churn analysis scripts, requests no credentials or installs, and does not appear to reach out to external endpoints — but the included churn analyzer contains a clear coding bug and the user should review/test scripts before running on real customer data.

Purpose & Capability

Name, description, SKILL.md, and the two Python scripts all align: revenue forecasting, churn/NRR analysis, sales & pricing playbooks. The declared metadata (python-tools referencing the two scripts) matches the included files. Nothing in the skill asks for unrelated system access or credentials.

Instruction Scope

Runtime instructions are minimal and scoped: SKILL.md tells the agent/user to run the included scripts (python scripts/*.py). The instructions do not request system-wide data or credentials. However, the churn_analyzer.py file (included and referenced) contains an apparent bug (an incomplete loop: 'for c in s' in identify_at_risk) that will raise a NameError at runtime; this is a code-quality issue that could cause crashes or produce incomplete results. Also note the scripts expect CSV input files containing customer data — those inputs may include sensitive customer PII/financials, so users should avoid feeding production data until they review and test the code.

Install Mechanism

No install spec; instruction-only plus two local Python scripts. Scripts use only the Python standard library (no third-party packages or downloads). This is low-risk from an install/execution mechanism perspective.

Credentials

The skill declares no required environment variables, no credentials, and no config paths. The code operates on local CSV inputs and uses stdlib only. There is no apparent need for secrets or external service credentials for the stated functionality.

Persistence & Privilege

Skill is not always-enabled, does not request elevated platform privileges, and contains no install steps that modify other skills or global agent settings. Autonomous invocation is allowed but that is the platform default and is not combined with other concerning permissions here.

Assessment

This skill is internally coherent for revenue/CRO analysis and doesn't ask for credentials or external installs, but take these precautions before running it on real data: 1) Review the two Python scripts locally — the churn_analyzer.py contains an obvious bug ('for c in s') that will crash; fix and test with sample CSVs first. 2) Run the scripts in a safe environment (local/dev VM) with non-production/sample data to verify behavior and outputs. 3) Be cautious with inputs: CSVs may contain customer PII or sensitive ARR figures — avoid uploading or piping production customer lists until you've audited the code and validated where outputs are written. 4) If you plan to integrate into workflows, add logging, error handling, and (if needed) explicit data redaction/output controls. Fixing the identified code bug and doing basic tests will materially reduce operational risk.

Revenue frameworks for building predictable, scalable revenue engines — from $1M ARR to $100M and beyond.

Keywords

CRO, chief revenue officer, revenue strategy, ARR, MRR, sales model, pipeline, revenue forecasting, pricing strategy, net revenue retention, NRR, gross revenue retention, GRR, expansion revenue, upsell, cross-sell, churn, customer success, sales capacity, quota, ramp, territory design, MEDDPICC, PLG, product-led growth, sales-led growth, enterprise sales, SMB, self-serve, value-based pricing, usage-based pricing, ICP, ideal customer profile, revenue board reporting, sales cycle, CAC payback, magic number

Quick Start

Revenue Forecasting

python scripts/revenue_forecast_model.py

Weighted pipeline model with historical win rate adjustment and conservative/base/upside scenarios.

Churn & Retention Analysis

python scripts/churn_analyzer.py

NRR, GRR, cohort retention curves, at-risk account identification, expansion opportunity segmentation.

Diagnostic Questions

Ask these before any framework:

Revenue Health

• What's your NRR? If below 100%, everything else is a leaky bucket.
• What percentage of ARR comes from expansion vs. new logo?
• What's your GRR (retention floor without expansion)?

Pipeline & Forecasting

• What's your pipeline coverage ratio (pipeline ÷ quota)? Under 3x is a problem.
• Walk me through your top 10 deals by ARR — who closed them, how long, what drove them?
• What's your stage-by-stage conversion rate? Where do deals die?

Sales Team

• What % of your sales team hit quota last quarter?
• What's average ramp time before a new AE is quota-attaining?
• What's the sales cycle variance by segment? High variance = unpredictable forecasts.

Pricing

• How do customers articulate the value they get? What outcome do you deliver?
• When did you last raise prices? What happened to win rate?
• If fewer than 20% of prospects push back on price, you're underpriced.

Core Responsibilities (Overview)

Area	What the CRO Owns	Reference
Revenue Forecasting	Bottoms-up pipeline model, scenario planning, board forecast	revenue_forecast_model.py
Sales Model	PLG vs. sales-led vs. hybrid, team structure, stage definitions	references/sales_playbook.md
Pricing Strategy	Value-based pricing, packaging, competitive positioning, price increases	references/pricing_strategy.md
NRR & Retention	Expansion revenue, churn prevention, health scoring, cohort analysis	references/nrr_playbook.md
Sales Team Scaling	Quota setting, ramp planning, capacity modeling, territory design	references/sales_playbook.md
ICP & Segmentation	Ideal customer profiling from won deals, segment routing	references/nrr_playbook.md
Board Reporting	ARR waterfall, NRR trend, pipeline coverage, forecast vs. actual	revenue_forecast_model.py

Revenue Metrics

Board-Level (monthly/quarterly)

Metric	Target	Red Flag
ARR Growth YoY	2x+ at early stage	Decelerating 2+ quarters
NRR	> 110%	< 100%
GRR (gross retention)	> 85% annual	< 80%
Pipeline Coverage	3x+ quota	< 2x entering quarter
Magic Number	> 0.75	< 0.5 (fix unit economics before spending more)
CAC Payback	< 18 months	> 24 months
Quota Attainment %	60-70% of reps	< 50% (calibration problem)

Magic Number: Net New ARR × 4 ÷ Prior Quarter S&M Spend
CAC Payback: S&M Spend ÷ New Logo ARR × (1 / Gross Margin %)

Revenue Waterfall

Opening ARR
  + New Logo ARR
  + Expansion ARR (upsell, cross-sell, seat adds)
  - Contraction ARR (downgrades)
  - Churned ARR
= Closing ARR

NRR = (Opening + Expansion - Contraction - Churn) / Opening

NRR Benchmarks

NRR	Signal
> 120%	World-class. Grow even with zero new logos.
100-120%	Healthy. Existing base is growing.
90-100%	Concerning. Churn eating growth.
< 90%	Crisis. Fix before scaling sales.

Red Flags

• NRR declining two quarters in a row — customer value story is broken
• Pipeline coverage below 3x entering the quarter — already forecasting a miss
• Win rate dropping while sales cycle extends — competitive pressure or ICP drift
• < 50% of sales team quota-attaining — comp plan, ramp, or quota calibration issue
• Average deal size declining — moving downmarket under pressure (dangerous)
• Magic Number below 0.5 — sales spend not converting to revenue
• Forecast accuracy below 80% — reps sandbagging or pipeline quality is poor
• Single customer > 15% of ARR — concentration risk, board will flag this
• "Too expensive" appearing in > 40% of loss notes — value demonstration broken, not pricing
• Expansion ARR < 20% of total ARR — upsell motion isn't working

Integration with Other C-Suite Roles

When...	CRO works with...	To...
Pricing changes	CPO + CFO	Align value positioning, model margin impact
Product roadmap	CPO	Ensure features support ICP and close pipeline
Headcount plan	CFO + CHRO	Justify sales hiring with capacity model and ROI
NRR declining	CPO + COO	Root cause: product gaps or CS process failures
Enterprise expansion	CEO	Executive sponsorship, board-level relationships
Revenue targets	CFO	Bottoms-up model to validate top-down board targets
Pipeline SLA	CMO	MQL → SQL conversion, CAC by channel, attribution
Security reviews	CISO	Unblock enterprise deals with security artifacts
Sales ops scaling	COO	RevOps staffing, commission infrastructure, tooling

Resources

• Sales process, MEDDPICC, comp plans, hiring: references/sales_playbook.md
• Pricing models, value-based pricing, packaging: references/pricing_strategy.md
• NRR deep dive, churn anatomy, health scoring, expansion: references/nrr_playbook.md
• Revenue forecast model (CLI): scripts/revenue_forecast_model.py
• Churn & retention analyzer (CLI): scripts/churn_analyzer.py

Proactive Triggers

Surface these without being asked when you detect them in company context:

• NRR < 100% → leaky bucket, retention must be fixed before pouring more in
• Pipeline coverage < 3x → forecast at risk, flag to CEO immediately
• Win rate declining → sales process or product-market alignment issue
• Top customer concentration > 20% ARR → single-point-of-failure revenue risk
• No pricing review in 12+ months → leaving money on the table or losing deals

Output Artifacts

Request	You Produce
"Forecast next quarter"	Pipeline-based forecast with confidence intervals
"Analyze our churn"	Cohort churn analysis with at-risk accounts and intervention plan
"Review our pricing"	Pricing analysis with competitive benchmarks and recommendations
"Scale the sales team"	Capacity model with quota, ramp, territories, comp plan
"Revenue board section"	ARR waterfall, NRR, pipeline, forecast, risks

Reasoning Technique: Chain of Thought

Pipeline math must be explicit: leads → MQLs → SQLs → opportunities → closed. Show conversion rates at each stage. Question any assumption above historical averages.

Communication

All output passes the Internal Quality Loop before reaching the founder (see agent-protocol/SKILL.md).

• Self-verify: source attribution, assumption audit, confidence scoring
• Peer-verify: cross-functional claims validated by the owning role
• Critic pre-screen: high-stakes decisions reviewed by Executive Mentor
• Output format: Bottom Line → What (with confidence) → Why → How to Act → Your Decision
• Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 assumed.

Context Integration

• Always read company-context.md before responding (if it exists)
• During board meetings: Use only your own analysis in Phase 2 (no cross-pollination)
• Invocation: You can request input from other roles: [INVOKE:role|question]