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npx claudepluginhub frank-luongt/faos-skills-marketplace --plugin faos-croHow this skill is triggered — by the user, by Claude, or both
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/faos-cro:revenue-operationsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
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Smart pipeline analytics that learns from deal outcomes over time — identify patterns, predict risks, and surface coaching opportunities from pipeline data. Use this skill whenever a manager wants pipeline insights beyond basic reporting, when analyzing conversion rates, deal velocity, or stage progression, when someone says "why are we losing deals at stage X", "what's wrong with our pipeline", "pipeline trends", or when building data-driven coaching strategies. Also trigger when someone mentions pipeline health, deal velocity, conversion analysis, or RevOps analytics. This is the layer that turns pipeline data into actionable intelligence.
Generates weighted sales forecasts with best/likely/worst scenarios, commit/upside breakdowns, and gap-to-quota analysis from CRM pipeline CSVs or manual deal inputs.
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End-to-end RevOps framework for pipeline analytics, revenue forecasting, quota management, and cross-functional alignment between Sales, Marketing, and Customer Success.
pricing-strategy)startup-metrics-framework)ab-test-analysis)Master reference for revenue metrics — know these before building any dashboard:
| Metric | Formula | Benchmark (SaaS) |
|---|---|---|
| ARR | MRR x 12 | Growth target: 2-3x <$10M, 1.5-2x >$10M |
| MRR | Sum of all monthly recurring revenue | Track net new, expansion, contraction, churn |
| Net Revenue Retention (NRR) | (Starting MRR + Expansion - Contraction - Churn) / Starting MRR | >120% = elite, >100% = healthy |
| Gross Revenue Retention (GRR) | (Starting MRR - Contraction - Churn) / Starting MRR | >90% = healthy, <85% = problem |
| Metric | Formula | Benchmark |
|---|---|---|
| Magic Number | Net New ARR (QoQ) / S&M Spend (prev Q) | >0.75 = efficient, invest more |
| CAC Payback | CAC / (ARR per customer x Gross Margin) | <18 months = healthy |
| LTV:CAC | Customer LTV / CAC | >3:1 = healthy, >5:1 = underinvesting |
| Sales Efficiency | Net New ARR / Total Sales Cost | >1.0 = self-funding |
| Metric | Formula | Benchmark |
|---|---|---|
| Pipeline Coverage | Total Pipeline Value / Revenue Target | 3-4x = healthy |
| Win Rate | Closed Won / (Closed Won + Closed Lost) | 20-30% = typical B2B SaaS |
| Average Deal Size | Total Revenue / Number of Deals | Track trend, not absolute |
| Sales Cycle Length | Avg days from opportunity created to closed won | Varies by segment (SMB: 30d, Mid: 60d, Enterprise: 90-180d) |
Run this assessment monthly or quarterly:
| Dimension | Metric | Target | Actual | Status |
|---|---|---|---|---|
| Coverage | Pipeline / Target | 3-4x | ||
| Quality | Win rate (trailing 2Q) | >25% | ||
| Velocity | Avg cycle length vs. benchmark | Within 20% | ||
| Balance | Stage distribution (no stage >40%) | Even spread | ||
| Freshness | % pipeline <90 days old | >60% | ||
| Source Mix | No single source >50% | Diversified |
Interpretation:
Best for: Mid-market and enterprise with defined sales stages.
| Stage | Probability | Pipeline Value | Weighted Value |
|---|---|---|---|
| Discovery | 10% | ||
| Qualification | 20% | ||
| Demo/Evaluation | 40% | ||
| Proposal | 60% | ||
| Negotiation | 80% | ||
| Verbal Commit | 90% | ||
| Total Weighted | $ |
Best for: Quarterly forecasting with sales team input.
| Category | Definition | Example |
|---|---|---|
| Commit | Rep stakes their quota on it closing this quarter | Signed MSA, verbal PO |
| Best Case | High confidence but with known risk | Champion engaged, budget approved, timeline unclear |
| Upside | Could close but significant unknowns | Early stage, multi-threaded but no champion |
Forecast = Commit + (Best Case x 0.7) + (Upside x 0.3)
Best for: Mature businesses with 4+ quarters of data.
Stage-by-stage diagnostic to find bottlenecks:
## Funnel Conversion Report — [Quarter]
| Stage Transition | Volume | Conversion Rate | Benchmark | Delta | Action |
|-----------------|--------|-----------------|-----------|-------|--------|
| Lead → MQL | | % | 30-40% | | |
| MQL → SQL | | % | 40-60% | | |
| SQL → Opportunity | | % | 50-70% | | |
| Opportunity → Demo | | % | 60-80% | | |
| Demo → Proposal | | % | 40-60% | | |
| Proposal → Closed Won | | % | 20-40% | | |
| **End-to-end** | | **%** | **2-5%** | | |
### Bottleneck Analysis
- **Biggest drop-off:** [Stage] at [X]% vs. [Y]% benchmark
- **Root cause hypothesis:** [...]
- **Recommended intervention:** [...]
| Rep / Team | Quota | Closed | Attainment | Pipeline | Coverage | Forecast |
|---|---|---|---|---|---|---|
| $ | $ | % | $ | Xx | $ | |
| Team Total | $ | $ | % | $ | Xx | $ |
Ramp-Adjusted Quotas:
| Handoff Point | SLA | Metric | Owner |
|---|---|---|---|
| Marketing → SDR (MQL) | Respond within 5 min | Lead response time | Marketing Ops |
| SDR → AE (SQL) | Complete BANT qualification | MQL-to-SQL conversion | SDR Manager |
| AE → CS (Closed Won) | Handoff call within 5 days | Time-to-onboard | AE + CS |
| CS → AE (Expansion) | Flag expansion signal | Expansion pipeline | CS Manager |
# RevOps Report — Q[X] [Year]
## Executive Summary
- Revenue: $[X] vs. $[Y] target ([Z]% attainment)
- Pipeline coverage: [X]x (target: 3-4x)
- Key risk: [summary]
## Revenue Performance
[Actual vs. forecast vs. target waterfall]
## Pipeline Health
[Scorecard results]
## Funnel Conversion
[Stage-by-stage analysis with bottleneck callout]
## Forecast — Next Quarter
[Commit + Best Case + Upside breakdown]
## Actions Required
1. [Action] — Owner — Deadline
2. [Action] — Owner — Deadline
startup-metrics-framework (early-stage metrics), pricing-strategy (pricing impact on pipeline)