revenue-operations

---
name: revenue-operations
description: Use when analyzing sales pipeline coverage, forecasting revenue accuracy with MAPE, or calculating GTM efficiency (Magic Number, LTV:CAC, Rule of 40) for SaaS revenue teams.
category: Business Growth
version: 1.0.0
tools: []
---

# Revenue Operations

Deliver pipeline analysis, forecast accuracy tracking, and GTM efficiency
measurement for SaaS revenue teams. Perform each analysis directly by
reasoning over the deal, forecast, or financial data the user provides —
apply the same formulas and benchmarks every time for deterministic,
repeatable output.

## 1. Pipeline Analyzer

Analyzes sales pipeline health: coverage ratios, stage conversion rates, deal
velocity, aging risks, and concentration risk.

**Needed input:** quota, pipeline stages, average cycle length in days, and a
list of deals (id, name, stage, value, age in days, close date, owner).

**Key Metrics:**
- **Pipeline Coverage Ratio** — Total pipeline value / quota target (healthy: 3-4x)
- **Stage Conversion Rates** — Stage-to-stage progression rates
- **Sales Velocity** — (Opportunities × Avg Deal Size × Win Rate) / Avg Sales Cycle
- **Deal Aging** — Flag deals exceeding 2x average cycle time for their stage
- **Concentration Risk** — Warn when >40% of pipeline value sits in a single deal
- **Coverage Gap Analysis** — Identify quarters with insufficient pipeline

## 2. Forecast Accuracy Tracker

Tracks forecast accuracy over time using MAPE, detects systematic bias,
analyzes trends, and breaks down accuracy by category.

**Needed input:** forecast periods (period, forecast, actual) and optional
category breakdowns (e.g., by rep, product, segment).

**Key Metrics:**
- **MAPE** — mean(|actual − forecast| / |actual|) × 100
- **Forecast Bias** — Over-forecasting (positive) vs under-forecasting (negative) tendency
- **Weighted Accuracy** — MAPE weighted by deal value for materiality
- **Period Trends** — Improving, stable, or declining accuracy over time
- **Category Breakdown** — Accuracy by rep, product, segment, or any custom dimension

**Accuracy Ratings:**
| Rating | MAPE Range | Interpretation |
|--------|-----------|----------------|
| Excellent | <10% | Highly predictable, data-driven process |
| Good | 10-15% | Reliable forecasting with minor variance |
| Fair | 15-25% | Needs process improvement |
| Poor | >25% | Significant forecasting methodology gaps |

## 3. GTM Efficiency Calculator

Calculates core SaaS GTM efficiency metrics with industry benchmarking,
ratings, and improvement recommendations.

**Needed input:** revenue metrics (current ARR, prior ARR, net new ARR, ARPA,
growth %), cost metrics (S&M spend, CAC, gross margin %, operating expense,
net burn, FCF margin %), and customer metrics (beginning ARR, expansion ARR,
contraction ARR, churned ARR, annual churn rate %).

**Key Metrics:**
| Metric | Formula | Target |
|--------|---------|--------|
| Magic Number | Net New ARR / Prior Period S&M Spend | >0.75 |
| LTV:CAC | (ARPA × Gross Margin / Churn Rate) / CAC | >3:1 |
| CAC Payback | CAC / (ARPA × Gross Margin), in months | <18 months |
| Burn Multiple | Net Burn / Net New ARR | <2x |
| Rule of 40 | Revenue Growth % + FCF Margin % | >40% |
| Net Dollar Retention | (Begin ARR + Expansion − Contraction − Churn) / Begin ARR | >110% |

## Revenue Operations Workflows

### Weekly Pipeline Review

1. Confirm the pipeline data is current and all required fields (stage,
   value, close_date, owner) are populated.
2. Generate the pipeline report using the Pipeline Analyzer metrics above.
3. Cross-check output totals against the CRM source data for integrity.
4. Review key indicators: is coverage above 3x quota? which deals are aging
   past threshold? is there concentration risk? is the stage distribution a
   healthy funnel shape?
5. Note action items: address aging deals, redistribute concentration, fill
   coverage gaps.

### Forecast Accuracy Review

Run monthly or quarterly to evaluate and improve forecasting discipline.

1. Confirm all forecast periods have corresponding actuals with no gaps.
2. Generate the accuracy report using the Forecast Accuracy Tracker metrics.
3. Cross-check actuals against closed-won records before drawing conclusions.
4. Analyze patterns: is MAPE trending down? which reps or segments have the
   highest error rates? is there systematic over- or under-forecasting?
5. Recommend improvement actions: coach high-bias reps, adjust methodology,
   improve data hygiene.

### GTM Efficiency Audit

Run quarterly or during board prep to evaluate go-to-market efficiency.

1. Confirm revenue, cost, and customer figures reconcile with finance records.
2. Calculate the efficiency metrics above.
3. Cross-check computed ARR and spend totals against finance data.
4. Benchmark against targets: Magic Number (>0.75), LTV:CAC (>3:1), CAC
   Payback (<18 months), Rule of 40 (>40%).
5. Recommend strategic decisions: adjust spend allocation, optimize channels,
   improve retention.

### Quarterly Business Review

Combine all three analyses for a comprehensive QBR:

1. Pipeline analysis for forward-looking coverage
2. Forecast tracking for backward-looking accuracy
3. GTM efficiency for benchmarks
4. Cross-reference pipeline health with forecast accuracy
5. Align GTM efficiency metrics with growth targets