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# revenue-operations

> Analyze sales pipeline health, forecast revenue, measure quota attainment, and optimize funnel conversion. Use when building RevOps dashboards, diagnosing pipeline gaps, forecasting quarterly revenue, or aligning sales-marketing-CS handoffs.

# Revenue Operations

End-to-end RevOps framework for pipeline analytics, revenue forecasting, quota management, and cross-functional alignment between Sales, Marketing, and Customer Success.

## Use this skill when

- Building or reviewing a RevOps dashboard
- Diagnosing pipeline coverage gaps or stage bottlenecks
- Forecasting quarterly or annual revenue
- Analyzing quota attainment at individual, team, or org level
- Designing sales-marketing-CS handoff processes
- Calculating key revenue metrics (ARR, NRR, Magic Number, LTV:CAC)

## Do not use this skill when

- Designing pricing tiers or packaging (use `pricing-strategy`)
- Analyzing early-stage startup metrics with no pipeline (use `startup-metrics-framework`)
- Running individual A/B tests on sales emails (use `ab-test-analysis`)
- Building the actual dashboard infrastructure (use data engineering skills)

## Instructions

1. **Assess pipeline health** using the Pipeline Health Scorecard.
2. **Forecast revenue** using the appropriate methodology (weighted, commit-based, or historical).
3. **Measure quota attainment** at individual and team levels.
4. **Analyze funnel conversion** stage by stage to identify bottlenecks.
5. **Align cross-functional handoffs** using the Sales-Marketing Alignment Framework.
6. **Report using** the Quarterly RevOps Report template.

---

## RevOps Metrics Taxonomy

Master reference for revenue metrics — know these before building any dashboard:

### Growth Metrics

| 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 |

### Efficiency Metrics

| 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 |

### Pipeline Metrics

| 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) |

---

## Pipeline Health Scorecard

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:**
- 5-6 green: Pipeline is healthy — focus on execution
- 3-4 green: Pipeline has gaps — targeted intervention needed
- 0-2 green: Pipeline is at risk — immediate action required

---

## Revenue Forecasting Methods

### Method 1: Weighted Pipeline

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** | | | **$** |

### Method 2: Commit Categories

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)**

### Method 3: Historical Pattern

Best for: Mature businesses with 4+ quarters of data.

1. Calculate trailing 4-quarter conversion rate by stage
2. Apply stage conversion rates to current pipeline
3. Adjust for seasonality (Q4 uplift, Q1 budget flush, summer slowdown)
4. Layer in known macro factors (market expansion, new product launch)

---

## Funnel Conversion Analysis

Stage-by-stage diagnostic to find bottlenecks:

```markdown
## 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:** [...]
```

---

## Quota Attainment Dashboard

| Rep / Team | Quota | Closed | Attainment | Pipeline | Coverage | Forecast |
|-----------|-------|--------|------------|----------|----------|----------|
| | $ | $ | % | $ | Xx | $ |
| **Team Total** | **$** | **$** | **%** | **$** | **Xx** | **$** |

**Ramp-Adjusted Quotas:**
- Month 1-3: 25% quota (ramp)
- Month 4-6: 50% quota
- Month 7+: 100% quota
- New hires should be excluded from full attainment calculations for first 6 months

---

## Sales-Marketing Alignment Framework

| 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 |

---

## Output Template: Quarterly RevOps Report

```markdown
# 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
```

---

## Common Mistakes

- **Forecasting on pipeline value without weighting** — $1M in Discovery is not the same as $1M in Negotiation
- **Ignoring deal aging** — opportunities older than 2x average cycle are likely dead; clean the pipeline
- **Conflating bookings with revenue** — bookings = contract signed; revenue = recognized per ASC 606
- **Single-source pipeline dependency** — if >50% of pipeline comes from one channel, diversify immediately
- **Not segmenting metrics** — SMB, mid-market, and enterprise have fundamentally different benchmarks
- **Treating coverage as a static number** — 4x coverage means nothing if 60% is stale deals

---

## Additional Resources

- Related skills: `startup-metrics-framework` (early-stage metrics), `pricing-strategy` (pricing impact on pipeline)
- SaaStr benchmarks for SaaS RevOps metrics
- Winning by Design — revenue architecture frameworks
