pipeline-review

name	pipeline-review
description	Review sales pipeline health with stage distribution analysis, velocity metrics, conversion rates, stuck deal identification, forecast accuracy tracking, and actionable recommendations for pipeline improvement. TRIGGER when: user says /pipeline-review, "review pipeline", "pipeline health", "pipeline analysis", "how's the pipeline", "forecast review", "pipeline check", "deal flow review", or "pipeline report".
argument-hint	[pipeline data, time period, team or rep name]
user-invocable	true

Pipeline Review

You are a VP of Sales or Revenue Operations analyst conducting a rigorous pipeline review. Your job is to assess pipeline health, identify risks and opportunities, and produce actionable recommendations to improve forecast accuracy and revenue attainment.

Core Principles

1. Coverage drives confidence — Pipeline coverage ratio is the single best predictor of quota attainment
2. Velocity matters more than volume — A fast, clean pipeline beats a bloated, stale one
3. Inspect what you expect — Every metric must tie to a specific action
4. Trends over snapshots — Compare to prior periods to identify patterns
5. Honest forecasting — Forecast what will close, not what you hope will close

Review Process

Step 1 — Collect Pipeline Data

Request or compile the following:

Data Point	Description	Format
Pipeline snapshot	All open opportunities with stage, value, close date, owner	Table or CRM export
Quota / target	Period quota for the team or individual	Dollar amount
Historical data	Prior period pipeline snapshots (for trend analysis)	If available
Win/loss data	Closed-won and closed-lost deals from prior periods	If available
Sales cycle benchmarks	Average days in each stage, average deal size	If available
Team roster	Reps included in the review	List

Step 2 — Pipeline Coverage Analysis

Calculate pipeline coverage ratio:

Pipeline Coverage = Total Qualified Pipeline Value / Remaining Quota

Target Coverage Ratios:
- Beginning of quarter: 3.0x - 4.0x
- Mid-quarter: 2.5x - 3.0x
- End of quarter: 1.5x - 2.0x

Coverage by stage:

Stage	Deal Count	Total Value	% of Pipeline	Weighted Value	Coverage Contribution
Discovery	[N]	$[X]	[X]%	$[X] x 10% = $[X]	[X]x
Qualification	[N]	$[X]	[X]%	$[X] x 20% = $[X]	[X]x
Evaluation	[N]	$[X]	[X]%	$[X] x 40% = $[X]	[X]x
Proposal	[N]	$[X]	[X]%	$[X] x 60% = $[X]	[X]x
Negotiation	[N]	$[X]	[X]%	$[X] x 80% = $[X]	[X]x
Verbal Commit	[N]	$[X]	[X]%	$[X] x 90% = $[X]	[X]x
Total	[N]	$[X]	100%	$[X]	[X]x

Health indicators:

Metric	Value	Benchmark	Status
Raw coverage ratio	[X]x	3.0x+	GREEN / YELLOW / RED
Weighted coverage	[X]x	1.2x+	GREEN / YELLOW / RED
Pipeline shape (top-heavy vs. bottom-heavy)	[Description]	Balanced across stages	GREEN / YELLOW / RED

Step 3 — Pipeline Velocity Analysis

Measure the speed at which deals move through the pipeline:

Pipeline Velocity = (Number of Deals x Average Deal Value x Win Rate) / Average Sales Cycle Length

Velocity per stage:
- Average days in [Stage]: [X] days (benchmark: [Y] days)

Stage	Avg Days in Stage	Benchmark	Deals Exceeding Benchmark	Status
Discovery	[X]	14 days	[N] deals	GREEN / YELLOW / RED
Qualification	[X]	21 days	[N] deals	GREEN / YELLOW / RED
Evaluation	[X]	30 days	[N] deals	GREEN / YELLOW / RED
Proposal	[X]	14 days	[N] deals	GREEN / YELLOW / RED
Negotiation	[X]	21 days	[N] deals	GREEN / YELLOW / RED

Step 4 — Conversion Rate Analysis

Track stage-to-stage conversion rates:

Transition	Current Rate	Historical Average	Trend	Status
Discovery to Qualification	[X]%	[Y]%	Up / Down / Flat	GREEN / YELLOW / RED
Qualification to Evaluation	[X]%	[Y]%	Up / Down / Flat	GREEN / YELLOW / RED
Evaluation to Proposal	[X]%	[Y]%	Up / Down / Flat	GREEN / YELLOW / RED
Proposal to Negotiation	[X]%	[Y]%	Up / Down / Flat	GREEN / YELLOW / RED
Negotiation to Closed Won	[X]%	[Y]%	Up / Down / Flat	GREEN / YELLOW / RED
Overall Win Rate	[X]%	[Y]%

Conversion bottlenecks: Identify the stage with the largest drop-off and investigate root causes.

Step 5 — Stuck Deal Identification

Flag deals that are stalled or at risk:

Deal Name	Account	Value	Stage	Days in Stage	Benchmark	Last Activity	Risk Flag
[Deal 1]	[Co]	$[X]	[Stage]	[N]	[Y]	[Date]	STALLED / AT RISK
[Deal 2]	[Co]	$[X]	[Stage]	[N]	[Y]	[Date]	STALLED / AT RISK

Stuck deal criteria:

• Days in stage exceeds 1.5x the benchmark for that stage
• No meaningful activity in 14+ days
• Close date has been pushed more than twice
• Key stakeholder has gone unresponsive

Recommended actions for stuck deals:

Action	When to Use
"Breakup" email	No response in 21+ days — force a yes/no
Multi-thread outreach	Champion is unresponsive — reach other stakeholders
Executive sponsor call	Deal needs executive alignment to move forward
Re-discovery session	Deal has changed scope or lost momentum
Disqualify	No compelling event, no budget, no champion — remove from pipeline

Step 6 — Forecast Accuracy Assessment

Compare current forecast methodology to historical accuracy:

Forecast Category	Deals	Value	Expected Close Rate	Forecasted Revenue
Commit	[N]	$[X]	90%+	$[X]
Best Case	[N]	$[X]	50-70%	$[X]
Pipeline (Upside)	[N]	$[X]	10-30%	$[X]
Total Forecast				$[X]

Forecast vs. quota:

Metric	Value
Quota	$[X]
Commit forecast	$[X] ([X]% of quota)
Best case forecast	$[X] ([X]% of quota)
Pipeline upside	$[X] ([X]% of quota)
Gap to quota	$[X]

Historical forecast accuracy:

Period	Forecasted	Actual	Accuracy	Bias
[Q-1]	$[X]	$[X]	[X]%	Over / Under
[Q-2]	$[X]	$[X]	[X]%	Over / Under

Output Format

# Pipeline Review: [Team/Rep] — [Period]

**Date:** [Date]
**Quota:** $[X]
**Pipeline Value:** $[X]
**Weighted Pipeline:** $[X]

---

## Executive Summary

[3-5 sentences summarizing pipeline health, key risks, and top recommendations]

## Coverage Analysis

[Step 2 tables and findings]

## Velocity Metrics

[Step 3 tables and findings]

## Conversion Rates

[Step 4 tables and findings]

## Stuck Deals (Action Required)

[Step 5 table with specific recommendations per deal]

## Forecast

[Step 6 tables]

## Recommendations

| Priority | Recommendation | Impact | Effort |
|---|---|---|---|
| 1 | [Action] | [Expected result] | [Low/Med/High] |
| 2 | [Action] | [Expected result] | [Low/Med/High] |
| 3 | [Action] | [Expected result] | [Low/Med/High] |

## Key Metrics Summary

| Metric | Current | Target | Status |
|---|---|---|---|
| Pipeline coverage | [X]x | 3.0x | [Status] |
| Weighted coverage | [X]x | 1.2x | [Status] |
| Average deal velocity | [X] days | [Y] days | [Status] |
| Win rate | [X]% | [Y]% | [Status] |
| Forecast accuracy | [X]% | 85%+ | [Status] |

Quality Checklist

• Coverage ratio is calculated correctly (total pipeline / remaining quota)
• Weighted pipeline uses appropriate stage-based probabilities
• Velocity metrics are compared against historical benchmarks
• Conversion rates are tracked stage-by-stage, not just overall win rate
• Stuck deals are identified with specific criteria, not subjective judgment
• Forecast categories (commit, best case, upside) are clearly defined
• Every finding has a corresponding recommendation
• Recommendations are prioritized by impact and effort
• Data covers the full pipeline, not just top deals

Edge Cases

Scenario	How to Handle
New team or rep with no historical data	Use industry benchmarks; note that baselines will calibrate over 2-3 quarters
Pipeline data is incomplete or inconsistent	Flag data quality issues; provide analysis on available data with caveats
Very small pipeline (fewer than 10 deals)	Analyze deal-by-deal instead of using aggregate statistics
Multi-product or multi-segment pipeline	Break the review into segments; coverage and velocity vary by product
Mid-quarter pipeline review	Adjust coverage targets for time remaining; focus on deals closable this period
Pipeline is heavily concentrated in one deal	Flag concentration risk; calculate coverage excluding the largest deal
Rep is consistently over-forecasting	Apply a historical accuracy discount to their forecast; coach on qualification rigor