Pipeline Diagnostics

Pipeline Coverage

Coverage Ratio = Total Pipeline / Quota Target

Stage Conversion Benchmarks

Deal Velocity

Sales Velocity = (Deals × Win Rate × ACV) / Sales Cycle

Higher velocity = more revenue, faster

1. More qualified opportunities (volume)
2. Higher win rate (quality)
3. Larger deal sizes (ACV)
4. Shorter sales cycles (speed)

Stage Distribution Analysis

Healthy Pipeline Shape:

Stage 1 (Qualified):    ████████████████████ 35%
Stage 2 (Discovery):    ████████████████ 25%
Stage 3 (Demo):         ████████████ 20%
Stage 4 (Proposal):     ████████ 12%
Stage 5 (Negotiation):  █████ 8%

Red Flags:
- Top-heavy: Too much early stage
- Bottom-heavy: Not enough new pipeline
- Middle stuck: Conversion problem

Age Analysis

• <7 days stale: Update and next steps
• 7-14 days stale: Manager review

• 14 days stale: Downgrade or close

Win/Loss Analysis

• What was the trigger event?
• Who was the champion?
• What was the competitive situation?
• What value resonated most?
• How long was the sales cycle?

• What stage did we lose?
• Who made the decision?
• What was the stated reason?
• What was the real reason?
• What would we do differently?

Problem Diagnosis

Not Enough Pipeline

• Coverage <3x in first half of quarter
• New pipeline creation slowing
• Deals closing without replacement

• Increase outbound activity 50%
• Run targeted campaign to ICP
• Re-engage closed-lost from 6+ months ago
• Ask for referrals from recent wins
• Partner-sourced pipeline push

Deals Stuck in Stage

• Average age exceeds benchmark
• Same deals appearing in reviews
• No clear next steps

• Implement stage exit criteria
• Add "days in stage" to dashboards
• Manager review for stale deals
• Create urgency with limited-time offer
• Multi-thread to other stakeholders

Low Win Rate

• Win rate <20%
• Losing to "no decision"
• Losing to specific competitor

• Tighten qualification criteria
• Improve discovery process
• Build champion enablement
• Create competitive battle cards
• Address pricing/packaging

Inaccurate Forecasts

• Consistent over/under forecasting
• Deals slipping between periods
• Late-quarter surprises

• Define clear commit criteria
• Weekly deal-by-deal review
• Track forecast accuracy by rep
• Implement deal scoring
• Require close plan for commits