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Glossary:
Sales Performance Metrics
Master the essential revenue and financial metrics that drive B2B SaaS success. From ARR and MRR to retention metrics and customer economics, these terms are critical for understanding pipeline health, forecasting growth, and making data-driven decisions.
Weighted Pipeline
Short Definition
Definition
Weighted Pipeline is a sales forecasting method that multiplies each opportunity's potential value by its probability of closing (based on pipeline stage), then sums those values for a probability-adjusted revenue forecast. In B2B SaaS, it provides a more realistic view than unweighted pipeline (which assumes 100% close rate for all deals).
Each stage has a defined probability (Stage 1: 10%, Proposal: 50%, Negotiation: 80%). This reveals true pipeline health, guides resource allocation, and improves forecast accuracy over raw pipeline value.
How to Calculate Weighted Pipeline
Weighted Pipeline Formula
Weighted Pipeline Value= ∑ (Deal Value × Stage Probability)
Step-by-Step Calculation
- Assign close probability to each pipeline stage based on historical win rates.
- For each deal, multiply deal value by its stage probability.
- Sum all weighted deal values.
- Compare to quota for coverage ratio.
Example:
Weighted Pipeline = $245K (vs. $450K unweighted)
Why Weighted Pipeline Matters
Weighted Pipeline transforms "hopeful pipeline" into actionable forecasts:
- Realistic coverage (3x weighted vs. 5x unweighted signals risk)
- Resource prioritization (focus on high-probability late-stage deals)
- Forecast baseline (weighted value + velocity = expected closes)
- Process diagnostics (low late-stage probabilities signal execution gaps)
CROs use it to set pipeline generation targets and validate forecast categories.
Industry Benchmarks
Coverage targets: 3–4x weighted pipeline to quota (vs. 4–6x unweighted).
Real-World Examples
- A mid-market SaaS has 5x unweighted coverage but only 2.2x weighted. The CRO doubles down on late-stage pipeline generation, adding $2.5M in negotiation/proposal deals in 60 days.
- An enterprise sales team starts the quarter with $10M in weighted pipeline (3.5x $2.85M quarterly quota coverage: $3M Opp@25%, $4M Proposal@50%, $3M Negotiation@80%). They execute with a 85% late-stage close rate to deliver $2.7M (95% quota).
- RevOps adjusts stage probabilities quarterly based on actual win rates, improving weighted forecast accuracy from 72% to 89% across 150+ deals.
Common Mistakes
- Static probabilities: using 20/40/60/80 regardless of actual win rates.
- Early-stage inflation: treating MQLs/SQLs as "pipeline.”
- No historical validation: guessing probabilities vs. measuring.
- Ignoring deal age: leaving stale older deals at higher probabilities.
- Over-reliance: weighted pipeline and velocity still need qualitative review.
The Fix: Calibrate probabilities quarterly from actual stage win rates, exclude pre-opp stages, age-weight stale deals, combine with forecast categories and velocity.
Frequently Asked Questions
Weighted vs. unweighted pipeline?
Weighted = deal value × stage probability (realistic).
Unweighted = full deal value (optimistic).
How often should we update stage probabilities?
Quarterly, based on actual win rates from prior periods. Monthly for high-velocity teams.
Should expansion deals use the same probabilities?
Typically you should use separate probabilities. Renewals and expansions tend to have higher probabilities than new business.
What's a good weighted pipeline coverage?
3–4x quota is standard for most B2B SaaS. Enterprise may need 4–5x due to longer cycles.
Can weighted pipeline be higher than quota?
Yes. This provides a buffer for slippage. Target 3–4x for predictable attainment.
Last Updated: December 18, 2025
Reviewed by: Ben Hale