Weighted Pipeline
Weighted pipeline is 30-50% more accurate for forecasting than raw pipeline value, reducing forecast error from ±40% to ±20% (Clari 2024).
💡TL;DR
Weighted Pipeline = sum of (deal amount × win probability). Assign probabilities by stage: Discovery 10%, Demo 25%, Proposal 50%, Negotiation 75%, Verbal 90%. Example: $500k raw pipeline with weighted value of $175k means you'll likely close ~$175k. Use weighted for forecasting, raw for pipeline coverage calculations.
Definition
Pipeline value adjusted by probability of close at each stage. Weighted Pipeline = Σ(Deal Value × Stage Probability). A $100k deal at 50% stage counts as $50k weighted. It provides more realistic revenue forecasts than raw pipeline totals.
🏢What This Means for SMB Teams
SMB deals are more volatile—actual close rates may differ from stage probabilities. Calibrate probabilities quarterly by comparing weighted forecast to actual closed revenue.
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📋Practical Example
A 25-person SaaS had $2.4M raw pipeline but kept missing quarterly forecasts by 40%+. They implemented weighted pipeline with calibrated probabilities: Discovery 5%, Demo 15%, Proposal 35%, Negotiation 60%, Contract 85%. Weighted pipeline showed $680k vs. $1.2M quota—a clear gap. They added top-of-funnel campaigns. Next quarter, weighted pipeline reached $1.4M and they hit $1.1M actual (within 20% of weighted).
🔧Implementation Steps
- 1
Analyze historical win rates by stage to set accurate probabilities.
- 2
Configure CRM to auto-calculate weighted value based on stage.
- 3
Compare weighted forecast to actuals quarterly; adjust probabilities if off >15%.
- 4
Use weighted for forecasting calls, raw pipeline for coverage analysis.
- 5
Alert reps when weighted pipeline is below quota × (1 / average close rate).
❓Frequently Asked Questions
Should I use company-wide or rep-specific probabilities?
Start with company-wide for simplicity. As you gather data, consider rep-specific for accurate forecasting—top performers may have higher stage probabilities than average.
How do I handle custom deal-level probabilities?
Some CRMs allow reps to override stage probability per deal. Use sparingly—reps tend to be optimistic. Require justification for overrides and audit accuracy quarterly.
⚡How Optifai Uses This
Optifai calculates weighted pipeline automatically using calibrated stage probabilities. The Revenue Dashboard shows both raw and weighted views, alerting when weighted coverage falls below quota targets.
📚References
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Related Terms
Pipeline Coverage
The ratio of total pipeline value to sales quota, indicating whether there are enough opportunities to meet revenue targets given historical conversion rates.
Pipeline Management
The process of tracking and managing sales opportunities as they move through stages, including forecasting, prioritization, and identifying at-risk deals.
Revenue Forecast Accuracy
The percentage deviation between forecasted and actual revenue over a given period. Calculated as 1 - |Actual - Forecast| / Actual. High accuracy (within 5-10%) indicates healthy pipeline visibility and rep discipline; low accuracy suggests poor data hygiene or unrealistic projections.
Sales Velocity
A metric measuring how quickly deals move through the pipeline and generate revenue, calculated as: (Number of Opportunities × Win Rate × Average Deal Size) / Sales Cycle Length.