Forecasting works with your existing pipeline data. No additional setup is required beyond having opportunities with values and stages configured.
Pipeline forecasting overview
Pipeline forecasting calculates expected revenue by combining two data points for each opportunity:- Opportunity value — the dollar amount of the deal
- Stage probability — the likelihood of closing based on the current pipeline stage
Weighted pipeline values
Each pipeline stage has an associated close probability. As opportunities advance through stages, their weighted value increases:| Stage | Probability | Deal value | Weighted value |
|---|---|---|---|
| Qualification | 10% | $50,000 | $5,000 |
| Discovery | 25% | $50,000 | $12,500 |
| Proposal | 50% | $50,000 | $25,000 |
| Negotiation | 75% | $50,000 | $37,500 |
| Closed Won | 100% | $50,000 | $50,000 |
Forecast categories
Beyond stage-based weighting, you can assign a forecast category to each opportunity for manual override:- Commit
- Best case
- Pipeline
- Omitted
Deals the rep is confident will close this period. These should be in late stages with verbal or written agreement. Commit deals form the floor of your revenue forecast.
Revenue prediction
The forecasting dashboard provides three revenue views:Weighted forecast
Total expected revenue based on stage probabilities. This is the most common forecast metric and updates automatically as deals move through stages.
Category forecast
Revenue broken down by forecast category (Commit, Best Case, Pipeline). Gives managers a rep-level view of deal confidence.
Unweighted total
Raw sum of all open opportunity values without probability weighting. Useful for understanding total addressable pipeline but not for revenue planning.
Viewing your forecast
Set the time period
Use the date range selector to choose the forecast period — weekly, monthly, quarterly, or custom range. The forecast shows only opportunities with an expected close date within this window.
Filter by pipeline or rep
Use the filter controls to narrow the view to a specific pipeline, sales rep, or team. This lets managers drill into individual performance.
Forecast vs actual comparison
After a period closes, the platform compares your forecast to actual results:| Metric | Description |
|---|---|
| Forecast accuracy | Percentage match between predicted and actual closed revenue |
| Commit accuracy | How often Commit-category deals actually closed |
| Slip rate | Percentage of deals that pushed to a future period |
| Upside wins | Deals that closed but were not in the Commit category |
| Coverage ratio | Total pipeline value divided by quota — indicates whether there is enough pipeline to hit target |
Using forecasting data for decision-making
Forecasting is not just a reporting exercise. Use the data to drive action:Identify pipeline gaps early
Identify pipeline gaps early
If the weighted forecast is below target with two weeks left in the quarter, you need to generate more pipeline or accelerate existing deals. Do not wait until the period closes to react.
Coach reps on forecast discipline
Coach reps on forecast discipline
Compare each rep’s Commit accuracy over time. Reps who consistently over-commit need coaching on realistic deal assessment. Reps who under-commit may be sandbagging.
Prioritize high-probability deals
Prioritize high-probability deals
Sort opportunities by weighted value to see which deals will have the biggest revenue impact if they close. Focus team energy on moving these deals forward.
Plan resource allocation
Plan resource allocation
Use the category forecast to anticipate workload. If a large number of Best Case deals are expected to close next month, ensure your onboarding and delivery teams are prepared.
Set realistic quotas
Set realistic quotas
Use historical forecast accuracy and coverage ratios to set quotas that are ambitious but achievable. Quotas disconnected from pipeline reality damage team morale.