B2B Sales Glossary:

Sales Forecasting

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.

Forecast Call

Short Definition

A recurring sales meeting in which leaders and reps review pipeline to produce a committed revenue prediction for the current period, typically broken into commit, best case, and upside figures.

What Is a Forecast Call?

A forecast call is a recurring meeting—typically weekly or bi-weekly—in which sales leaders and their teams review the current state of the pipeline, assess which deals are expected to close within a defined period, and produce a revenue prediction for that period. In most B2B SaaS organizations, forecast calls happen at multiple levels: rep to manager, manager to VP, VP to CRO, and CRO to CEO or board.

‍

The core output of a forecast call is a commit number: the revenue figure that the sales leader is confident will close in the current period, barring unforeseen circumstances. Supporting the commit is typically a best-case number (deals likely to close but not certain) and an upside number (deals that could close with a positive surprise). Together these three figures give leadership a range for the period's revenue outcome.

‍

Forecast calls are one of the highest-stakes recurring rituals in a sales organization. Only 45% of sales leaders are confident in their organization's forecast accuracy. This means most leaders are walking into these calls knowing the number they share carries significant uncertainty.

Why Forecast Calls Matter in B2B Sales

The forecast call is where pipeline data becomes a business decision. Finance plans headcount and spend against the sales number. The CEO and board set investor expectations against it. Operations plans hiring, capacity, and infrastructure against it. A missed forecast is not just a sales problem, it’s a company-wide credibility event.

‍

For sales leaders focused on forecasting accurately, the quality of the forecast call process is as important as the quality of the underlying data. The best forecast calls surface risk early, create accountability for deal progression, and give leaders enough lead time to intervene before a deal is lost. Poorly run forecast calls become exercise in wishful thinking; managers hear what reps want them to hear rather than what the data actually shows.

How to Run a High-Quality Forecast Call

1. Review the data before the call, not during it.

The forecast call should not be the first time the manager is looking at the pipeline. Prepare beforehand by reviewing deal activity, stage changes, close date movements, and any new additions or removals since the last call. Use the call for conversation and decision-making, not data discovery.

2. Focus on deals in commit, not the whole pipeline.

Do not review every deal in the funnel. Focus the call on deals the rep has committed to closing in the current period. For each committed deal, ask three questions: What is the next step? Who is the economic buyer and are they engaged? What could cause this deal to slip?

3. Ask for evidence, not opinions.

Challenge reps to ground their confidence in data: last activity date, number of stakeholders engaged, legal or procurement status, pricing conversations completed. A rep who says "I feel good about this one" should be asked: "What happened in the last seven days that gives you confidence?"

4. Track close date discipline.

The most common sign of forecast manipulation is close dates that consistently push to the end of the quarter. Flag any deal whose close date has moved more than once without a documented reason. Close date slippage is the leading indicator of a deal that is not as strong as reported.

5. Document changes and hold the team accountable.

Log what was said in the forecast call: what was committed, what was pulled back, and what the expected outcome is for each deal. Compare the actual outcome to what was forecast and use the gap as a coaching tool in the following call.

6. Separate commit from upside clearly.

Train reps and managers to apply strict criteria to their commit number. Commit should mean "I will be surprised if this does not close." Upside should mean "This could close but I cannot bank on it." Blurring this distinction is the root cause of most forecast inaccuracy.

Forecast Call Structure

Section Content Time
Pipeline review prep Manager reviews CRM data and flags issues before the call Pre-call
Commit review Rep walks through deals in commit; manager probes for evidence 50–60% of call
Upside and best case Deals that could close; key actions needed to pull them forward 20–25% of call
Risk and slippage review Deals that have moved out or gone dark; recovery plan discussion 15–20% of call
Number roll-up Final commit, best case, and upside figures for the period 5 minutes

Key Metrics and Benchmarks

Metric What It Measures Benchmark / Target
Forecast Accuracy Actual closed revenue vs. committed forecast at the start of the period Only 45% of organizations achieve >75% forecast accuracy; best-in-class target ±5%
Commit Conversion Rate Percentage of committed deals that actually close in the period Target 80–90%; below 70% indicates systemic over-commit
Close Date Slippage Rate Percentage of committed deals whose close date moved out from the call Track weekly; sustained above 20% signals data hygiene and forecast discipline issues
Upside Conversion Rate Percentage of upside deals that close in the same period Track to calibrate how much upside to add to a working forecast

Common Mistakes and How to Fix Them

Mistake Fix Impact on Revenue and Forecast
Accepting rep commit numbers without asking for supporting evidence. Build a standard evidence checklist for commit deals: last activity, economic buyer engagement, legal status, and next step with a date. Unverified commit numbers inflate the forecast; the gap between forecast and actual erodes leadership credibility with the board.
Using the forecast call as a pipeline review rather than a commit conversation. Separate pipeline review (all open deals) from forecast call (commit and upside only). Focus the forecast call exclusively on the current period's close candidates. Broad pipeline reviews eat time without improving accuracy; real forecast risk goes unaddressed.
Allowing close dates to slip without consequence or documentation. Flag every close date move in the CRM with a required reason field; review slippage patterns in coaching. Unchecked slippage creates a culture of sandbagging and makes quarter-end revenue impossible to predict.
Rolling up the forecast from bottom-line rep numbers without any independent data validation. Use pipeline analytics — deal health scores, engagement signals, stage velocity — as an independent data layer to pressure-test rep numbers. Pure rep-driven forecasts are subject to optimism bias; data-validated forecasts consistently outperform on accuracy.

Frequently Asked Questions

How often should forecast calls happen?

Most B2B SaaS organizations run forecast calls weekly at the rep-to-manager level, and bi-weekly or monthly at the VP-to-CRO level. The cadence should match your sales cycle length. Organizations with short, transactional cycles may benefit from more frequent calls; enterprise teams with 90 - 180 day cycles may find weekly calls excessive at the leadership level.

What is the difference between commit, best case, and upside?

Commit is what the rep or manager is confident will close. Best case includes commit plus deals that could close under favorable conditions. Upside refers to incremental deals beyond best case that are possible but uncertain. Different organizations use these terms differently; what matters is internal consistency and clear definitions.

How do I get reps to give honest forecast numbers instead of sandbagging or overcommitting?

The key is psychological safety combined with data accountability. Reps sandbag when they are punished for missing a commit; they overcommit when they are rewarded for big numbers regardless of outcome. Build a culture where an honest, evidence-based forecast is valued more than a confident-sounding one. And use CRM data to validate rather than contradict rep judgment.

What CRM data should I review before each forecast call?

At minimum, look at the last activity date on each commit deal, number of days in the current stage, number of unique contacts engaged, close date change history, and any pending next steps. If you have a deal health scoring tool, review those scores as a second opinion on rep-reported confidence.

How does AI improve forecast call quality?

AI-powered forecasting tools analyze deal behavior (engagement patterns, stage velocity, close date discipline, and historical win/loss signals) to generate an independent deal confidence score. This gives managers a data layer to compare against rep-reported commit, surfacing deals where rep confidence is misaligned with underlying signals before the call rather than after the miss.

‍

‍

Updated February 27, 2026

Reviewed by Ben Hale

Back to Category 

Sales Forecasting

Back to All Glossary Terms