What is Sales Forecasting?
Sales forecasting is the process of predicting future revenue based on pipeline data, historical trends, and rep-level deal assessments, and it's the metric CROs are most frequently judged on.
Sales forecasting predicts how much revenue your team will close in a given period. It combines quantitative data (pipeline value, stage conversion rates, historical patterns) with qualitative judgment (rep confidence, deal momentum, competitive dynamics). Accurate forecasting is the single most visible skill that separates great CROs from average ones.
Forecasting Methods
There are four common approaches. Bottom-up: sum individual rep forecasts based on deal-level assessments. Top-down: apply historical conversion rates to current pipeline value. Weighted pipeline: multiply each deal's value by its stage probability (Stage 3 = 40%, Stage 5 = 80%). AI-assisted: tools like Clari and Gong use machine learning on historical deal data to predict outcomes. Most CROs use a combination, triangulating bottom-up rep calls with weighted pipeline and AI signals.
Forecast Accuracy Benchmarks
Best-in-class sales organizations forecast within 5-10% of actual results. The industry average is 15-25% variance. Consistent over-forecasting (sandbagging) or under-forecasting (happy ears) are both problems. CROs track forecast accuracy by rep to identify who needs coaching. A rep who misses forecast by 30% every quarter either can't qualify deals or won't give you honest assessments.
The CRO Forecasting Cadence
Most CROs run a weekly forecast cadence: Monday pipeline review with managers, Tuesday deal inspection on at-risk opportunities, Wednesday/Thursday rep-level coaching, Friday updated commit to the CEO/board. Monthly and quarterly roll-ups feed into board reporting. Our job posting data shows 'forecasting accuracy' or 'revenue predictability' mentioned in 42% of CRO postings, making it the most-cited operational capability.
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