Statistical Quota Attainment Forecasting
The Forecast Engine projects rep and segment attainment with confidence intervals derived from multi-source signal data — not spreadsheet point estimates.
Forecast methodology built for B2B sales cycles
The Forecast Engine uses weighted signal aggregation across three data categories to project attainment probability distributions, not single-point guesses.
Signal Weighting
Each data signal (CRM stage, product engagement, support health) is weighted by its historical predictive accuracy for your specific sales motion. Weights adjust automatically as new data validates predictions.
Time-Decay Modeling
Older deal activity discounts forward in proportion to your average deal cycle. A 90-day-old engagement on a 30-day-cycle deal means something different than on a 120-day-cycle deal.
Segment Separation
Enterprise and mid-market deals run separate models. Binary close patterns in enterprise versus volume velocity in mid-market produce fundamentally different confidence distributions.
Confidence intervals your CFO will trust
We don't give you one number. We give you the number your signal data supports, with the range that honestly represents what the data can and cannot tell you.
80% Confidence Band
The outer band shows the range where 8 in 10 forecast outcomes are expected to fall given current signal data. CFOs use this as scenario planning input.
50% Confidence Median
The inner band and central line represent the most probable attainment range. This is what you cite in the QBR when asked for the base case.
Band Narrowing
Confidence bands narrow as quarter progresses. More actual activity data reduces forecast uncertainty — the model acknowledges this mathematically.
What multi-source signals change
CRM-only forecasts structurally overestimate because reps log activity; multi-source models correct for that bias.
See your first confidence interval forecast
Connect your CRM and see the Forecast Engine produce your first attainment model in 48 hours.