See how Forecast turns operating history into clear projections, confidence ranges, assumptions, and plans a team can act on.
Forecast predicts demand for each of 240 SKUs for the next 12 weeks with confidence intervals. The ops team right-sizes purchase orders, reducing overstock by 31% and stockouts by 44% in Q4.
Forecast learns the normal churn pattern and alerts customer success whenever actual churn deviates more than 1.5 standard deviations from baseline. The team intervenes with at-risk accounts three to four weeks earlier than before.
Forecast pulls invoicing data from accounting software via API, cleans it for seasonality, and produces a 6-month rolling revenue forecast by service line. The pipeline runs on the 1st of each month, board meetings no longer open with a 30-minute argument over which Excel is correct.
Forecast predicts footfall by location and daypart for the next four weeks using historical covers, reservations, and a local-events calendar. Managers set rotas with 25% less overtime while maintaining service, saving roughly £18K a month across the group.
Forecast the scenario: "what if we shift 20% of paid search budget to LinkedIn?" Feed in 24 months of weekly spend and lead data across six channels; the model predicts MQL impact with 84% historical accuracy. Allocation decisions are data-backed in hours, not weeks.