AI forecasting: how to accurately predict your revenue 90 days ahead
e-Signal's AI forecasting models analyze your sales history, active campaigns and market trends to give you a clear view of what's ahead.
How our forecasting model works
e-Signal Forecast combines three data sources: your sales history (at least 90 days), the real-time behavior of your pipeline (active leads, intent score, conversion stage), and external signals calibrated for West Africa (seasonality, local public holidays, economic cycles). The model is retrained every night.
Reading and interpreting your forecast curve
Your dashboard shows three curves: the central forecast (solid line), the lower bound at 85% confidence, and the upper bound. The gap between the bounds measures market uncertainty. A narrow gap points to a stable pipeline; a wide gap signals sources of volatility to address first.
Using the forecast to make decisions
The real value of a forecast isn't the prediction itself, but the decisions it makes possible. If your 30-day forecast is 20% below target, you still have time to launch a follow-up campaign, rethink your segmentation or bring in extra sales resources. Reacting on the day is impossible; reacting 30 days ahead changes everything.
Accuracy measured over 12 months of customer data
Across all our customers with at least 6 months of history, our MAE (mean absolute error) over a 30-day horizon is 8.3%. Over 90 days, it rises to 14.7%. These figures beat the CRM SaaS benchmarks published by Gartner for emerging markets.
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