Portfolio Renewal Forecasting

Individual renewal probability scores aggregate into portfolio-level renewal forecasts — the predicted retention rate, revenue retention, and net revenue retention for the upcoming period. These forecasts are critical for organizational planning: revenue projections, capacity planning, and investment decisions. A CS team that can forecast renewal rates with +/-5% accuracy is a strategic planning partner. A CS team that guesses is a cost center.

1. Calculate Expected Renewal Revenue For each account approaching renewal, multiply the annual contract value by the renewal probability. Sum across all renewing accounts to produce the expected renewal revenue. This is your best estimate of what will actually renew — more accurate than assuming 100% renewal, more useful than hoping for the best.
2. Build Scenario Models Create three scenarios: optimistic (all accounts above 60% probability renew), expected (renewal probability applied as-is), and pessimistic (only accounts above 80% probability renew). The range between optimistic and pessimistic is your forecast uncertainty. Narrowing this range through better leading indicators and scoring calibration is one of the highest-value improvements you can make.
3. Track Forecast Accuracy After each renewal period, compare the forecast against actual results. Did the expected scenario match reality? Were you systematically optimistic or pessimistic? Forecast accuracy tracking reveals calibration drift and enables continuous improvement. The CS team that tracks accuracy becomes the most reliable source of revenue prediction in the organization.