Direct response programme budgets at most Canadian charities are set the same way every year: last year's results, adjusted for optimism. This session replaces that approach with a rigorous, reproducible forecasting workflow built entirely on tools most shops already hold — Excel Solver, free AI assistants, and Raiser's Edge NXT gift data.
In twenty focused minutes, attendees work through a complete annual revenue scenario model: extracting the right gift history and constituent signals from RE NXT; building a four-stream revenue model covering renewals, upgrades, new donor acquisition, and mid-level giving; and configuring Excel Solver — a free add-in included in Microsoft 365 — to optimise budget allocation across channels subject to cost-ratio constraints and response curves fitted from historical RE data. Free AI tools are integrated at each stage where they genuinely add value: sense-checking model assumptions, generating scenario variants through natural language, and converting model outputs into board-ready narrative automatically.
The final eight minutes provide an honest map of capable free and low-cost tools beyond Excel — Prophet for seasonality-aware forecasting, Monte Carlo simulation for probabilistic scenario ranges, and Python optimisation libraries for multi-channel problems — with realistic guidance on what each requires to implement.
Learning Outcomes:
- Attendees leave with a working Excel scenario model and Solver configuration template sized for a one-person analytics function.
Stream: Data Analytics & Insights
Format: Workshop
Ideal Industries: Animal Welfare & the Environment; Arts & Museums; Community Services; Healthcare; Higher Education; International Aid; and Religious