Blood Cancer UK

With event income playing such a central role in the charity’s fundraising plan, Blood Cancer UK needed a reliable way to forecast it forward. No application existed in-house that could support this kind of planning with any precision, leaving the team reliant on broad assumptions rather than a model grounded in their own participant data.

Existing planning relied on broad, top-down assumptions about how an appeal or event series would perform, with little ability to model different scenarios or see which factors were actually driving income year on year.

Adroit built EventSee, an Excel-based forecasting application underpinned by data engineered in IBM SPSS, deduplicated in Cygnus and modelled in Python. Multiple years of participant and response data were engineered into a single structure, giving the model a foundation broad enough to distinguish real patterns from one-off event quirks. Alongside the tool itself, the supporting analysis surfaced insights the charity hadn’t previously quantified.

High-value, rare fundraisers

Quantifying the impact of high-value, rare fundraisers on overall event financial performance.

Repeat participation

Establishing the value of repeat participation, and what it’s worth retaining year on year.

Fundraising pages

Confirming that participants who set up a fundraising page (e.g. via JustGiving) fundraise materially more.

Built-in scenario planning

Letting the team parameterise assumptions and immediately see the effect on forecast income, rather than rebuilding a spreadsheet model from scratch for every scenario.

EventSee has been well received internally and gives Blood Cancer UK a way to parameterise and forecast forward event income, including the probability of attracting high-value participants — turning event planning from an assumption-led exercise into a data-led one.

Blood Cancer UK now treats event forecasting as an ongoing, adjustable process rather than a once-a-year exercise, revisiting assumptions as new events and years of data come in.