Donor/Revenue Stream Forecasting

This use case explains how to forecast donations, membership income and other revenue streams for not-for-profit and education organisations in Model Reef.

You will:

  • Segment income streams by donor type, product or channel.

  • Model donor counts, retention, upgrade and acquisition.

  • Forecast memberships, events and earned revenue.

  • Connect income streams to programs and group level reporting.

Model Reef is not a donor CRM. It sits above CRM and fundraising tools, using aggregated metrics and imported data to drive financial forecasts.

When to use this pattern

Use this pattern when:

  • You rely on a mix of grants, donations, memberships, events and earned income.

  • You want to understand how donor behaviour drives revenue.

  • You need to test campaigns, pricing and retention strategies.

  • You want fundraising and earned income assumptions integrated with program costs and cash planning.

It is often used alongside:

  • Grant Funding Models

  • Program Cost Modelling

  • Multi Program Consolidated Reporting

Architecture overview

Donor and revenue stream forecasting uses:

  1. Income stream segmentation

    • Individual donors, major donors, corporates, trusts and foundations.

    • Memberships, events, courses or products.

    • Channels such as digital, mail, face to face or corporate partnerships.

  2. Donor and customer drivers

    • Donor or member counts by segment.

    • Retention, upgrade and acquisition rates.

    • Average gift or spend per donor, member or transaction.

  3. Revenue variables

    • Revenue per segment and channel.

    • One off versus recurring streams.

    • Timing of receipts.

  4. Financial outputs

    • Income by source and program.

    • Channel performance metrics.

    • Cashflow and volatility patterns.

1

Step 1: Define revenue segments and channels

Create a list of income streams that matter for planning, such as:

  • Individual regular giving.

  • Individual one off donations.

  • Major donors.

  • Corporate giving and sponsorship.

  • Trusts and foundations.

  • Memberships or subscriptions.

  • Events and campaigns.

  • Course fees or tuition.

  • Merchandise or other earned income.

For each stream, decide whether it will live in:

  • A program branch, where it is directly linked to a program, or

  • A central fundraising or revenue branch, where it supports multiple programs.

2

Step 2: Create donor and customer drivers

In the Data Library, create time series drivers such as:

  • Number of Regular Givers.

  • Average Monthly Gift - Regular Givers.

  • Number of One Off Donors per Campaign.

  • Average One Off Gift.

  • Number of Members and Average Membership Fee.

  • Event Attendees and Average Ticket Price.

Where relevant, also define behavioural drivers:

  • Retention Rate - Regular Givers.

  • Upgrade Rate - Regular Givers.

  • Acquisition Rate or new donor counts.

  • Churn Rate - Members.

You can implement these as direct level drivers (counts and amounts per period) or as transition drivers that change the counts over time.

3

Step 3: Build revenue variables per stream

For each segment, create Revenue type variables, for example:

  • Revenue - Regular Giving.

  • Revenue - One Off Giving.

  • Revenue - Major Donors.

  • Revenue - Membership Fees.

  • Revenue - Events.

  • Revenue - Course Fees.

Define formulas such as:

  • Revenue - Regular Giving = Number of Regular Givers × Average Monthly Gift × 12 for annual models, or times the number of periods in each period.

  • Revenue - Membership Fees = Number of Members × Average Membership Fee per Period.

For events and campaigns, you can model:

  • Number of events.

  • Average attendees per event.

  • Average revenue per attendee.

These variables will flow into P&L and cash once timing is configured.

4

Step 4: Apply timing and payment methods

For each revenue variable, define timing rules that reflect how cash arrives, for example:

  • Regular giving debits at the start or end of each month.

  • Online donations cleared within a few days.

  • Direct debit batches with a small delay.

  • Event ticket sales occurring ahead of the event date.

  • Course fees collected up front or per term.

Set delays or schedules so that:

  • Revenue is recognised when earned in P&L.

  • Receivables or deferred income appear on the Balance Sheet where appropriate.

  • Cashflow and Cash Waterfall reflect actual inflows.

This allows you to see the impact of revenue seasonality and the lag between campaign activity and cash received.

5

Step 5: Map revenue streams to programs and purposes

To understand how revenue supports program activity:

  • Use branches to link revenue streams directly to programs where restricted.

  • Represent unrestricted or general funds in a central branch and allocate them conceptually to programs in reporting views.

  • Tag revenue variables with program or purpose where a single stream supports multiple areas.

Custom reports and dashboards can then show:

  • Income by source per program.

  • Share of restricted versus unrestricted funding.

  • Dependence on particular donor types or channels.

This supports risk assessment and communication with funders and boards.

6

Step 6: Use scenarios for campaigns and behaviour changes

Clone the base model into scenario models to explore situations such as:

  • Increased investment in acquisition campaigns.

  • Changes in retention or upgrade rates.

  • Loss of a major donor or partner.

  • Introduction of new revenue products, memberships or events.

  • Macro shocks that reduce giving or course enrolments.

In each scenario, adjust:

  • Donor and member counts.

  • Behavioural drivers (retention, upgrade, churn).

  • Average gift or spend per donor, member or customer.

  • Campaign volumes and cost where linked to program or fundraising costs.

Compare scenarios using:

  • Total income by stream and in aggregate.

  • Volatility and concentration of income.

  • Cash runway and reserves.

  • Ability to fund program portfolios over time.

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Check your work

  • Donor, member and customer counts reflect recent history when the model is calibrated.

  • Average gift and behavioural assumptions are realistic, based on internal data or benchmarks.

  • Revenue timing assumptions match actual payment patterns.

  • The model is segmented enough to be useful but not so granular that it is hard to maintain.

Troubleshooting

chevron-rightIncome appears too smooth compared with historyhashtag

Introduce seasonality or campaign effects and adjust timing so that peaks align with typical fundraising or enrolment periods.

chevron-rightScenario results are hard to interprethashtag

Focus on a limited number of key segments for scenario analysis and keep minor streams grouped for simplicity.

chevron-rightDependence on a small number of donors is not obvioushashtag

Use dashboards that highlight concentration, such as top ten donor or partner contributions, even if these are modelled at aggregated levels.

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