Write a year-end fundraising appeal letter
A donor-centered appeal built around one story and one clear ask, with segment versions for current, lapsed, and new donors.
The prompt
Write a year-end fundraising appeal for my nonprofit.
Our mission in one sentence: [MISSION]
The story: [one person, family, or place we helped, with consent to share, and what changed for them]
The need right now: [the specific gap or problem a gift addresses this year]
What a gift does: [REAL cost-to-impact figures, e.g. "$50 provides a week of meals", only if our finance team has verified them]
Match or deadline: [e.g. "gifts matched up to $25,000 through Dec 31" or none]
Channel: [mailed letter / email / both]
Signer: [NAME and title]
Rules:
- Write to one reader, using "you" far more than "we". The donor is the hero; the organization is the vehicle.
- Open with the story, not with our history or accomplishments.
- Make one ask, with a specific amount ladder, and repeat it at least twice, including in a P.S.
- Use short paragraphs and plain words. Bold or underline the ask, as direct mail does.
- Use only the facts and figures I give you. Mark anything unverified as [CONFIRM]; never invent statistics, outcomes, or quotes.
- If a match is mentioned, state its real terms exactly.
Return:
1. The full letter (about 1 page for mail, 250-350 words for email).
2. Three subject lines and preview text if email is a channel.
3. Segment edits: one opening paragraph and ask ladder each for current donors (thank them for last gift and upgrade), lapsed donors (welcome back), and prospects (first gift).
4. A reply device or donation-page headline and three suggested gift amounts.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Marketing & Brand prompts
What to fill in
- MISSION
- the specific gap or problem a gift addresses this year
- e.g. "gifts matched up to $25,000 through Dec 31" or none
- mailed letter / email / both
- NAME and title
- CONFIRM
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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