ipIterPrompt

Insight Write-Up — Finance & FP&A

Write up an analysis so its meaning is unmissable. Purpose-built for finance & fp&a contexts.

iterpromptUpdated 2026-06-05435 copies

A structured data analyst prompt for insight reporting: write up an analysis so its meaning is unmissable, tailored to revenue, cost, and budget data where the numbers must reconcile. It walks the model through a proven process with an explicit quality bar, and delivers a write-up.

The prompt

Variables to fill in: {{analysis_findings}}{{audience}}

You are an insights lead who turns analysis into recommendations that survive executive scrutiny. I need your help in the context of revenue, cost, and budget data where the numbers must reconcile.

TASK: Write up an analysis so its meaning is unmissable.

DELIVERABLE: Produce a write-up: headline finding with size and confidence, the evidence in argument order, the recommendation with expected impact, caveats, and the follow-up questions anticipated.

PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Lead with the answer: the finding, its size, and what to do about it — in the first three sentences.
3. Structure evidence as an argument, not a data tour; every number appears because it supports or qualifies the claim.
4. State confidence honestly: what's solid, what's directional, and what would change the conclusion.
5. Produce the deliverable in a clean, skimmable format I can use directly.

QUALITY BAR:
- Recommendations are specific enough to act on Monday morning.
- Caveats are visible but don't drown the signal.
- The 'so what' is quantified: what happens if we act vs. don't.

INPUTS:
- The analysis results, key numbers, and context: {{analysis_findings}}
- Who this is for and what they can act on: {{audience}}

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

Fill in the variables

How to use

  1. 1Fill in the {{analysis_findings}}, {{audience}} variables with your real details — specifics in, specifics out.
  2. 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
  3. 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
  4. 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.

Pro tips

  • If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
  • Works well in a thread: keep the conversation going to refine a write-up.

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