What to do with survey answers
The scores are in — now turn them into decisions rather than a slide with a number.
The prompt
You are a product analyst. Work through survey responses. What you asked: {the wording} Scores and comments: {paste} How many answered, out of how many: {numbers} Product: {what it is} Work through: 1. Who answered. Extremes answer — the delighted and the furious. The middle stays silent and is absent from this data. 2. Themes in the comments with mention counts. One mention is not a theme. 3. What you actually intend to fix and what you do not. A list nobody intends to build is worse than no list. 4. Who to reply to personally and what to say: a low score with a coherent comment is a free interview, if you write the same day. 5. What to do with high scores: ask for a review or a referral, but not in the same email where you thank them. 6. One product change for the coming month. 7. What to ask next time so the data is more useful. The score itself decides nothing. The comments decide, and so does who wrote them: a complaint from a large customer and one from a free plan are worth different amounts.
Anything in curly braces is yours to replace.
Example output
84 of 1,200 answered — 7%. Almost no middling scores; this is not a picture of the base. Themes: slow search (19 mentions), no dark mode (11), plan is unclear (9). Fixing: search. Dark mode already exists — so it is not being found, which is a different problem. Reply personally: the 6 people scoring 3-5 with a coherent comment, today. Next time ask: what they did in the product this week.
Related prompts
Your idea broken down into risks plus a one-week test plan — before you spend months.
You are a product strategist who has seen plenty of projects die. Assess my SaaS idea honestly, without cheering me on. Idea: {what the service does} For whom: {who, as narrowly as possible} What the person does today without us: {how the job gets done now} How I plan to charge: {model and price} Time and money I can spend before first revenue: {resources} Break it down: 1. The problem: does it hurt regularly, or is it a one-off inconvenience? Answer plainly. 2. Who pays: the user themselves or their manager — and why that changes the product. 3. The three main risks: why this could fail. For each — the cheapest way to test it. 4. What already exists on the market, including a spreadsheet, a notebook and "do nothing" — count those as competitors too. 5. The most dangerous assumption: the one that makes everything else pointless if it's wrong. 6. A one-week test plan: what to do on which day to get a signal without writing code. 7. The kill criterion: what result means the idea should be dropped. If the idea is weak, say so in the first paragraph.
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Most dangerous assumption: that the bookkeeper is allowed to change tools. The finance director decides, not them — so you sell "fewer reporting errors", not "more convenient". Kill criterion: if fewer than 3 out of 20 conversations end in "let me try it", drop the idea.
The smallest set of features you can already sell, plus what's deferred and why.
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Do it by hand: PDF export is done by support on request for the first months. Three requests a week is one hour; automating it would have cost two weeks. Boundary for the site: "We don't replace your accountant — we prepare the data for them."
A feature turned into tasks with testable criteria — including errors and empty states.
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