Analyze Survey

/analyze-survey

Analyze survey results, following the analysis guidance in the survey-design skill.

Input: $ARGUMENTS

Workflow

1. Resolve the inputs. The results may arrive as a file path (CSV or markdown export from any survey tool), pasted data, or a file already in the repo. Find the matching survey design in product/surveys/ (or ask for it) — it carries the learning goals and the goal-per-question mapping that structure the whole analysis. Without a design file, reconstruct the apparent goals from the questions and confirm them with the user.

2. Establish the denominator. n, recruitment channel, response rate if known. State the limits up front and let every later claim inherit them; with small or self-selected samples, keep findings directional and say so.

3. Analyze per the survey-design skill, organized by learning goal, not question order: distributions for closed questions, segment cuts where screening/demographic data allows, open-ends coded into themes with mention counts and 1–2 verbatim quotes each. For each goal: what was believed, what the data shows, what decision follows.

4. Extract insights to the insight-extraction quality bar: actionable, grounded in numbers or quotes, prioritized by impact. Flag every "why" the data raises as a candidate for follow-up interviews — surveys say what, not why. When the design carried the screening + opt-in block, close the analysis with the recruitment pool: respondents who accepted a conversation, tagged by whether their answers confirm or contradict the beliefs at stake, contradictors first.

5. Present and iterate. Show the analysis; let the user challenge segment cuts or codings before saving.

6. Save to product/insights/{YYYY-MM-DD-HHMM}-{slug}.md with a header listing the survey design file, the results source, n, and source: survey.

7. Contrast against the overview's beliefs. Read the unverified beliefs in product/overview.md (skip silently if the file or section doesn't exist) — every scope alike: [product], [opportunity: {slug}], [feature: {slug}]. If a survey finding confirms or contradicts one, say so in one line, citing the analysis file, and offer to annotate the belief on its own line in the overview: — confirmed/contradicted/weakened by [analysis file] (date) (status keywords stay in English; no status = still unverified). Survey evidence comes from real people, so it can confirm or contradict — but within the limits established in step 2: with a small or self-selected sample, propose weakened rather than contradicted, and promising-in-conversation rather than confirmed. Nothing is written without the user's approval.

8. Close with the natural next step in one line: feed the findings into a spec (/write-spec), design follow-up interviews for the open "why"s recruiting from the opt-in pool (/design-interview), or — once enough real data has accumulated — derive evidence-based personas (/derive-personas).

Language

Conversation and the saved analysis in the language of the conversation.