ThinkWithPrompt by SynotticThinkWithPrompt

Find what extra data would strengthen my analysis

Reviews your analysis and data to pinpoint the missing information that would most improve confidence, and how to get it.

Data & AnalysisFew-ShotAdvancedSummarizeAnalyzeFill-in Template

The prompt

Review my analysis and tell me what additional data would make it more reliable or more useful. The question I'm trying to answer: [e.g. "why are renewals dropping?", "should we open a second warehouse?"] The data I have: [describe each source: what it contains, date range, level of detail - or PASTE column headers and a sample] My analysis or current conclusions: [PASTE or summarize] Decision it will support and when: [e.g. "budget decision in 3 weeks"] Data I know exists but haven't used: [e.g. "CRM notes", "survey results", "finance cost data"] Do this: 1. Identify the gaps: questions my current data cannot answer, alternative explanations I can't rule out, segments or time periods missing, and metrics measured only indirectly. 2. For each gap, name the specific data that would close it (fields, period, granularity) and the likely source (internal system, team, survey, public data, benchmark). 3. Rate each one on: impact on the conclusion, effort to get it, and time needed. 4. Point out where more data would NOT change the decision, so I don't over-collect. Return: | Gap | Why it matters | Data needed | Likely source / owner | Impact (H/M/L) | Effort (H/M/L) | Get it before deciding? | Then: - The top 3 additions, in order. - What I can responsibly conclude now with the data I have, and the caveats to state. - A short request I can send to the data owner for the top item. Do not suggest collecting personal or sensitive data without noting the privacy and consent considerations.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • PASTE or summarize
  • e.g. "budget decision in 3 weeks"
  • e.g. "CRM notes", "survey results", "finance cost data"

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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