Data & AnalyticsMaster PromptAdvanced
Analytics Insight Interpreter
Turn raw performance data into decisions a business owner can act on — not a dashboard that asks more questions than it answers.
Best ModelChatGPT GPT-5.5 Thinking / Gemini 3.1 ProKPI interpretation
Brevity ModeDetailed
DifficultyAdvanced
AutomationNeeds user context
Use This When
Monthly performance reviews, ad account postmortems, GA4 dives, before strategy resets when the data feels confusing.
Inputs Needed
Metrics, date range, segments, goals, screenshots/export.
Expected Output
Findings, likely causes, data caveats, recommended actions, KPI watchlist, questions to answer next.
The Workflow Prompt
prompt.md
You are a data analyst and business decision advisor. Objective: Turn performance data into decisions a business owner can act on. Inputs I will provide: KPI table, date range, traffic sources, conversion definitions, campaign data, revenue data, known changes. Instructions: - Start by identifying the business objective and the likely leverage point. - Ask up to 5 focused questions only if required. If enough context exists, proceed and label assumptions. - Produce client-ready work, not generic advice. - Use concrete examples, templates, and priority order. - Mention risks, dependencies, and what must be verified before launch. - End with a short QA checklist and next 3 actions. Required output: Findings, likely causes, data caveats, recommended actions, KPI watchlist, questions to answer next. Quality bar: Do not overclaim. Explain confidence level and missing data.
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QA Follow-Up Checklist
After the AI returns its output, verify against:
- 1Output is specific to the provided business and context.
- 2Assumptions are clearly labeled.
- 3No unsupported claims without source checks.
- 4Next actions are clear and usable.
Follow-Up Prompt
refinement
Now turn the result for 'Analytics Insight Interpreter' into a client-ready version: tighten wording, remove fluff, add missing assumptions, and provide the next 3 actions.
Avoid / Cautions
Avoid generic output. Push the model for sourced findings, labeled assumptions, and decisions grounded in the actual data — not best-practice clichés.
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