Spreadsheet Formula Wizard — Solve Any Excel/Sheets Problem in Plain English
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Transform messy survey responses into structured insights with statistical context, themes, and actionable recommendations.
You are a research analyst who turns raw survey data into actionable insights. Analyze my results. Survey Context: - Purpose: [WHY did I run this?] - Respondents: [WHO answered? Sample size] - Type: [CSAT / NPS / Employee / Market research / Product] - Key questions: [LIST or paste] Raw Results: [PASTE SUMMARY STATS OR KEY NUMBERS] Analyze: 1. EXECUTIVE SUMMARY (3 key takeaways) 2. METRICS WITH CONTEXT (score vs benchmark, good or bad?) 3. THEME ANALYSIS (top 5 themes from open-ended, with frequency and sentiment) 4. SEGMENTATION (which groups differ?) 5. CORRELATIONS (what predicts satisfaction?) 6. STATISTICAL VALIDITY (sample size confidence, bias concerns) 7. PRIORITIZED RECOMMENDATIONS (finding → action → impact → effort) 8. PRESENTATION TEMPLATE (5-slide structure)
📋 EXECUTIVE SUMMARY: NPS 42 (above SaaS benchmark of 36), but mid-tier customers at risk due to onboarding confusion. Fixing onboarding could improve NPS by 8-12 points. 📊 METRICS: | Metric | Score | Benchmark | Status | | NPS | 42 | 36 | 🟢 | | Onboarding | 2.8/5 | 3.5 | 🔴 Critical | | Support | 4.6/5 | 4.2 | 🟢 Strength | 🎯 PRIORITY #1: Redesign self-serve onboarding Impact: NPS +8-12, churn -15% Effort: Medium (4-6 weeks)
Raw survey data is overwhelming. This applies research methodology to extract signal from noise: benchmarking, theme identification, and converting findings into prioritized actions.
After collecting any survey results, when preparing results for leadership, or when NPS/CSAT data needs the 'why' behind the numbers.
Complete analysis with summary, benchmarked metrics, themes, and prioritized recommendations.
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