분석 "So What?" Method
PRO분석 "So What?" Method 완전 정복! AI가 도와줘서 효율 200% 상승. 진짜 대박임!
사용 예시
분석 “So What?” Method 막막해요. 단계별로 알려주실 수 있나요?
스킬 프롬프트
이 스킬은 findskill.ai에서 복사할 때 가장 잘 작동합니다 — 다른 곳에서는 변수와 포맷이 제대로 전송되지 않을 수 있습니다.
이 스킬 사용법
1
스킬 복사 위의 버튼 사용
2
AI 어시스턴트에 붙여넣기 (Claude, ChatGPT 등)
3
아래에 정보 입력 (선택사항) 프롬프트에 포함할 내용 복사
4
전송하고 대화 시작 AI와 함께
추천 맞춤 설정
| 설명 | 기본값 | 내 값 |
|---|---|---|
| Percentage change that triggers investigation (e.g., any metric moving ±20% gets root cause analysis) | 20% | |
| How many levels deep to segment data (e.g., source → device → browser) | 3 | |
| Historical context to examine when analyzing metric changes | 30 days | |
| Communication style: 'technical' (methodology focus), 'moderate' (findings focus), 'executive' (business impact only) | moderate | |
| Statistical significance required before claiming a finding is real | 95% | |
| Recommendation priority: 'critical' (act immediately), 'medium' (schedule within sprint), 'low' (consider for next cycle) | medium |
연구 출처
이 스킬은 다음 신뢰할 수 있는 출처의 연구를 바탕으로 만들어졌습니다:
- Consumer Insights: 'So What' & 'Now What' Data for Advantage Comprehensive article defining 'So What' as meaningful interpretation and 'Now What' as actionable strategies
- Data Interpretation: The Ultimate Guide to Turning Data Into Insights Differentiates data analysis (the 'how') from data interpretation (the 'so what?'); structured methodology
- What is website analytics? Understand customer journeys Adobe's explanation of why metrics alone fall short without interpretation and context
- What Are Website Analytics? 8 Tips for Better Website Metrics Distinguishes between metrics (answer 'what happened?') and analytics (answer 'why?' and 'what should we do?')
- Data storytelling: Adding meaning to metrics How to merge data science, visualization, and narrative to translate raw metrics into organizational impact
- How to Use Analytics to Support Data Storytelling Structure narratives around data with clear characters, setting, conflict, and resolution
- Turn Data into Actionable Insights: A Practical Guide Four-stage framework: data preparation, pattern discovery, findings communication, and action translation
- How To Fix a High Bounce Rate Without Redoing Your Site Practical bounce rate interpretation: diagnosing root causes (speed, messaging, content) and implementing targeted fixes
- Metrics Dashboards: Everything You Need to Know How metrics dashboards transform numerical data into visual insights that drive real-time decision-making
- How to answer the 'so what' questions in an analysis Community perspective from experienced data scientists on addressing 'So What?' gaps and staying business-focused