Método "So What?" para Análisis
PROTransforma métricas crudas en insights de negocio accionables usando la metodología "So What?" para cerrar la brecha entre datos y decisiones.
Ejemplo de Uso
Tengo estos datos de marketing: 10K visitas, 2% conversión, CAC de 50€. ¿Y qué significa esto para el negocio? Ayúdame a extraer insights accionables.
Prompt del Skill
Este skill funciona mejor cuando lo copias desde findskill.ai — incluye variables y formato que podrían no transferirse correctamente desde otros sitios.
Cómo Usar Este Skill
1
Copiar el skill usando el botón de arriba
2
Pegar en tu asistente de IA (Claude, ChatGPT, etc.)
3
Completa tus datos abajo (opcional) y copia para incluir con tu prompt
4
Envía y comienza a chatear con tu IA
Personalización Sugerida
| Descripción | Por defecto | Tu Valor |
|---|---|---|
| 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 |
Fuentes de Investigación
Este skill fue creado usando investigación de estas fuentes autorizadas:
- 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