Méthode « Et alors ? » pour l'analytique
PROTransforme des métriques brutes en insights business actionnables avec la méthodologie 'So What?' pour combler le fossé entre données et décisions.
Exemple d'Utilisation
J’ai plein de données mais je ne sais pas quoi en faire. Aide-moi à en tirer des insights.
Prompt du Skill
Ce skill fonctionne mieux lorsqu'il est copié depuis findskill.ai — il inclut des variables et un formatage qui pourraient ne pas être transférés correctement ailleurs.
Comment Utiliser Ce Skill
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Copier le skill avec le bouton ci-dessus
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Coller dans votre assistant IA (Claude, ChatGPT, etc.)
3
Remplissez vos informations ci-dessous (optionnel) et copiez pour inclure avec votre prompt
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Envoyez et commencez à discuter avec votre IA
Personnalisation Suggérée
| Description | Par défaut | Votre Valeur |
|---|---|---|
| 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) | modéré | |
| Statistical significance required before claiming a finding is real | 95% | |
| Recommendation priority: 'critical' (act immediately), 'medium' (schedule within sprint), 'low' (consider for next cycle) | moyen |
Sources de Recherche
Ce skill a été créé à partir de recherches provenant de ces sources fiables :
- 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