Analyze customer feedback and identify trends
This Cowork prompt mass-analyzes your customer feedback (reviews, tickets, NPS, emails) to extract actionable insights. Claude identifies overall sentiment, recurring themes, critical pain points, and weak signals. Verbatims are extracted for marketing use. Recommendations are prioritized across 3 time horizons.
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
Analyse l'ensemble des retours clients contenus dans [chemin du dossier ou fichier, ex: ~/Clients/feedback/ ou ~/Clients/avis.csv].
## Types de données possibles
- Avis clients (Google, Trustpilot, App Store, etc.)
- Tickets support / conversations
- Résultats d'enquêtes NPS ou CSAT
- Commentaires sur les réseaux sociaux
- Emails de clients
- Notes de calls clients
## Analyse demandée
### 1. Sentiment global
- Score de sentiment moyen (positif / neutre / négatif en %)
- Évolution du sentiment dans le temps (si dates disponibles)
- Net Promoter Score estimé (si données suffisantes)
### 2. Thèmes récurrents
Identifie et classe les 10 thèmes les plus fréquemment mentionnés :
- Nom du thème
- Fréquence (nombre de mentions)
- Sentiment associé (positif/négatif)
- Citations représentatives (3 verbatims par thème)
### 3. Pain points critiques
Top 5 des frustrations clients, classées par :
- Fréquence de mention
- Intensité du sentiment négatif
- Impact estimé sur la rétention
- Suggestion de résolution
### 4. Points forts à valoriser
Top 5 des éléments les plus appréciés :
- Ce que les clients adorent
- Verbatims utilisables en témoignage/marketing
- Fonctionnalités ou aspects à mettre en avant
### 5. Signaux faibles
Éléments mentionnés rarement mais potentiellement importants :
- Nouvelles demandes de fonctionnalités
- Problèmes émergents
- Changements de comportement ou d'attentes
### 6. Recommandations
Plan d'action en 3 horizons :
- Immédiat (quick fixes) : 3 actions
- Court terme (1-3 mois) : 3 actions
- Moyen terme (3-6 mois) : 3 actions
Sauvegarde le rapport dans [chemin, ex: ~/Clients/rapports/analyse-feedback-{date}.md].Why this prompt works
Mass feedback analysis is an ideal Cowork use case: processing hundreds of reviews would take days manually. Theme categorization and impact/frequency ranking transform noise into actionable customer intelligence.
Use Cases
Variants
Learn more
Check the full skill on Prompt Guide to master this technique from A to Z.
View on Prompt Guide📬 Get new prompts every week
Join our newsletter and never miss a prompt.
Similar Prompts
Create a weekly summary of my activities
This prompt leverages Cowork's ability to read and analyze your local files to compile an automatic weekly review. By scanning your notes, projects, and task files, Claude produces a structured summary with productivity metrics, project progress, and pending tasks. The result is saved directly as Markdown, ready to share with your team or archive.
Build a tech watch system
This Cowork prompt structures your tech watch by analyzing your scattered sources (saved articles, notes, newsletters, bookmarks). Claude identifies strong trends and weak signals, evaluates emerging tools, and checks updates for your tech stack. The personalized training plan helps prioritize your skill development.
Generate a project status report
This Cowork prompt automates project status report creation by analyzing your files: tasks, meeting notes, deliverables. Claude identifies progress, blockers, risks, and pending decisions. The report follows standard PMO format with visual health indicators. Saved as Markdown, it's ready for distribution to your team or management.
Prepare a monthly financial report
This Cowork prompt generates a professional financial report from your accounting files (bank exports, invoices, tracking spreadsheets). Claude analyzes data, calculates KPIs, compares with previous month, and flags alerts. M+1 projections help with planning. Ideal for freelancers, small businesses, and startups without a CFO.