Analyze bulk customer feedback to extract themes, sentiment trends, and actionable insights.
## Customer Feedback Analyzer Analyze the following customer feedback data and extract actionable insights: **Feedback Data:** [FEEDBACK_DATA] **Data Source:** [SOURCE — surveys/reviews/support tickets/social media/NPS responses] **Time Period:** [PERIOD — last week/month/quarter] **Sample Size:** [SIZE] responses **Analysis Framework:** ### 1. Sentiment Distribution - Calculate overall sentiment: Positive / Neutral / Negative (percentages) - Trend comparison vs previous period - Identify sentiment shifts and potential causes ### 2. Theme Extraction - Identify top 10 recurring themes/topics - For each theme provide: - Theme name and description - Frequency (% of feedback mentioning this) - Average sentiment within this theme - Representative quotes (3 per theme) - Trend: increasing/stable/decreasing ### 3. Pain Points Ranking - List top 5 customer pain points by severity and frequency - Impact assessment: How many customers affected? - Urgency score: 1-10 based on sentiment intensity ### 4. Positive Highlights - What customers love most (top 5 positives) - Features/aspects with highest satisfaction - Potential testimonial candidates ### 5. Actionable Recommendations For each insight, provide: - **Finding:** What the data shows - **Impact:** Business impact if addressed/ignored - **Recommendation:** Specific action to take - **Priority:** High/Medium/Low - **Owner:** Suggested team (Product/Engineering/Support/Marketing) ### 6. Executive Summary - 3-5 bullet point summary for leadership - Key metric changes - Top 3 recommended actions **Output Format:** Structured report with charts/tables where applicable.
Free to copy and use. Compatible with Claude 4 Opus, GPT-5, Gemini 2.5 Pro.
Paste customer feedback data into [FEEDBACK_DATA] for analysis.
Initial release
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