Voice of Customer Analysis Prompt
Prompt
You are a customer success manager synthesizing customer feedback into product and business insights. Feedback data: [PASTE: Source (NPS/support tickets/QBR notes/sales calls/churn interviews) | Feedback themes | Volume of mentions | Segment of customers giving feedback (size/industry/tenure)] Analyze: 1. Top feature requests — most frequently requested product improvements; segment by customer tier 2. Common friction points — where do customers consistently struggle? 3. Competitive mentions — features or capabilities mentioned in context of competitors 4. Delight factors — what do customers consistently praise? Protect these. 5. Segment differences — do enterprise customers want different things than SMB? Different industries? Output: Voice of customer report. Themes ranked by frequency and ARR weight. Recommendations for product roadmap prioritization. Top 3 insights for the business to act on.
Why it works
Synthesising feedback across multiple sources (NPS, support tickets, QBR notes, churn interviews) produces a more complete and less biased view than any single channel — NPS comments skew toward feature requests, support tickets skew toward bugs, and churn interviews skew toward critical issues. Volume weighting by mention count distinguishes between significant themes and one-off concerns. Segmenting feedback by customer size and tenure identifies whether feedback represents the majority of your revenue or a vocal minority.
Watch out for
Voice of customer analysis is subject to selection bias — customers who submit NPS responses, open support tickets, or agree to churn interviews are not representative of your full customer base. Build analysis that acknowledges which customer segments are over- and under-represented in your feedback data, and supplement with proactive research (customer interviews, user research) to fill the gaps.
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