customer successadvanced1320 tokens
Customer Feedback Analysis
Analyze customer feedback to extract actionable product insights
feedback-analysisnpscustomer-insightsproduct-managementsentiment-analysis
Prompt Template
You are a product analyst. Analyze customer feedback and extract actionable insights.
**Feedback Source:** {source}
**Time Period:** {time_period}
**Total Responses:** {response_count}
Analyze feedback systematically:
**1. Sentiment Analysis:**
**Overall Sentiment Distribution:**
- Positive: {positive_pct}% ({positive_count} responses)
- Neutral: {neutral_pct}% ({neutral_count} responses)
- Negative: {negative_pct}% ({negative_count} responses)
**Net Promoter Score (NPS):**
- Promoters (9-10): {promoter_pct}%
- Passives (7-8): {passive_pct}%
- Detractors (0-6): {detractor_pct}%
- **NPS Score:** {nps_score}
**Trend:** {trending_direction} (vs last period: {previous_nps})
**2. Thematic Analysis:**
**Top Themes (by mention frequency):**
**Theme 1: {theme_1}** - Mentioned {mention_count_1} times
- Sentiment: {sentiment_1}
- Sample quotes:
- "{quote_1}"
- "{quote_2}"
- Actionable insight: {insight_1}
**Theme 2: {theme_2}** - Mentioned {mention_count_2} times
- Sentiment: {sentiment_2}
- Sample quotes:
- "{quote_3}"
- "{quote_4}"
- Actionable insight: {insight_2}
**Theme 3: {theme_3}** - Mentioned {mention_count_3} times
- Sentiment: {sentiment_3}
- Sample quotes:
- "{quote_5}"
- "{quote_6}"
- Actionable insight: {insight_3}
[Continue for top 5-7 themes]
**3. Feature Requests:**
**Most Requested Features:**
| Feature | Requests | Paying Customers | MRR Impact | Priority |
|---------|----------|------------------|------------|----------|
| {feature_1} | {count_1} | {paying_1} | ${mrr_1} | High |
| {feature_2} | {count_2} | {paying_2} | ${mrr_2} | Medium |
| {feature_3} | {count_3} | {paying_3} | ${mrr_3} | High |
**Feature Request Analysis:**
**{feature_1}:**
- **Use Cases:** {use_cases}
- **User Segments:** {segments}
- **Competitive Gap:** {competitive_analysis}
- **Effort Estimate:** {effort}
- **Recommendation:** {recommendation}
**4. Pain Points:**
**Critical Pain Points (by severity & frequency):**
**Pain Point 1: {pain_1}**
- Severity: High
- Frequency: {frequency_1}
- Affected users: {affected_users_1}
- Current workaround: {workaround_1}
- Recommended fix: {fix_1}
- Impact if not fixed: {impact_1}
**Pain Point 2: {pain_2}**
- Severity: Medium
- Frequency: {frequency_2}
- Affected users: {affected_users_2}
- Current workaround: {workaround_2}
- Recommended fix: {fix_2}
- Impact if not fixed: {impact_2}
**5. Customer Segmentation:**
**Feedback by User Segment:**
**Power Users ({power_user_pct}%):**
- Top requests: {power_user_requests}
- Sentiment: {power_user_sentiment}
- Key insight: {power_user_insight}
**New Users (<30 days) ({new_user_pct}%):**
- Top requests: {new_user_requests}
- Sentiment: {new_user_sentiment}
- Key insight: {new_user_insight}
**At-Risk Users ({at_risk_pct}%):**
- Top complaints: {at_risk_complaints}
- Sentiment: {at_risk_sentiment}
- Churn risk: {churn_risk}
- Retention strategy: {retention_strategy}
**6. Competitive Insights:**
**Competitor Mentions:**
- {competitor_1}: Mentioned {mentions_1} times
- Context: "{context_1}"
- What they do better: {better_1}
- What we do better: {better_us_1}
- {competitor_2}: Mentioned {mentions_2} times
- Context: "{context_2}"
- What they do better: {better_2}
- What we do better: {better_us_2}
**7. Action Items by Priority:**
**High Priority (Next Sprint):**
1. **{action_1}**
- Why: {reason_1}
- Impact: {impact_1}
- Effort: {effort_1}
- Owner: {owner_1}
2. **{action_2}**
- Why: {reason_2}
- Impact: {impact_2}
- Effort: {effort_2}
- Owner: {owner_2}
**Medium Priority (Next Quarter):**
1. {action_3} - {reason_3}
2. {action_4} - {reason_4}
**Low Priority (Backlog):**
1. {action_5} - {reason_5}
2. {action_6} - {reason_6}
**8. Quantitative Metrics:**
**Key Metrics:**
- Response rate: {response_rate}%
- Average rating: {avg_rating}/5
- CSAT Score: {csat_score}%
- Feature adoption after feedback: {adoption_rate}%
**Correlation Analysis:**
- Usage frequency vs satisfaction: {correlation_1}
- Account size vs NPS: {correlation_2}
- Onboarding completion vs retention: {correlation_3}
**9. Feedback Loop:**
**How to Close the Loop:**
**For Positive Feedback:**
- Reply: "Thank you for the kind words! Would you be willing to write a quick review?"
- Action: Request testimonial/case study
**For Feature Requests:**
- Reply: "Thanks for the suggestion! We've added this to our roadmap. You'll be the first to know when it's ready."
- Action: Add to roadmap, tag requester
**For Complaints:**
- Reply: "I'm sorry you experienced {issue}. We're working on a fix, expected by {date}. Meanwhile, try {workaround}."
- Action: Assign to team, follow up when fixed
**10. Reporting:**
**Executive Summary:**
```
**Feedback Analysis - {time_period}**
**Overview:**
- {response_count} responses analyzed
- NPS: {nps_score} ({trend} vs last period)
- Top theme: {top_theme}
**Key Insights:**
1. {insight_1}
2. {insight_2}
3. {insight_3}
**Recommended Actions:**
1. {action_1} - Expected impact: {impact_1}
2. {action_2} - Expected impact: {impact_2}
**Risks:**
- {risk_1}
- {risk_2}
**Next Steps:**
- {next_step_1}
- {next_step_2}
```
Provide: Complete analysis + prioritized actions + executive summary.Variables to Replace
{source}{time_period}{response_count}{positive_pct}{positive_count}{neutral_pct}{neutral_count}{negative_pct}{negative_count}{promoter_pct}{passive_pct}{detractor_pct}{nps_score}{trending_direction}{previous_nps}{theme_1}{mention_count_1}{sentiment_1}{quote_1}{quote_2}{insight_1}{theme_2}{mention_count_2}{sentiment_2}{quote_3}{quote_4}{insight_2}{theme_3}{mention_count_3}{sentiment_3}{quote_5}{quote_6}{insight_3}{feature_1}{count_1}{paying_1}{mrr_1}{feature_2}{count_2}{paying_2}{mrr_2}{feature_3}{count_3}{paying_3}{mrr_3}{use_cases}{segments}{competitive_analysis}{effort}{recommendation}{pain_1}{frequency_1}{affected_users_1}{workaround_1}{fix_1}{impact_1}{pain_2}{frequency_2}{affected_users_2}{workaround_2}{fix_2}{impact_2}{power_user_pct}{power_user_requests}{power_user_sentiment}{power_user_insight}{new_user_pct}{new_user_requests}{new_user_sentiment}{new_user_insight}{at_risk_pct}{at_risk_complaints}{at_risk_sentiment}{churn_risk}{retention_strategy}{competitor_1}{mentions_1}{context_1}{better_1}{better_us_1}{competitor_2}{mentions_2}{context_2}{better_2}{better_us_2}{action_1}{reason_1}{effort_1}{owner_1}{action_2}{reason_2}{effort_2}{owner_2}{action_3}{reason_3}{action_4}{reason_4}{action_5}{reason_5}{action_6}{reason_6}{response_rate}{avg_rating}{csat_score}{adoption_rate}{correlation_1}{correlation_2}{correlation_3}{issue}{date}{workaround}{trend}{top_theme}{risk_1}{risk_2}{next_step_1}{next_step_2}Pro Tips
Look for patterns, not individual comments. Prioritize by impact + frequency. Always close the feedback loop - tell customers what you did.
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