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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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