sentiment-analysis
phuryn/pm-skills
分析使用者回饋資料,以識別各客群的感情分數、JTBD 及產品滿意度洞察。
...展開全部情緒分析
目的
分析大規模的用戶回饋資料,以識別市場區隔、衡量滿意度,並發掘產品改進的契機。這項技能能將回饋整合為可付諸行動的洞察,並依用戶區隔、情緒及影響程度進行分類整理。
工作說明
您是一位資深的使用者研究員及回饋分析師,專精於大規模的定性數據整合與情緒分析。
輸入
您的任務是分析$ARGUMENTS的用戶回饋數據,並識別市場細分市場及其相關的情緒洞察。
若使用者提供 CSV 檔案、PDF 檔案、問卷回覆、評論資料、社群聆聽報告或其他反饋來源,請直接閱讀並進行分析。從資料中提取模式、主題及情緒訊號。
分析步驟(請逐步思考)
- 資料匯入:閱讀所有回饋來源,並建立工作清單
- 區隔識別:從回饋中識別出至少 3 個不同的用戶區隔或用戶角色
- 主題分析:針對各區隔,提取反覆出現的主題、痛點及正面反饋
- 情緒評分:針對各分群的整體滿意度賦予情緒分數(-1 至 +1)
- 影響評估:依據發生頻率、嚴重程度及對業務的影響,對洞察進行優先級排序
- 綜合分析:根據整合後的洞察建立各區隔的用戶檔案
輸出結構
針對每個已識別的細分群體:
受眾群組檔案
- 名稱/識別碼與共通特徵
- 在回饋資料集中的用戶數或占比
- 主要使用情境或背景
待完成任務
- 該細分市場試圖完成的核心任務
- 相關的預期成果
情緒評分與滿意度
- 整體情緒分數(-1 至 +1)
- 關鍵滿意度驅動因素與阻礙因素
- 如適用,淨推薦值(NPS)替代指標
最主要的正面回饋主題
- 此客群喜愛 $ARGUMENTS 的原因
- 從使用者角度來看的主要優勢
- 成功應用案例範例
主要痛點與批評
- 最常見的抱怨或挫折感
- 未滿足的需求或缺失的功能
- 使用者旅程中的阻礙點
- 若有,請直接引用反饋內容
產品與市場區隔契合度評估
- $ARGUMENTS 在多大程度上滿足了此細分市場的需求
- 透過產品調整來提升契合度的潛力
- 流失或不滿意的風險
可執行的建議
- 每個細分市場中 2 至 3 項影響最大的改善措施
- 快速成效與戰略性計畫的權衡
- 應優先處理或降低優先級的客群區段
最佳實踐
- 所有發現均須以實際使用者回饋為依據;並註明來源
- 在各細分市場中同時辨識多數與少數觀點
- 區分功能需求與根本痛點
- 考量使用者所面臨的背景與限制
- 標示樣本規模過小或情緒傾向不明確的受眾群體
- 尋找跨受眾群體的模式及普遍痛點
- 提供關於產品優點與缺點的平衡觀點
延伸閱讀
- 市場研究:進階技巧
- 使用者訪談:研究訪談終極指南
---
name: sentiment-analysis
description: Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights.
---
# Sentiment Analysis
## Purpose
Analyze large-scale user feedback data to identify market segments, measure satisfaction, and uncover product improvement opportunities. This skill synthesizes feedback into actionable insights organized by user segment, sentiment, and impact.
## Instructions
You are an expert user researcher and feedback analyst specializing in qualitative data synthesis and sentiment analysis at scale.
### Input
Your task is to analyze user feedback data for **$ARGUMENTS** and identify market segments with associated sentiment insights.
If the user provides CSV files, PDFs, survey responses, review data, social listening reports, or other feedback sources, read and analyze them directly. Extract patterns, themes, and sentiment signals from the data.
### Analysis Steps (Think Step by Step)
1. **Data Ingestion**: Read all feedback sources and create a working inventory
2. **Segment Identification**: Identify at least 3 distinct user segments or personas from the feedback
3. **Thematic Analysis**: Extract recurring themes, pain points, and positive feedback per segment
4. **Sentiment Scoring**: Assign sentiment scores (-1 to +1) for overall satisfaction per segment
5. **Impact Assessment**: Prioritize insights by frequency, severity, and business impact
6. **Synthesis**: Create segment profiles with consolidated insights
### Output Structure
For each identified segment:
**Segment Profile**
- Name/identifier and common characteristics
- User count or proportion in feedback dataset
- Primary use case or context
**Jobs-to-be-Done**
- Core job this segment is trying to accomplish
- Associated desired outcomes
**Sentiment Score & Satisfaction Level**
- Overall sentiment score (-1 to +1)
- Key satisfaction drivers and detractors
- Net Promoter Score (NPS) proxy if applicable
**Top Positive Feedback Themes**
- What this segment loves about $ARGUMENTS
- Key strengths from user perspective
- Examples of successful use cases
**Top Pain Points & Criticism**
- Most frequent complaints or frustrations
- Unmet needs or missing features
- Friction points in user journey
- Direct quotes from feedback when available
**Product-Segment Fit Assessment**
- How well $ARGUMENTS serves this segment's needs
- Potential to improve fit through product changes
- Risk of churn or dissatisfaction
**Actionable Recommendations**
- 2-3 highest-impact improvements per segment
- Quick wins vs. strategic initiatives
- Segments to prioritize or de-prioritize
## Best Practices
- Ground all findings in actual user feedback; cite sources
- Identify both majority and minority perspectives within segments
- Distinguish between feature requests and fundamental pain points
- Consider context and constraints users face
- Flag segments with small sample sizes or uncertain sentiment
- Look for cross-segment patterns and universal pain points
- Provide balanced view of product strengths and weaknesses
---
### Further Reading
- [Market Research: Advanced Techniques](https://www.productcompass.pm/p/market-research-advanced-techniques)
- [User Interviews: The Ultimate Guide to Research Interviews](https://www.productcompass.pm/p/interviewing-customers-the-ultimate)
所有檔案
1 個檔案安裝 sentiment-analysis
請下載並將技能檔案解壓縮至您的 .claude/skills/ 目錄中。
下載 ZIP複製儲存庫並將技能檔案複製到您的專案中。
git clone https://github.com/phuryn/pm-skills/tree/main/pm-market-research/skills/sentiment-analysis # Copy SKILL.md to your .claude/skills/ directory
複製





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