customer-research
Conduct Customer Research and Build Data-Driven Personas
Stop guessing what your customers want. This skill helps you extract actionable insights from interviews, surveys, support tickets, and online communities to build personas and messaging grounded in real customer voice.
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正在使用“customer-research”。 I have 15 customer interview transcripts. What insights can you extract about why customers buy our tool?
预期结果:
Based on the transcripts, here are the top 3 buying triggers ranked by frequency x intensity:
1. 'Embarrassing spreadsheet failure' (HIGH confidence - mentioned in 12/15 interviews)
- Quote: 'We sent a report to the CEO with the wrong numbers and had to present it'
- Trigger: Public mistake or near-miss with manual processes
2. 'Team scaling broke our old process' (MEDIUM confidence - 8/15 interviews)
- Quote: 'When we hired person #5, Google Sheets became a nightmare'
- Trigger: Crossing 5+ person team threshold
3. 'CEO asked for a report we couldn't produce' (MEDIUM confidence - 6/15 interviews)
- Trigger: Executive visibility request exposed gaps
Implications: Your messaging should lead with 'avoid embarrassing mistakes' rather than 'save time' - the emotional pain is stronger.
正在使用“customer-research”。 Mine Reddit for what people hate about project management tools.
预期结果:
From analyzing 47 Reddit threads across r/projectmanagement, r/entrepreneur, and r/SaaS:
Top pain themes:
1. 'Over-engineered for what I need' (19 threads)
- Quote: 'I just want to track tasks, not configure 47 fields'
- Quote: 'Jira feels like getting a root canal'
2. 'Steep learning curve for my team' (15 threads)
- Quote: 'Adoption failed because half my team refused to use it'
- Quote: 'Takes longer to log the task than to do it'
3. 'Too expensive for small teams' (12 threads)
- Quote: '$50/user/month is insane for a 3-person team'
Vocabulary to use: 'simple', 'setup in minutes', 'your team will actually use', 'pricing that grows with you'
安全审计
安全All 70 static analysis findings are false positives from documentation patterns. MD5 hashes in evals.json are content integrity checksums, backtick characters in markdown files are code examples, and path sequences like '../' are relative documentation links. No executable code, external commands, or security risks present in this pure documentation skill.
质量评分
你能构建什么
Product Manager Validating Feature Priorities
Analyze support tickets and interview transcripts to identify recurring pain points and validate which problems customers actually want solved before building features.
Marketing Team Building ICP Personas
Mine G2 reviews, Reddit discussions, and interview data to build detailed personas with real customer language, trigger events, and buying objections for targeting and messaging.
Founder Conducting Lean Customer Research
Use digital watering hole research techniques to gather customer intelligence from online communities when no existing research data is available, then synthesize into actionable insights.
试试这些提示
I have [number] customer interview transcripts. Help me extract jobs-to-be-done, pain points, and trigger events. My goal is to improve [messaging/product/positioning]. Here are the transcripts: [paste transcripts or describe file locations].
Research what customers say about [competitor name] on G2 and Capterra. Focus on their 4-star reviews to find what customers love but still complain about. Extract: top praise, top complaints, unmet needs, and switching triggers.
Build a persona for [role/title] at [company size/type] based on this research: [paste research data or summarize findings]. Include: profile, primary job-to-be-done, trigger events, top pains in their words, desired outcomes, objections, alternatives considered, and key vocabulary.
Help me find where [ICP description] spend time online. My product is [category/description]. I want to understand their [pains/vocabulary/objections]. Recommend specific sources (subreddits, review sites, communities) and what to search for.
最佳实践
- Always check for product-marketing-context.md file first to avoid asking questions already answered
- Label every insight with confidence level (high/medium/low) based on sample size and source consistency
- Prioritize 3-star reviews and unprompted comments over perfect 5-star reviews for authentic feedback
- Extract exact customer quotes rather than paraphrasing - gold for copywriting and messaging
- Segment research by customer profile before drawing conclusions - don't average across different use cases
- Use research from the last 12 months as primary source - markets and products shift quickly
避免
- Don't build personas from fewer than 5 data points per segment - high risk of outliers
- Don't average insights across different customer segments or churn causes - masks real patterns
- Don't treat all support tickets as equal signal - categorize by bug vs confusion vs feature request
- Don't invent persona details without data - leave fields blank rather than guessing
- Don't rely solely on quantitative survey data without open-ended context - misses the why
常见问题
What's the difference between Mode 1 and Mode 2 research?
Why do you recommend reading 3-star reviews first?
How much data do I need before building personas?
Can this skill conduct customer interviews for me?
What if I don't have any existing research data?
Why does the skill keep asking about my goal?
开发者详情
许可证
MIT
引用
main
文件结构