Market Research

Market Research

统一研究入口：市场面看清赛道，用户面看懂用户。

What This Skill Does

按研究交付物分为两种模式：

• 市场面 (Market Intelligence)：搜索驱动的市场趋势、市场规模（TAM-SAM-SOM）、关键玩家、机会与威胁分析，交付 market-analysis.json + Markdown 报告
• 用户面 (User Research)：访谈提纲、调研设计、用户画像与洞察，交付 user-research.json + Markdown 报告

两种模式可独立运行，也可组合执行（先市场面定赛道，再用户面定人群）。

When to Use

市场面 — activate when:

• User asks about market trends or industry developments
• Phrases like "market research", "industry analysis", "market size", "X 市场发生了什么"
• Exploring new markets or product categories
• Need to understand market dynamics before product decisions

用户面 — activate when:

• User asks about understanding user needs or behaviors
• Phrases like "user research", "talk to users", "用户想要什么", "create personas"
• Creating or updating user personas
• Analyzing user feedback or interview data
• Need to validate product ideas with real users

How It Works

1. Determine mode — 根据用户意图选择市场面、用户面或两者组合；意图不明时询问用户
2. 市场面: Define market scope → Search industry sources → Analyze trends → Assess market size (TAM/SAM/SOM) → Identify opportunities → Generate insights
3. 用户面: Define research goals → Select methods → Create instruments (interview guides, surveys) → Gather data → Analyze findings → Create artifacts (personas, journey maps, insights)

Research Modes

市场面 (Market Intelligence)

搜索驱动：所有市场数据必须来自实际搜索，禁止仅凭训练记忆输出（见 Anti-Hallucination Rules）。

分析深度：

用户面 (User Research)

研究方法：

【未验证】规则（关键约束）：没有真实用户数据（真实访谈记录、调研结果或用户提供的一手资料）时，不得把推断包装成结论：

• 所有基于推断的画像和结论必须标注【未验证】
• 同时注明所需验证方式（如"需 5+ 目标用户访谈验证"、"需 N≥100 问卷验证"）
• 推断画像可作为假设交付，但必须与真实数据得出的结论明确区分

引用行业报告、统计数据时，同样适用下方 Anti-Hallucination Rules。

Persona Template

### [Name]（verified / 【未验证】）
**Role**: [Job title] at [Company type]

**Goals**:
- [Primary goal]
- [Secondary goal]

**Pain Points**:
- [Key frustration 1]
- [Key frustration 2]

**Behaviors**:
- [Observable behavior 1]
- [Observable behavior 2]

**Quote**: *"[Direct user quote]"*（无真实引用时删除此行，禁止虚构）

**Demographics**:
- Company size: [X-Y employees]
- Tech stack: [Key tools]
- Experience level: [Years]

**Verification**: [已验证来源 / 所需验证方式]

Interview Guide Template

## Interview Questions

### Warm-up
1. Tell me about your role
2. What does a typical day look like?

### Discovery
3. How do you currently [solve problem X]?
4. What tools do you use?
5. What works well? What doesn't?

### Deep Dive
6. Walk me through the last time you [encountered problem]
7. What was frustrating about that?
8. What did you try instead?

### Closing
9. If you could change one thing, what would it be?
10. Is there anything else I should know?

Anti-Hallucination Rules (Self-Contained)

The following rules are mandatory for this skill. They are inlined here for standalone installation compatibility.

1. Mandatory Search First

输出任何市场数据前必须先使用 WebSearch/WebReader。

• 禁止仅凭训练记忆输出任何具体数据（市场规模、增长率、参与者等）
• 每个数据点必须来自实际搜索和访问的页面
• 搜索查询应包含年份，例如 SaaS project management market size 2025 2026

2. Every Claim Must Have a Source

每个数字、趋势、参与者必须有 URL 来源。

• 没有来源 = 不得写入
• 来源格式：{ "claim": "...", "source": "https://...", "source_name": "...", "fetched_at": "..." }

3. Unknown is Acceptable

找不到数据时标注 "Unknown"，禁止编造。标注未知是诚实，不是失败。

4. Confidence Rating

每个关键数据点标注 confidence (high/medium/low)。

• high: 权威来源（Gartner, Forrester, IDC, 官方财报）
• medium: 可靠来源（TechCrunch, Statista, 行业报告）
• low: 社区讨论、博客、推测性分析

5. Distinguish Fact from Inference

明确区分已验证事实和推断。推断必须标注 basis 和 confidence。

6. Quality Gate (Non-negotiable)

以下任一条未满足，不得输出结果：

• 所有具体数字/趋势声明都有来源 URL
• 无法验证的数据已标注 "Unknown"
• 每个数据点标注了 confidence 等级
• facts 和 inferences 已明确区分
• 搜索记录已附在输出中

Search Record

每个分析输出必须附带搜索记录：{ "search_queries_used": [...], "sources_accessed": [{ "url": "...", "title": "...", "used_for": "..." }] }

Input Parameters

Evidence Discipline (证据纪律)

1. 缺失信息标记【待确认】：任何无法从输入或上下文获得的信息，标记为【待确认】，不得脑补填默认值。
2. 证据追溯【未验证】：用户需求/市场断言必须追问证据来源；无证据的标记为【未验证】并注明所需验证方式。
3. 完整度检查门：正式输出交付物前，先输出信息完整度清单（已确认 ✅ / 待确认 ⚠️ / 未验证 ❓），经用户确认后才生成正文。
4. 可追溯：正式输出中的关键结论必须能追溯到以下来源之一：已确认的用户输入、引用的证据（含 URL）、或用户的显式决策；无法追溯的结论视为脑补，删除或改标【待确认】。

Output Structure

每种模式生成两个输出；JSON 文件名为下游契约（contracts/ 与其他 skill 按此引用），不得改名：

1. 市场面 → docs/product/.ompm/market-analysis.json（结构化数据）+ Markdown 报告
2. 用户面 → docs/product/.ompm/user-research.json（结构化数据）+ Markdown 报告

market-analysis.json Format

{
  "analysis": {
    "id": "uuid",
    "timestamp": "2026-03-12T...",
    "market": "SaaS project management",
    "market_size": {
      "tam": { "value": "$10B", "confidence": "high", "source": { "url": "https://...", "source_name": "Gartner", "fetched_at": "2026-03-12T..." } },
      "sam": { "value": "$3B", "confidence": "high", "source": { "url": "https://...", "source_name": "IDC", "fetched_at": "2026-03-12T..." } },
      "som": { "value": "$300M", "confidence": "medium", "source": { "url": "https://...", "source_name": "Internal estimate", "fetched_at": "2026-03-12T..." } }
    },
    "growth_rate": { "value": "15% CAGR", "confidence": "high", "source": { "url": "https://...", "source_name": "Forrester", "fetched_at": "2026-03-12T..." } },
    "key_trends": [
      { "trend": "AI-powered automation", "confidence": "high", "source": { "url": "https://...", "source_name": "TechCrunch", "fetched_at": "2026-03-12T..." } }
    ],
    "key_players": [
      { "name": "Asana", "market_share": "20%", "confidence": "high", "source": { "url": "https://...", "source_name": "Statista", "fetched_at": "2026-03-12T..." } }
    ],
    "opportunities": [
      { "opportunity": "Small business segment underserved", "confidence": "medium", "basis": "Based on competitor focus analysis" }
    ],
    "threats": [
      { "threat": "Market saturation in mid-market", "confidence": "high", "source": { "url": "https://...", "source_name": "Gartner", "fetched_at": "2026-03-12T..." } }
    ]
  },
  "search_record": {
    "search_queries_used": ["SaaS project management market size 2025 2026"],
    "sources_accessed": [{ "url": "https://...", "title": "Market Report 2025", "used_for": "market size data" }]
  },
  "last_updated": "2026-03-12T..."
}

市场面 Markdown Report Structure

# Market Intelligence Report

## Market Overview
- **Market**: SaaS Project Management
- **Date**: YYYY-MM-DD
- **Geography**: Global

## Market Size
| Segment | Size | Confidence | Source |
|:--------|-----:|:-----------|:-------|
| TAM | $10B | high | Gartner, 2025 |
| SAM | $3B | high | IDC, 2025 |
| SOM | $300M | medium | Internal estimate |

## Key Trends
1. **AI-Powered Automation** - Teams are demanding AI assistance for task management...
2. **Remote Work Collaboration** - Post-pandemic shift continues driving demand...
3. **Industry-Specific Solutions** - Generic tools losing ground to vertical products...

## Key Players
| Company | Market Share | Strength | Weakness |
|:--------|-------------:|:---------|:---------|
| Asana | 20% | Enterprise features | Expensive |
| Monday.com | 18% | UX simplicity | Limited customization |

## Opportunities
- **Small Business Segment**: Underserved by enterprise-focused tools
- **Integration Ecosystem**: Gaps in connecting with specialized tools

## Threats
- Market saturation in mid-market segment
- Platform vendors (Microsoft, Google) adding features

## Strategic Recommendations
1. Focus on small business segment for growth
2. Build deep integrations with developer tools
3. Consider vertical specialization (e.g., for agencies)

user-research.json Format

{
  "research": {
    "id": "uuid",
    "timestamp": "2026-03-12T...",
    "goal": "Understand onboarding pain points",
    "method": "interviews",
    "participants": 8,
    "personas": [
      {
        "name": "Product Manager Alice",
        "role": "PM at B2B SaaS",
        "goals": ["Ship features faster", "Align team"],
        "pain_points": ["Too many tools", "Unclear priorities"],
        "behaviors": ["Checks Jira first thing", "Prefers async comms"],
        "confidence": "medium",
        "verification_status": "verified",
        "verification_method": "8 场真实访谈交叉验证",
        "source": { "type": "interview", "url_or_reference": "interview-2026-03-12-01", "fetched_at": "2026-03-12T..." }
      },
      {
        "name": "Hypothetical Startup PM",
        "verification_status": "未验证",
        "verification_method": "需 5+ 目标用户访谈验证",
        "confidence": "low",
        "basis": "基于市场面用户细分推断，无真实访谈数据"
      }
    ],
    "key_insights": [
      { "insight": "Users spend 40% of time context-switching between tools", "confidence": "high", "evidence_count": 6, "total_participants": 8 }
    ],
    "quotes": [
      { "user": "PM Alice", "quote": "I just wish everything was in one place", "source": "interview-2026-03-12-01" }
    ],
    "recommendations": [
      "Add integrations with popular tools",
      "Simplify onboarding flow"
    ]
  },
  "search_record": {
    "search_queries_used": ["B2B SaaS PM user pain points study 2025"],
    "sources_accessed": [{ "url": "https://...", "title": "...", "used_for": "industry benchmark data" }]
  },
  "last_updated": "2026-03-12T..."
}

用户面 Markdown Report Structure

# User Research Report

## Research Overview
- **Goal**: Understand onboarding pain points
- **Method**: User Interviews
- **Participants**: 8 users
- **Date**: YYYY-MM-DD

## User Personas

### Product Manager Alice（verified）
**Role**: PM at B2B SaaS company (50-200 employees)

**Goals**:
- Ship features faster without breaking things
- Keep team aligned on priorities

**Pain Points**:
- Too many tools to check (Jira, Slack, GitHub, Notion)
- Unclear priorities lead to context-switching

**Behaviors**:
- Checks Jira first thing every morning
- Prefers async communication over meetings

**Quote**: *"I just wish everything was in one place instead of checking 5 different apps."*

**Verification**: 8 场真实访谈交叉验证

### Hypothetical Startup PM【未验证】
**Role**: PM at early-stage startup

**Pain Points**:
- [推断项] 资源有限，一人多角

**Verification**: 基于市场面用户细分推断，需 5+ 目标用户访谈验证

## Key Insights

### Insight 1: Context-Switching Friction
**Finding**: Users spend 40% of time switching between tools
**Evidence**: 6/8 participants mentioned this as top frustration
**Opportunity**: Unified workspace could save hours daily

## Recommendations

1. **Short-term**: Add status page showing all work in one view
2. **Medium-term**: Build integrations with Jira, GitHub, Slack
3. **Long-term**: Create AI-powered priority recommendations

## Next Steps
- [ ] 验证【未验证】画像：完成 5+ 目标用户访谈
- [ ] Run A/B test on simplified onboarding

Quality Standards

市场面：

• Cover market size (TAM/SAM/SOM) — use "Unknown" if not found, do NOT fabricate
• Identify real trends found through search (no minimum count required)
• List major players found in search results
• Provide actionable opportunities based on real data
• Note significant threats

用户面：

• Include 3+ personas (if applicable) — base on real data, do NOT fabricate
• 无真实用户数据时，所有推断画像/结论已标注【未验证】并注明所需验证方式
• Provide real insights with evidence counts from actual research
• Include direct user quotes with source references（无真实引用则不引用，禁止虚构）
• Link insights to actionable recommendations

通用：

• ALL numeric claims, market sizes, growth rates, industry benchmarks have source URLs
• ALL data points have confidence rating (high/medium/low)
• Facts and inferences are clearly distinguished
• Search record is included proving searches were executed
• 完整度检查门已通过（Evidence Discipline 第 3 条：已确认 ✅ / 待确认 ⚠️ / 未验证 ❓ 清单经用户确认）
• Be valid JSON for downstream skills

Context Integration

Reads:

• docs/product/.ompm/market-analysis.json — 用户面复用市场上下文（组合执行时）

Writes:

• docs/product/.ompm/market-analysis.json — 市场分析结果（契约文件名，供下游 skill 使用）
• docs/product/.ompm/user-research.json — 用户研究结果（契约文件名，供下游 skill 使用）

Read By:

• product-strategy — Uses market data and personas for positioning strategy
• competitive-analysis — References key players for comparison
• prd-gen — References user needs and market opportunities in requirements

Example Usage

User: "What's the market for AI writing assistants?"
→ 市场面：搜索驱动分析该市场，输出 market-analysis.json

User: "Research the project management software market"
→ 市场面，focus on SaaS PM tools

User: "Is the fitness app market growing?"
→ 市场面，depth=overview

User: "Create personas for our product"
→ 用户面，method=personas；无真实数据时画像标注【未验证】并注明验证方式

User: "Analyze these user interviews"
→ 用户面，分析用户提供的访谈数据（真实数据，可直接得出结论）

User: "先研究下市场规模，再帮我做用户画像"
→ 组合执行：市场面 → 用户面

Execution Profile (执行建议)

• 模型建议：轻量(haiku 级)——宿主支持多模型/子代理时按此分配；单模型宿主忽略
• 工具姿态：读写 + 联网搜索——遵循最小权限
• 记忆文件：docs/product/.ompm/memory/market-research.md——跨会话积累经验（优质信源、领域基线、分析框架）；执行开始时读取、结束时更新；文件不存在则新建
• Claude Code 增强：本 profile 在该宿主由 market-researcher subagent 以隔离上下文实现

下一步

本 skill 完成后，如果用户没有明确下一步，引导用户使用 ompm skill 做意图路由——它会读取本轮产出和当前状态，判断最有价值的下一步。不要替用户预设固定长链；output-to 声明的是数据流向，不是强制路径。