什么是 客户画像？

客户画像技能使开发人员和营销人员能够构建高质量、有研究支撑的受众概况，这远远超出了基本的假设。通过利用先进的搜索能力和 AI 图像生成，该工具将人口统计、心理特征和待办事项（JTBD）综合成可操作的模板。对于那些需要用实际数据验证产品市场匹配度的人来说，它是 Openclaw Skills 库的基石。

该技能自动收集市场趋势、薪资数据和工具使用模式，允许团队创建真实的虚拟角色和详细的旅程地图。无论您是为新的 SaaS 产品定义目标受众，还是完善内容策略，该工具都能确保您的画像建立在专业的行业事实基础之上。

下载入口:https://github.com/openclaw/skills/tree/main/skills/okaris/customer-persona

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

客户画像 应用场景

• 基于实时数据，利用高保真买家画像制定营销策略。
• 通过以用户为中心的研究和心理特征分析指导产品开发。
• 创建针对量化客户痛点的销售赋能材料。
• 绘制客户旅程图，以识别销售周期中的摩擦点和购买触发因素。
• 定义反向画像以简化线索转化并避免资源浪费。

1. 使用搜索助手研究目标市场，收集人口统计数据、行业调查和当前的薪资报告。
2. 分析心理数据，识别驱动用户行为的价值观、动机和专业兴趣。
3. 量化痛点和目标，从模糊的假设转向可操作的、有数据支持的洞察。
4. 应用待办事项 (JTBD) 框架对功能、情感和社会需求进行分类。
5. 绘制购买流程图，识别触发因素、关键影响者和潜在阻碍。
6. 使用 AI 图像模型生成视觉形象，为数据概况提供人性化元素。

客户画像 配置指南

要开始使用此技能，请安装 inference.sh CLI 并登录。您还可以添加相关的 Openclaw Skills 以增强您的研究能力。

curl -fsSL https://cli.inference.sh | sh && infsh login

# 添加支持模块
npx skills add inference-sh/skills@web-search
npx skills add inference-sh/skills@ai-image-generation

客户画像 数据架构与分类体系

该技能将画像数据组织成结构化板块，以确保清晰度和专业实用性：

name: customer-persona
description: "Research-backed customer persona creation with market data and avatar generation. Covers demographics, psychographics, jobs-to-be-done, journey mapping, and anti-personas. Use for: marketing strategy, product development, UX research, sales enablement, content strategy. Triggers: customer persona, buyer persona, user persona, target audience, ideal customer, customer profile, audience research, user research, icp, ideal customer profile, target market, customer avatar, audience persona"
allowed-tools: Bash(infsh *)

Customer Persona

Create data-backed customer personas with research and visuals via inference.sh CLI.

Quick Start

curl -fsSL https://cli.inference.sh | sh && infsh login

# Research your target market
infsh app run tavily/search-assistant --input '{
  "query": "SaaS product manager demographics pain points 2024 survey"
}'

# Generate a persona avatar
infsh app run falai/flux-dev-lora --input '{
  "prompt": "professional headshot photograph of a 35-year-old woman, product manager, friendly confident expression, modern office background, natural lighting, business casual attire, realistic portrait",
  "width": 1024,
  "height": 1024
}'

Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.

Persona Template

┌──────────────────────────────────────────────────────┐
│  [Avatar Photo]                                      │
│                                                      │
│  SARAH CHEN, 34                                      │
│  Product Manager at a Series B SaaS startup          │
│                                                      │
│  "I spend more time making reports than making       │
│   decisions."                                        │
│                                                      │
├──────────────────────────────────────────────────────┤
│  DEMOGRAPHICS          │  PSYCHOGRAPHICS             │
│  Age: 30-38            │  Values: efficiency, data   │
│  Income: $120-160K     │  Personality: analytical,   │
│  Education: BS/MBA     │    organized, collaborative │
│  Location: Urban US    │  Interests: productivity,   │
│  Role: Product/PM      │    leadership, AI tools     │
├──────────────────────────────────────────────────────┤
│  GOALS                 │  PAIN POINTS                │
│  ? Ship features       │  ? Too many meetings        │
│  faster                │  ? Manual reporting (15     │
│  ? Data-driven         │    hrs/week)                │
│  decisions             │  ? Stakeholder alignment    │
│  ? Team alignment      │    is slow                  │
│  ? Career growth to    │  ? Tool sprawl (8+ apps)   │
│    Director            │  ? No single source of      │
│                        │    truth                    │
├──────────────────────────────────────────────────────┤
│  CHANNELS              │  BUYING TRIGGERS            │
│  ? LinkedIn (daily)    │  ? Peer recommendation      │
│  ? Product Hunt        │  ? Free trial experience    │
│  ? Podcasts (commute)  │  ? Integration with Jira    │
│  ? Lenny's Newsletter  │  ? Team plan pricing        │
│  ? T@witter/X           │  ? ROI calculator           │
└──────────────────────────────────────────────────────┘

Building a Persona Step-by-Step

Step 1: Research

Start with data, not assumptions.

# Market demographics
infsh app run tavily/search-assistant --input '{
  "query": "product manager salary demographics 2024 survey report"
}'

# Pain points and challenges
infsh app run exa/search --input '{
  "query": "biggest challenges facing product managers SaaS companies"
}'

# Tool usage patterns
infsh app run tavily/search-assistant --input '{
  "query": "most popular tools product managers use 2024 survey"
}'

# Content consumption habits
infsh app run exa/answer --input '{
  "question": "Where do product managers get their industry news and professional development?"
}'

Step 2: Demographics

Use ranges, not exact values. Personas represent a segment, not one person.

Step 3: Psychographics

What they think, value, and believe.

Step 4: Goals

What they're trying to achieve (both professional and personal).

Professional:
- Ship features faster with fewer meetings
- Make data-driven decisions (not gut feelings)
- Get promoted to Director of Product within 2 years
- Build a more autonomous product team

Personal:
- Leave work by 6pm more often
- Be seen as a strategic leader, not a ticket manager
- Stay current with industry trends without information overload

Step 5: Pain Points

Quantify whenever possible. Vague pain = vague persona.

? "Has trouble with reporting"
? "Spends 15 hours per week creating manual reports for 4 different stakeholders"

? "Too many tools"
? "Uses 8 different tools daily (Jira, Slack, Notion, Figma, Analytics, Sheets, Docs, Email) with no unified view"

? "Meetings are a problem"
? "Averages 6 hours of meetings per day, leaving only 2 hours for deep work"

Step 6: Jobs-to-be-Done (JTBD)

Three types of jobs:

Step 7: Buying Process

Step 8: Generate Avatar

# Match demographics: age, gender, ethnicity, professional context
infsh app run falai/flux-dev-lora --input '{
  "prompt": "professional headshot photograph of a 34-year-old Asian American woman, product manager, warm confident smile, modern tech office background, natural lighting, wearing smart casual blouse, realistic portrait photography, sharp focus",
  "width": 1024,
  "height": 1024
}'

Avatar tips:

• Match the age range, ethnicity representation, and professional context
• Use "professional headshot photograph" for realistic results
• Friendly, approachable expression (not stock-photo-stiff)
• Background suggests their work environment
• Business casual or industry-appropriate attire

The Anti-Persona

Equally important: who is NOT your customer.

ANTI-PERSONA: "Enterprise Earl"
- CTO at a 5,000+ person enterprise
- Needs SOC 2, HIPAA, on-premise deployment
- 18-month procurement cycles
- Wants white-glove onboarding and dedicated CSM
- WHY NOT: Our product is self-serve SaaS for SMB/mid-market.
  Enterprise needs would require 2+ years of product investment.

Anti-personas prevent wasted effort on customers you can't serve.

Multiple Personas

Most products have 2-4 personas. More than 4 = too many to serve well.

Validation

Personas based on assumptions are fiction. Validate with:

Common Mistakes

Related Skills

npx skills add inference-sh/skills@web-search
npx skills add inference-sh/skills@ai-image-generation
npx skills add inference-sh/skills@prompt-engineering

Browse all apps: infsh app list