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lead-research

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English
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Chinese

Lead Research Skill

销售线索研究技能

Research LinkedIn prospects to gather personalization opportunities, ice breakers, and conversation starters for more effective outreach.
研究LinkedIn潜在客户，收集个性化沟通机会、破冰话题及对话开场素材，提升客户触达的有效性。

Process

流程

Step 0: Load Defaults

步骤0：加载默认设置

First, check for saved decisions:
Read 
.business_growth/sales/DECISIONS.md
if it exists. This file stores:
  • Sales Navigator availability
  • Buyer persona and problem we solve (useful for framing research)
  • Target industries (helps identify relevant talking points)
  • Competitors to avoid mentioning
If DECISIONS.md exists and has Sales Navigator info:
  • Use the saved preference, no need to ask again
  • Reference the buyer persona to focus research on relevant pain points
If DECISIONS.md doesn't exist or missing Sales Navigator: Ask: "Do you have LinkedIn Sales Navigator? It provides deeper profile insights."
Why Sales Navigator matters:
  • With Sales Navigator: Access full profile info, see who viewed them, more activity history, notes/tags
  • Without Sales Navigator: Standard profile view, may have limited visibility for non-connections
Offer to save: If user answers and no DECISIONS.md exists, offer to save this preference.
首先，检查已保存的设置：
若存在 
.business_growth/sales/DECISIONS.md
文件则读取该文件。此文件存储以下信息：
  • Sales Navigator的可用情况
  • 买家角色及我们解决的问题（有助于明确研究方向）
  • 目标行业（帮助识别相关沟通切入点）
  • 需要避免提及的竞争对手
若DECISIONS.md存在且包含Sales Navigator信息：
  • 使用已保存的偏好设置，无需再次询问
  • 参考买家角色，将研究重点放在相关痛点上
若DECISIONS.md不存在或缺少Sales Navigator信息： 询问用户：“你是否拥有LinkedIn Sales Navigator？它能提供更深入的个人资料洞察。”
Sales Navigator的重要性:
  • 拥有Sales Navigator：可访问完整的个人资料信息、查看谁浏览过其主页、更多活动历史、备注/标签
  • 没有Sales Navigator：仅能查看标准个人资料，对非联系人的可见性可能受限
提供保存选项： 如果用户给出答复且不存在DECISIONS.md文件，可提议保存该偏好设置。

Step 1: Identify Target Lead

步骤1：确定目标销售线索

If 
linkedin_url
provided:
  • Use directly for research
If 
lead_name
provided:
  • Search in campaigns under 
    .business_growth/sales/campaigns/
  • Find matching lead and get LinkedIn URL
If 
campaign_id
provided (without specific lead):
  • Load 
    LIST.md
    from 
    .business_growth/sales/campaigns/<campaign_id>/
  • Ask user which lead to research, or research all leads
If neither provided:
  1. Check for existing campaigns in 
    .business_growth/sales/campaigns/
  2. If campaigns exist, ask user:
    • (A) Create new campaign → Generate a meaningful snake_case name
    • (B) Add to existing campaign → Select from available campaigns
  3. Establish 
    campaign_id
    before proceeding
  4. Ask user for LinkedIn URL or lead name to research
若提供了
linkedin_url
：
  • 直接用于研究
若提供了
lead_name
：
  • 在 
    .business_growth/sales/campaigns/
    下的活动中搜索
  • 找到匹配的线索并获取其LinkedIn URL
若提供了
campaign_id
（未指定具体线索）：
  • 加载 
    .business_growth/sales/campaigns/<campaign_id>/
    路径下的
    LIST.md
    文件
  • 询问用户要研究哪个线索，或是否要研究所有线索
若以上信息均未提供：
  1. 检查 
    .business_growth/sales/campaigns/
    下是否存在现有活动
  2. 若存在活动，询问用户：
    • (A) 创建新活动 → 生成有意义的蛇形命名（snake_case）
    • (B) 添加至现有活动 → 从可用活动中选择
  3. 先确定
    campaign_id
    再继续
  4. 询问用户要研究的线索的LinkedIn URL或姓名

Step 2: Navigate to LinkedIn Profile

步骤2：访问LinkedIn个人资料

  1. Get browser context with 
    tabs_context_mcp
  2. Navigate to profile:
    • With Sales Navigator: Use 
      linkedin.com/sales/lead/<id>
      format for richer data
    • Without Sales Navigator: Use standard 
      linkedin.com/in/<username>
      URL
  3. Take screenshot to verify profile loaded
  4. Check for any access restrictions (may need to be connected for full profile)
  1. 使用
    tabs_context_mcp
    获取浏览器上下文
  2. 访问个人资料：
    • 拥有Sales Navigator：使用
      linkedin.com/sales/lead/<id>
      格式以获取更丰富的数据
    • 没有Sales Navigator：使用标准的
      linkedin.com/in/<username>
      URL
  3. 截图以验证个人资料已加载
  4. 检查是否存在访问限制（可能需要成为联系人才能查看完整资料）

Step 3: Extract Profile Information

步骤3：提取个人资料信息

Use 
read_page
to extract:
Basic Info:
  • Full name
  • Current title and company
  • Location
  • Profile headline
  • Connection degree
About Section:
  • Summary/bio content
  • Key themes and interests
  • Communication style
Experience:
  • Current role details
  • Previous companies
  • Career progression
  • Time in current role
Education:
  • Schools attended
  • Degrees and fields
  • Graduation years
Skills & Endorsements:
  • Top skills
  • Endorsement counts
使用
read_page
提取以下内容：
基本信息:
  • 全名
  • 当前职位与公司
  • 所在地
  • 个人资料标题
  • 人脉关联等级
关于我板块:
  • 简介/个人履历内容
  • 核心主题与兴趣
  • 沟通风格
工作经历:
  • 当前职位详情
  • 曾任职公司
  • 职业发展路径
  • 当前职位任职时长
教育背景:
  • 就读院校
  • 学位与专业
  • 毕业年份
技能与认可:
  • 核心技能
  • 认可次数

Step 4: Analyze Recent Activity

步骤4：分析近期活动

Scroll to activity section and extract:
Recent Posts (last 30 days):
  • Topics they post about
  • Engagement levels
  • Opinions and perspectives
Reactions & Comments:
  • Content they engage with
  • Thought leaders they follow
  • Interests indicated
Articles Written:
  • Published content
  • Expertise areas
滚动至活动板块并提取以下内容：
近期动态（过去30天）:
  • 发布内容的主题
  • 互动量
  • 观点与立场
互动与评论:
  • 其参与互动的内容
  • 关注的意见领袖
  • 展现出的兴趣点
发布的文章:
  • 已发布的内容
  • 专业领域

Step 5: Identify Personalization Opportunities

步骤5：挖掘个性化沟通机会

Analyze gathered data for:
Conversation Starters:
  • Recent post to reference
  • Shared connections
  • Common background (school, company)
  • Mutual interests
Pain Point Signals:
  • Job changes (new role = open to tools)
  • Company growth signals
  • Hiring activity
  • Complaints or challenges mentioned
Rapport Builders:
  • Hobbies and interests
  • Causes they support
  • Content preferences
Timing Signals:
  • Best time to reach out
  • Upcoming events
  • Recent achievements to congratulate
分析收集到的数据，挖掘以下内容：
对话开场切入点:
  • 可参考的近期动态
  • 共同联系人
  • 共同背景（院校、公司）
  • 共同兴趣
痛点信号:
  • 职位变动（新职位意味着对工具的需求可能增加）
  • 公司增长信号
  • 招聘活动
  • 提及的不满或挑战
建立 rapport 的切入点:
  • 爱好与兴趣
  • 支持的事业
  • 内容偏好
时机信号:
  • 最佳触达时间
  • 即将到来的活动
  • 近期可祝贺的成就

Step 6: Generate Ice Breakers

步骤6：生成破冰话题

Create 3-5 personalized ice breakers based on research:
Types of Ice Breakers:
  1. Content Reference: "Loved your post about X..."
  2. Shared Connection: "I see we both know Y..."
  3. Common Background: "Fellow [school/company] alum here..."
  4. Industry Insight: "Given your focus on X, thought you'd find..."
  5. Congratulations: "Congrats on the recent [achievement]..."
基于研究结果创建3-5个个性化破冰话题：
破冰话题类型:
  1. 内容参考：“很喜欢你关于X的动态……”
  2. 共同联系人：“我发现我们都认识Y……”
  3. 共同背景：“同为[院校/公司]校友……”
  4. 行业洞察：“考虑到你对X的关注，我觉得你可能会对……感兴趣”
  5. 祝贺类：“恭喜你近期取得的[成就]……”

Step 7: Save Research

步骤7：保存研究结果

Save to the campaign folder: 
.business_growth/sales/campaigns/<campaign_id>/leads/<lead_name>/research.md
Lead Naming: Generate meaningful snake_case names for leads based on their name and company (e.g., 
john_smith_acme
, 
sarah_jones_techcorp
). Keep names concise, lowercase with underscores, no special characters.
Create research file:
markdown
undefined
将结果保存至活动文件夹： 
.business_growth/sales/campaigns/<campaign_id>/leads/<lead_name>/research.md
线索命名规则：根据线索姓名与公司生成有意义的蛇形命名（例如 
john_smith_acme
、
sarah_jones_techcorp
）。命名需简洁、小写字母加下划线，无特殊字符。
创建研究文件：
markdown
undefined

Lead Research: <Full Name>

Lead Research: <Full Name>

Research Metadata

Research Metadata

  • Researched: <ISO timestamp>
  • LinkedIn: <url>
  • Campaign: <campaign_id if applicable>
  • Researched: <ISO timestamp>
  • LinkedIn: <url>
  • Campaign: <campaign_id if applicable>

Profile Overview

Profile Overview

Current Position

Current Position

  • Title: <title>
  • Company: <company>
  • Duration: <time in role>
  • Location: <location>
  • Title: <title>
  • Company: <company>
  • Duration: <time in role>
  • Location: <location>

Background

Background

  • Previous Role: <most recent previous>
  • Education: <school, degree>
  • Career Theme: <progression summary>
  • Previous Role: <most recent previous>
  • Education: <school, degree>
  • Career Theme: <progression summary>

About

About

<summary of their bio/about section>
<summary of their bio/about section>

Recent Activity (Last 30 Days)

Recent Activity (Last 30 Days)

Posts

Posts

  1. <date>: <topic/summary>
    • Engagement: <likes/comments>
    • Key quote: "<relevant excerpt>"
  2. <date>: <topic/summary>
    • Engagement: <likes/comments>
  1. <date>: <topic/summary>
    • Engagement: <likes/comments>
    • Key quote: "<relevant excerpt>"
  2. <date>: <topic/summary>
    • Engagement: <likes/comments>

Engagement Patterns

Engagement Patterns

  • Topics they engage with: <list>
  • Thought leaders followed: <names>
  • Activity level: Low / Medium / High
  • Topics they engage with: <list>
  • Thought leaders followed: <names>
  • Activity level: Low / Medium / High

Personalization Opportunities

Personalization Opportunities

Strong Signals

Strong Signals

  1. <signal with context>
  2. <signal with context>
  1. <signal with context>
  2. <signal with context>

Potential Pain Points

Potential Pain Points

  1. <inferred pain point>
  2. <inferred pain point>
  1. <inferred pain point>
  2. <inferred pain point>

Shared Context

Shared Context

  • Connections: <mutual connections>
  • Background: <shared experiences>
  • Interests: <common interests>
  • Connections: <mutual connections>
  • Background: <shared experiences>
  • Interests: <common interests>

Recommended Ice Breakers

Recommended Ice Breakers

Option 1: Content Reference

Option 1: Content Reference

"<personalized message referencing their recent post>"
Why this works: <explanation>
"<personalized message referencing their recent post>"
Why this works: <explanation>

Option 2: Industry Insight

Option 2: Industry Insight

"<message offering relevant insight>"
Why this works: <explanation>
"<message offering relevant insight>"
Why this works: <explanation>

Option 3: Mutual Connection

Option 3: Mutual Connection

"<message leveraging shared connection or background>"
Why this works: <explanation>
"<message leveraging shared connection or background>"
Why this works: <explanation>

Outreach Recommendations

Outreach Recommendations

Best Approach

Best Approach

<recommended outreach strategy>
<recommended outreach strategy>

Timing

Timing

<best time/day to reach out>
<best time/day to reach out>

Tone

Tone

<recommended communication style based on their profile>
<recommended communication style based on their profile>

Topics to Avoid

Topics to Avoid

<anything that might not resonate>
<anything that might not resonate>

Raw Notes

Raw Notes

<any additional observations> ```
<any additional observations> ```

Step 8: Report Summary

步骤8：提交研究摘要

Provide user with:
  • Key findings summary
  • Top 2-3 personalization angles
  • Recommended ice breaker
  • Suggested next steps
向用户提供以下内容：
  • 关键发现摘要
  • 2-3个核心个性化沟通方向
  • 推荐的破冰话题
  • 建议的后续步骤

Browser Tools Used

使用的浏览器工具

ToolPurpose
tabs_context_mcp
Get browser context
navigate
Go to LinkedIn profile
read_page
Extract profile content
computer
Scroll to load more content, screenshot
工具用途
tabs_context_mcp
获取浏览器上下文
navigate
访问LinkedIn个人资料
read_page
提取个人资料内容
computer
滚动加载更多内容、截图

Research Quality Tips

研究质量提示

Good Personalization

优质个性化内容的标准

  • Specific and recent (last 30 days)
  • Shows genuine interest
  • Relevant to outreach purpose
  • Not creepy or over-researched
  • 具体且时效性强（过去30天内）
  • 体现出真正的兴趣
  • 与触达目的相关
  • 不过度研究，避免引起不适

Avoid

需要避免的情况

  • Mentioning personal/family info
  • Referencing very old content
  • Being too detailed (feels stalky)
  • Generic compliments
  • Assumptions about their problems
  • 提及个人/家庭信息
  • 引用过于陈旧的内容
  • 细节过多（显得像跟踪）
  • 通用化赞美
  • 对其痛点做出假设

Integration with Campaign Execution

与销售活动执行的整合

When research is saved to a campaign lead folder:
  • {{custom}}
    token in templates can reference research findings
  • Campaign execution skill will use research for personalization
  • Higher quality outreach leads to better response rates
当研究结果保存至活动线索文件夹时：
  • 模板中的
    {{custom}}
    标记可引用研究发现
  • 销售活动执行技能会利用研究结果进行个性化设置
  • 高质量的客户触达能提升回复率