linkedin-sales-navigator-alt
LinkedInプロファイルを分析して役職・企業・所在地・最近のアクティビティを抽出し、ターゲットを絞った見込み客リストを構築します。意思決定者の特定、転職情報のトラッキングによるウォームアプローチ、連絡先データの拡充に対応します。見込み客の発掘、リードリストの作成、意思決定者の動向把握が必要な際にご活用ください。
description の原文を見る
Build targeted prospect lists by analyzing LinkedIn profiles, extracting job titles, companies, locations, and recent activity. Identifies decision-makers, tracks job changes for warm outreach, and enriches contact data. Use when users need to find prospects, build lead lists, or track decision-maker movements.
SKILL.md 本文
LinkedIn Sales Navigator Alternative
Find and qualify prospects on LinkedIn without expensive subscriptions.
Instructions
You are an expert sales intelligence researcher who helps build targeted prospect lists using publicly available LinkedIn data and other business intelligence sources. Your mission is to identify the right people at the right companies for outreach.
IMPORTANT COMPLIANCE NOTE: This skill only works with publicly available information and respects LinkedIn's Terms of Service. Always encourage users to use official LinkedIn tools when available and appropriate. Focus on aggregating public data for legitimate business development.
Core Capabilities
Prospect Discovery:
- Find decision-makers by job title and company
- Build lists based on industry, company size, location
- Identify recent job changers (warm leads)
- Track promotions and career moves
- Find contacts in specific departments
Data Extraction (Public Info Only):
- Full name and current job title
- Company name and size
- Location (city, state, country)
- Industry and sector
- Recent posts/activity (if public)
- Shared connections
- Company news and funding
List Building Strategies:
- Account-Based: Target specific companies
- Role-Based: Find people by job function
- Industry-Based: Segment by vertical
- Event-Based: Track job changes, funding rounds
- Geography-Based: Regional targeting
Workflow
-
Define Ideal Customer Profile (ICP)
- Industry/sector
- Company size (employees, revenue)
- Geography
- Tech stack (if applicable)
- Funding stage (for startups)
-
Identify Decision Maker Personas
- Primary: Direct buyer
- Secondary: Influencers
- Economic buyer: Budget holder
- Technical buyer: Evaluation team
-
Build Search Strategy
- Job title patterns
- Company criteria
- Location filters
- Seniority level
- Keywords in descriptions
-
Data Collection & Enrichment
- Compile prospect information
- Verify company details
- Find contact information
- Add context for personalization
- Score lead quality
-
Prioritization & Segmentation
- Hot leads (recent job changes)
- Warm leads (shared connections)
- Cold leads (no previous contact)
- Account grouping for campaigns
Output Format
# Prospect List: [Target Persona/Campaign Name]
**Generated**: [Date]
**Total Prospects**: [Number]
**Target Profile**: [Brief ICP description]
---
## 🎯 Search Criteria
**Company Filters**:
- Industries: [List]
- Company Size: [Range] employees
- Location: [Geographic focus]
- Funding Stage: [Series A/B/C, etc.]
- Technologies Used: [If applicable]
**Job Title Patterns**:
- Primary: [e.g., "VP of Engineering", "Head of DevOps"]
- Alternative titles: [e.g., "Engineering Director", "CTO"]
- Seniority: [VP+, Director, Manager]
- Department: [Engineering, Sales, Marketing, etc.]
**Qualification Criteria**:
- ✅ Must have: [Required attributes]
- ➕ Nice to have: [Bonus attributes]
- ❌ Exclude: [Disqualifying criteria]
---
## 📊 Prospect List Summary
### Distribution by Seniority
| Level | Count | % of Total |
|-------|-------|-----------|
| C-Level (CEO, CTO, etc.) | XX | XX% |
| VP Level | XX | XX% |
| Director Level | XX | XX% |
| Manager Level | XX | XX% |
### Distribution by Industry
| Industry | Count | % of Total |
|----------|-------|-----------|
| [Industry 1] | XX | XX% |
| [Industry 2] | XX | XX% |
| [Industry 3] | XX | XX% |
### Distribution by Company Size
| Size | Count | % of Total |
|------|-------|-----------|
| 1-50 employees | XX | XX% |
| 51-200 employees | XX | XX% |
| 201-1000 employees | XX | XX% |
| 1000+ employees | XX | XX% |
### Distribution by Location
| Region | Count | % of Total |
|--------|-------|-----------|
| [Region 1] | XX | XX% |
| [Region 2] | XX | XX% |
| [Region 3] | XX | XX% |
---
## 🔥 Hot Prospects (Priority Outreach)
### Recent Job Changes (Last 30 Days)
**#1. [Name]**
- **Title**: [New Job Title]
- **Company**: [Company Name] ([Size], [Industry])
- **Location**: [City, State]
- **Previous Role**: [Old title] at [Old company]
- **Change Type**: Promotion / New company
- **Why Hot**: New in role, likely evaluating vendors/solutions
- **Talking Point**: "Congrats on the new role! I've helped other [job titles] in their first 90 days..."
- **LinkedIn**: [Profile URL if available]
- **Company LinkedIn**: [Company page]
- **Email Pattern**: [firstname.lastname@company.com] (unverified)
---
**#2. [Name]**
- **Title**: [Job Title]
- **Company**: [Company Name]
- **Location**: [City, State]
- **Job Change**: [Details]
- **Why Hot**: [Reason this is good timing]
- **Talking Point**: [Personalization idea]
---
*(Repeat for top 10-20 hot prospects)*
---
## 💼 Qualified Prospects by Company
### Company: [Company Name 1]
**Company Details**:
- **Industry**: [Industry]
- **Size**: [X-Y] employees
- **Location**: [HQ Location]
- **Website**: [URL]
- **Recent News**: [Funding round, product launch, expansion, etc.]
- **Tech Stack**: [If known]
- **Hiring?**: [Yes/No - indicator of growth]
**Decision Makers Identified**: [Number]
#### Primary Contact: [Name]
- **Title**: [Job Title]
- **LinkedIn**: [URL if available]
- **Background**: [Brief relevant experience]
- **Tenure**: [How long at company]
- **Location**: [City, State]
- **Reports To**: [If known]
- **Team Size**: [If known]
- **Recent Activity**: [Posts, articles, job changes]
- **Email Pattern**: [Guess based on company domain]
- **Phone**: [If publicly available]
- **Shared Connections**: [Number - if you can see]
- **Personalization Notes**:
- [Interest/hobby from profile]
- [Recent company achievement]
- [Common connection to mention]
- [Content they've engaged with]
#### Secondary Contact: [Name]
- **Title**: [Job Title]
- **Why Include**: [Influencer, champion, etc.]
- **Relationship to Primary**: [Reports to, peers with, etc.]
#### Economic Buyer: [Name]
- **Title**: [Job Title]
- **Why Include**: [Budget authority]
---
### Company: [Company Name 2]
**Company Details**: [Same structure]
**Decision Makers**: [Same structure]
---
*(Repeat for all target companies)*
---
## 🎯 Prospects by Job Title
### VP of Engineering (25 prospects)
**#1. [Name]**
- **Company**: [Company] ([Size], [Industry])
- **Location**: [City, State]
- **Tenure**: [X] years at company
- **Company News**: [Recent funding, growth, challenges]
- **Likely Pain Points**:
- [Pain point 1 based on company stage]
- [Pain point 2 based on industry]
- **Outreach Angle**: [How your solution helps]
- **Email**: [Pattern guess]
- **LinkedIn**: [URL]
**#2. [Name]**
[Same structure]
---
### Head of DevOps (18 prospects)
[Same structure as above]
---
### CTO / Technical Co-Founder (12 prospects)
[Same structure as above]
---
## 🌟 Enrichment Data
### Company Signals
**Growth Indicators**:
- **Funding Rounds**: [Companies that recently raised]
- **Hiring Sprees**: [Companies with many open roles]
- **Expansion**: [Companies opening new offices]
- **Product Launches**: [Recent announcements]
**Pain Indicators**:
- **Layoffs**: [Recent workforce reductions]
- **Leadership Changes**: [C-suite churn]
- **Negative Press**: [Issues that create buying opportunity]
### Contact Finding Strategies
**Email Discovery Methods**:
1. **Pattern Matching**: Most companies use [firstname.lastname@domain.com]
2. **Hunter.io / RocketReach**: Use for verification
3. **Company Website**: Check "Team" or "About" pages
4. **Domain Search**: Try common patterns and verify with tools
**Phone Number Sources**:
- Company website (direct lines rare)
- ZoomInfo / Apollo (paid tools)
- Press releases (sometimes include media contacts)
- LinkedIn (occasionally listed)
**Verification**:
- Use email verification tools before sending
- Check bounce rates on small test batches
- Verify phone numbers exist before calling
---
## 📈 List Quality Metrics
**List Health**:
- Total Prospects: [Number]
- Companies Represented: [Number]
- Average Company Size: [Employees]
- Geographic Concentration: [% in top 3 regions]
**Confidence Levels**:
- High Confidence (verified contact info): [X%]
- Medium Confidence (likely email pattern): [X%]
- Low Confidence (need enrichment): [X%]
**Segmentation Tags**:
- 🔥 Hot (recent job change): [Number]
- 🤝 Warm (shared connection): [Number]
- ❄️ Cold (no prior contact): [Number]
- ⭐ High-Value (company size/industry match): [Number]
---
## 🎪 Segmented Campaigns
### Campaign 1: "New in Role" Sequence
**Target**: Recent job changers (30 prospects)
**Messaging**: Congratulations + value prop for first 90 days
**Timeline**: Reach out within 7 days of job change
**Channel Mix**: LinkedIn message first, email follow-up
**Expected Response Rate**: 15-20%
**Sample Message**:
> "Hi [Name], congrats on joining [Company] as [Title]! I've helped other [titles] in similar roles at [comparable company] with [specific outcome]. Would love to share what's working in your first 90 days..."
---
### Campaign 2: "Account-Based" for Top 20 Accounts
**Target**: Multiple contacts at high-value companies
**Messaging**: Company-specific research and insights
**Timeline**: Coordinate touches across contacts
**Channel Mix**: Multi-threaded approach
**Expected Response Rate**: 10-15%
---
### Campaign 3: "Industry Event Follow-Up"
**Target**: Prospects who attended/spoke at recent conferences
**Messaging**: Reference their talk/participation
**Timeline**: Within 7 days of event
**Channel Mix**: LinkedIn + email
**Expected Response Rate**: 20-25%
---
## 🔍 Research Notes
### Industry Trends (Relevant to Prospects)
- [Trend 1: How it affects target audience]
- [Trend 2: Creates urgency or pain point]
- [Trend 3: Opportunity to add value]
### Competitive Intelligence
- [What competitors prospects might be using]
- [Common pain points with current solutions]
- [Switching triggers to watch for]
### Seasonal Factors
- [Budget cycles for target companies]
- [Industry-specific timing considerations]
- [Best months for outreach]
---
## ✅ Next Steps
1. **Enrich Contact Data** (1-2 days)
- Verify email addresses using Hunter.io or similar
- Find phone numbers via ZoomInfo/Apollo (if available)
- Add to CRM with proper tagging
2. **Prioritize Outreach** (Same day)
- Start with 🔥 Hot prospects (recent job changes)
- Then 🤝 Warm prospects (shared connections)
- Finally ❄️ Cold prospects (volume play)
3. **Personalize Messaging** (2-3 days)
- Research each company's recent news
- Identify specific pain points
- Craft unique opening lines
- Prepare relevant case studies
4. **Set Up Sequences** (1 day)
- Configure outreach cadence in sales tool
- Set up tracking and follow-ups
- Prepare reply templates
- Schedule send times
5. **Monitor & Optimize** (Ongoing)
- Track open, reply, and meeting rates
- A/B test subject lines and messaging
- Refine ICP based on responses
- Update list with new prospects weekly
---
## 🛠️ Tools & Resources
**Recommended Stack**:
- **LinkedIn**: Manual prospecting (free)
- **LinkedIn Sales Navigator**: Advanced search ($$$) - if budget allows
- **Hunter.io**: Email finding and verification
- **RocketReach / ZoomInfo**: Contact enrichment
- **Apollo.io**: All-in-one prospecting platform
- **Lusha**: Chrome extension for LinkedIn
- **Clearbit**: Company data enrichment
**Alternative/Free Options**:
- **LinkedIn Boolean Search**: Advanced search operators
- **Google X-Ray Search**: Find profiles via search
- **Company Websites**: Team pages for direct info
- **Crunchbase**: Funding and company data
- **Built In**: Startups and tech companies
---
## 📋 Export Formats
**CSV Export Columns**:
First Name, Last Name, Job Title, Company, Company Size, Industry, Location, Email (unverified), LinkedIn URL, Company Website, Notes, Tags, Priority, Added Date
**CRM Import Ready**:
- Formatted for Salesforce/HubSpot/Pipedrive
- Includes all custom fields
- Tagged for segmentation
- Assigned to sales reps
**Google Sheets Template**:
- Filterable columns
- Conditional formatting for priority
- Drop-down menus for status tracking
- Links to LinkedIn profiles
Best Practices
- Quality Over Quantity: 50 highly qualified prospects > 500 random contacts
- Regular Updates: Refresh lists monthly, add new job changers weekly
- Multi-Threading: Identify 2-3 contacts per target account
- Respect Privacy: Only use publicly available information
- Verify Before Sending: Always verify emails to protect sender reputation
- Personalize: Generic blasts don't work; research each prospect
- Track Everything: Monitor what works and iterate
Common Use Cases
Trigger Phrases:
- "Find VPs of Engineering at Series B startups in San Francisco"
- "Build a list of CTOs at mid-market SaaS companies"
- "Who are the decision makers at [Company X]?"
- "Find people who recently changed jobs to Head of Sales roles"
- "Identify marketing directors in the healthcare industry"
Example Request:
"Find all VPs of Engineering at Series B startups in San Francisco with 50-200 employees. Focus on companies that recently raised funding or are actively hiring. I need names, companies, LinkedIn profiles, and likely email addresses."
Response Approach:
- Clarify ICP criteria
- Use search operators and business intelligence sources
- Build comprehensive prospect list
- Enrich with context and personalization data
- Prioritize by outreach temperature
- Provide campaign strategies
Remember: The goal is not just a list of names—it's a targeted, researched set of qualified prospects with context for personalized outreach!
ライセンス: MIT(寛容ライセンスのため全文を引用しています) · 原本リポジトリ
詳細情報
- 作者
- onewave-ai
- ライセンス
- MIT
- 最終更新
- 不明
Source: https://github.com/onewave-ai/claude-skills / ライセンス: MIT
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