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初始化提交
2026-03-01 16:24:24 +08:00

236 lines
6.9 KiB
Markdown

---
name: lead-hand-skill
version: "1.0.0"
description: "Expert knowledge for AI lead generation — web research, enrichment, scoring, deduplication, and report generation"
runtime: prompt_only
---
# Lead Generation Expert Knowledge
## Ideal Customer Profile (ICP) Construction
A good ICP answers these questions:
1. **Industry**: What vertical does your ideal customer operate in?
2. **Company size**: How many employees? What revenue range?
3. **Geography**: Where are they located?
4. **Technology**: What tech stack do they use?
5. **Budget signals**: Are they funded? Growing? Hiring?
6. **Decision-maker**: Who has buying authority? (title, seniority)
7. **Pain points**: What problems does your product solve for them?
### Company Size Categories
| Category | Employees | Typical Budget | Sales Cycle |
|----------|-----------|---------------|-------------|
| Startup | 1-50 | $1K-$25K/yr | 1-4 weeks |
| SMB | 50-500 | $25K-$250K/yr | 1-3 months |
| Enterprise | 500+ | $250K+/yr | 3-12 months |
---
## Web Research Techniques for Lead Discovery
### Search Query Patterns
```
# Find companies in a vertical
"[industry] companies" site:crunchbase.com
"top [industry] startups [year]"
"[industry] companies [city/region]"
# Find decision-makers
"[title]" "[company]" site:linkedin.com
"[company] team" OR "[company] about us" OR "[company] leadership"
# Growth signals (high-intent leads)
"[company] hiring [role]" — indicates budget and growth
"[company] series [A/B/C]" — recently funded
"[company] expansion" OR "[company] new office"
"[company] product launch [year]"
# Technology signals
"[company] uses [technology]" OR "[company] built with [technology]"
site:stackshare.io "[company]"
site:builtwith.com "[company]"
```
### Source Quality Ranking
1. **Company website** (About/Team pages) — most reliable for personnel
2. **Crunchbase** — funding, company details, leadership
3. **LinkedIn** (public profiles) — titles, tenure, connections
4. **Press releases** — announcements, partnerships, funding
5. **Job boards** — hiring signals, tech stack requirements
6. **Industry directories** — comprehensive company lists
7. **News articles** — recent activity, reputation
8. **Social media** — engagement, company culture
---
## Lead Enrichment Patterns
### Basic Enrichment (always available)
- Full name (first + last)
- Job title
- Company name
- Company website URL
### Standard Enrichment
- Company employee count (from About page, Crunchbase, or LinkedIn)
- Company industry classification
- Company founding year
- Technology stack (from job postings, StackShare, BuiltWith)
- Social profiles (LinkedIn URL, Twitter handle)
- Company description (from meta tags or About page)
### Deep Enrichment
- Recent funding rounds (amount, investors, date)
- Recent news mentions (last 90 days)
- Key competitors
- Estimated revenue range
- Recent job postings (growth signals)
- Company blog/content activity (engagement level)
- Executive team changes
### Email Pattern Discovery
Common corporate email formats (try in order):
1. `firstname@company.com` (most common for small companies)
2. `firstname.lastname@company.com` (most common for larger companies)
3. `first_initial+lastname@company.com` (e.g., jsmith@)
4. `firstname+last_initial@company.com` (e.g., johns@)
Note: NEVER send unsolicited emails. Email patterns are for reference only.
---
## Lead Scoring Framework
### Scoring Rubric (0-100)
```
ICP Match (30 points max):
Industry match: +10
Company size match: +5
Geography match: +5
Role/title match: +10
Growth Signals (20 points max):
Recent funding: +8
Actively hiring: +6
Product launch: +3
Press coverage: +3
Enrichment Quality (20 points max):
Email found: +5
LinkedIn found: +5
Full company data: +5
Tech stack known: +5
Recency (15 points max):
Active this month: +15
Active this quarter:+10
Active this year: +5
No recent activity: +0
Accessibility (15 points max):
Direct contact: +15
Company contact: +10
Social only: +5
No contact info: +0
```
### Score Interpretation
| Score | Grade | Action |
|-------|-------|--------|
| 80-100 | A | Hot lead — prioritize outreach |
| 60-79 | B | Warm lead — nurture |
| 40-59 | C | Cool lead — enrich further |
| 0-39 | D | Cold lead — deprioritize |
---
## Deduplication Strategies
### Matching Algorithm
1. **Exact match**: Normalize company name (lowercase, strip Inc/LLC/Ltd) + person name
2. **Fuzzy match**: Levenshtein distance < 2 on company name + same person
3. **Domain match**: Same company website domain = same company
4. **Cross-source merge**: Same person at same company from different sources merge enrichment data
### Normalization Rules
```
Company name:
- Strip legal suffixes: Inc, LLC, Ltd, Corp, Co, GmbH, AG, SA
- Lowercase
- Remove "The" prefix
- Collapse whitespace
Person name:
- Lowercase
- Remove middle names/initials
- Handle "Bob" = "Robert", "Mike" = "Michael" (common nicknames)
```
---
## Output Format Templates
### CSV Format
```csv
Name,Title,Company,Company URL,LinkedIn,Industry,Size,Score,Discovered,Notes
"Jane Smith","VP Engineering","Acme Corp","https://acme.com","https://linkedin.com/in/janesmith","SaaS","SMB (120 employees)",85,"2025-01-15","Series B funded, hiring 5 engineers"
```
### JSON Format
```json
[
{
"name": "Jane Smith",
"title": "VP Engineering",
"company": "Acme Corp",
"company_url": "https://acme.com",
"linkedin": "https://linkedin.com/in/janesmith",
"industry": "SaaS",
"company_size": "SMB",
"employee_count": 120,
"score": 85,
"discovered": "2025-01-15",
"enrichment": {
"funding": "Series B, $15M",
"hiring": true,
"tech_stack": ["React", "Python", "AWS"],
"recent_news": "Launched enterprise plan Q4 2024"
},
"notes": "Strong ICP match, actively growing"
}
]
```
### Markdown Table Format
```markdown
| # | Name | Title | Company | Score | Key Signal |
|---|------|-------|---------|-------|------------|
| 1 | Jane Smith | VP Engineering | Acme Corp | 85 | Series B funded, hiring |
| 2 | John Doe | CTO | Beta Inc | 72 | Product launch Q1 2025 |
```
---
## Compliance & Ethics
### DO
- Use only publicly available information
- Respect robots.txt and rate limits
- Include data provenance (where each piece of info came from)
- Allow users to export and delete their lead data
- Clearly mark confidence levels on enriched data
### DO NOT
- Scrape behind login walls or paywalls
- Fabricate any lead data (even "likely" email addresses without evidence)
- Store sensitive personal data (SSN, financial info, health data)
- Send unsolicited communications on behalf of the user
- Bypass anti-scraping measures (CAPTCHAs, rate limits)
- Collect data on individuals who have opted out of data collection
### Data Retention
- Keep lead data in local files only never exfiltrate
- Mark stale leads (>90 days without activity) for review
- Provide clear data export in all supported formats