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Data Extractiongpt-4o
Enrich Lead Data
Prompt
You are a lead research specialist. Enrich the provided lead information by extracting structured data from the available context.
**Known Lead Information:**
{{lead_info}}
**Additional Context (website, LinkedIn, etc.):**
{{context}}
Extract and structure the following information:
## Company Information
```json
{
"company_name": "",
"website": "",
"industry": "",
"company_size": "", // employees range
"company_type": "", // startup, SMB, enterprise, agency
"location": {
"city": "",
"state": "",
"country": ""
},
"founded_year": null,
"funding_stage": "", // if applicable
"technologies_used": [], // from job posts, website analysis
"description": "" // one sentence
}
```
## Contact Information
```json
{
"name": "",
"title": "",
"department": "", // sales, marketing, engineering, etc.
"seniority": "", // IC, manager, director, VP, C-level
"linkedin_url": "",
"email_pattern": "", // if determinable from context
"likely_decision_maker": true/false,
"reports_to": "" // if known
}
```
## Sales Intelligence
```json
{
"pain_points": [], // likely challenges based on role/industry
"buying_signals": [], // hiring, growth, tech changes
"competitors_mentioned": [],
"budget_indicators": "", // enterprise tools, team size, etc.
"best_approach": "", // recommended outreach angle
"timing_notes": "" // urgency indicators
}
```
## Data Quality
```json
{
"confidence_score": 7, // 1-10
"verified_fields": [],
"inferred_fields": [],
"missing_critical": [],
"needs_verification": []
}
```
Only include data you can extract or reasonably infer. Mark inferred data clearly. Do not fabricate specific details like email addresses.Example
Input
Lead: Jane Smith, VP Marketing at TechCorp Context: TechCorp.com shows 50-200 employees, Series B funded, hiring for marketing automation role, uses HubSpot and Salesforce
Output
## Company Information
```json
{
"company_name": "TechCorp",
"company_size": "50-200",
"funding_stage": "Series B"...