# Prospect Research — Account & Company Intelligence

Research companies and key contacts to build actionable sales intelligence for the lead pipeline. Draws on web search, lead_pipeline enrichment data, and connected CRM/enrichment tools.

## When This Skill Activates

Trigger phrases: "research [company]", "look up [prospect]", "intel on [company]", "who is [person] at [company]", "find out about [company]", "background on [lead]"

## Research Workflow

### Step 1: Parse the Request
- Identify the target: company name, person name, domain, or lead ID
- Determine scope: quick overview vs. deep dive
- Check if lead already exists in `~/.lead_pipeline/data/` campaigns

### Step 2: Gather Intelligence

**Always available (web search):**
1. Company overview — what they do, size, industry, founding date
2. Recent news — funding rounds, acquisitions, product launches, leadership changes
3. Hiring signals — open roles indicate growth areas and pain points
4. Key personnel — C-suite, decision-makers, relevant contacts
5. Technology stack — what tools/platforms they use
6. Social presence — LinkedIn, Twitter activity, blog posts

**Enhanced with lead_pipeline enrichment module:**
- Run `LeadEnricher.enrich()` for systematic contact discovery
- Cross-reference Tavily, Google Custom Search, DuckDuckGo results
- Extract emails, phone numbers, LinkedIn profiles
- Match against UK Companies House or Qatar registry data

**Enhanced with connected tools (if MCP servers configured):**
- **HubSpot/Pipedrive**: Check existing CRM records, past interactions, deal history
- **Clay/ZoomInfo/Apollo**: Verified contact info, org charts, technographics
- **Slack**: Internal discussions mentioning the company
- **LinkedIn**: Professional profiles and mutual connections

### Step 3: Qualify the Prospect

Assess using the BANT framework:
- **Budget**: Company size, funding, revenue indicators
- **Authority**: Identify decision-makers vs. influencers
- **Need**: Pain points matching our value proposition
- **Timeline**: Hiring urgency, contract renewal signals

### Step 4: Synthesize Output

```markdown
## 🏢 [Company Name] — Research Brief

### Quick Summary
[2-3 sentence overview with the most important finding]

### Company Profile
| Field | Details |
|-------|---------|
| Industry | ... |
| Size | ... employees |
| Founded | ... |
| HQ | ... |
| Website | ... |
| Revenue | ... (if available) |

### Recent News & Signals
1. [Date] — [Headline] — [Why it matters for outreach]
2. [Date] — [Headline] — [Relevance]
3. [Date] — [Headline] — [Relevance]

### Key Contacts
| Name | Role | LinkedIn | Email |
|------|------|----------|-------|
| ... | ... | ... | ... |

### Hiring Signals
- [Open role] → Indicates [growth area/pain point]
- [Open role] → Indicates [growth area/pain point]

### Technology Stack
[Known tools, platforms, and vendors]

### Qualification Signals
✅ Positive: [reasons this is a good prospect]
⚠️ Concerns: [potential blockers]
❓ Unknown: [what we still need to find out]

### Recommended Outreach Approach
- **Best contact**: [Name, Role]
- **Hook**: [Personalization angle based on research]
- **Discovery questions**:
  1. [Question based on findings]
  2. [Question based on findings]
  3. [Question based on findings]
```

## Integration with Lead Pipeline

When a company matches an existing lead in the pipeline:
- Pull existing `Company` and `ContactInfo` data from `types.py` models
- Show pipeline status (NEW → ENRICHED → EMAIL_DRAFTED → SENT)
- Reference the `CampaignResult` if previously contacted
- Check GDPR audit log for compliance history

## Key Rules
- ALWAYS search before making claims — never fabricate company details
- Prioritize recency — news from the last 6 months matters most
- Flag uncertainty — clearly mark unverified information
- Respect GDPR — note data sources for audit trail compliance
- Use the lead_pipeline's `RegistrySource` data when available (UK Companies House, Qatar registries)
