account-research

Account Research

Get a complete picture of any company or person before outreach. This skill always works with web search, and gets significantly better with enrichment and CRM data.

Lark-native execution (read the depth core first: LARK-PATTERNS, LARK-RECIPES, LARK-FUSION; tool map in CONNECTORS.md). External web search + enrichment tools (Clay/ZoomInfo/Apollo) stay as-is. The CRM is a Lark Base (P5, system-of-record): read prior relationship with lark_base_search (requires search_fields; narrow with select_fields — base_search does NOT support jq), and when the user wants a person resolved to a real teammate, use lark_contact_search (P1). Internal intel about the account lives in chat (lark_im_search) and meetings (lark_minutes_search, P6). Land the durable research brief in Wiki (lark_wiki_node_create, P8) and surface the "Quick Take + recommended approach" as an interactive card (lark_im_card_send, P4) — don't leave it as a chat wall of text. For deep CRM/Base reads delegate to lark-base; for a full relationship dossier on a known person delegate to the contact-360 skill.

How It Works

┌─────────────────────────────────────────────────────────────────┐
│                     ACCOUNT RESEARCH                             │
├─────────────────────────────────────────────────────────────────┤
│  ALWAYS (works standalone via web search)                        │
│  ✓ Company overview: what they do, size, industry               │
│  ✓ Recent news: funding, leadership changes, announcements      │
│  ✓ Hiring signals: open roles, growth indicators                │
│  ✓ Key people: leadership team from LinkedIn                    │
│  ✓ Product/service: what they sell, who they serve              │
├─────────────────────────────────────────────────────────────────┤
│  SUPERCHARGED (when you connect your tools)                      │
│  + Enrichment: verified emails, phone, tech stack, org chart    │
│  + CRM: prior relationship, past opportunities, contacts        │
└─────────────────────────────────────────────────────────────────┘

---

Getting Started

Just tell me who to research:

• "Research Stripe"
• "Look up the CTO at Lark Wiki"
• "Intel on acme.com"
• "Who is Sarah Chen at TechCorp?"
• "Tell me about [company] before my call"

I'll run web searches immediately. If you have enrichment or CRM connected, I'll pull that data too.

---

Connectors (Optional)

Connect your tools to supercharge this skill:

Connector	What It Adds
Enrichment	Verified emails, phone numbers, tech stack, org chart, funding details
CRM	Prior relationship history, past opportunities, existing contacts, notes

No connectors? No problem. Web search provides solid research for any company or person.

---

Output Format

# Research: [Company or Person Name]

**Generated:** [Date]
**Sources:** Web Search [+ Enrichment] [+ CRM]

---

## Quick Take

[2-3 sentences: Who they are, why they might need you, best angle for outreach]

---

## Company Profile

| Field | Value |
|-------|-------|
| **Company** | [Name] |
| **Website** | [URL] |
| **Industry** | [Industry] |
| **Size** | [Employee count] |
| **Headquarters** | [Location] |
| **Founded** | [Year] |
| **Funding** | [Stage + amount if known] |
| **Revenue** | [Estimate if available] |

### What They Do
[1-2 sentence description of their business, product, and customers]

### Recent News
- **[Headline]** — [Date] — [Why it matters for your outreach]
- **[Headline]** — [Date] — [Why it matters]

### Hiring Signals
- [X] open roles in [Department]
- Notable: [Relevant roles like Engineering, Sales, AI/ML]
- Growth indicator: [Hiring velocity interpretation]

---

## Key People

### [Name] — [Title]
| Field | Detail |
|-------|--------|
| **LinkedIn** | [URL] |
| **Background** | [Prior companies, education] |
| **Tenure** | [Time at company] |
| **Email** | [If enrichment connected] |

**Talking Points:**
- [Personal hook based on background]
- [Professional hook based on role]

[Repeat for relevant contacts]

---

## Tech Stack [If Enrichment Connected]

| Category | Tools |
|----------|-------|
| **Cloud** | [AWS, GCP, Azure, etc.] |
| **Data** | [Snowflake, Databricks, etc.] |
| **CRM** | [e.g. Salesforce, HubSpot] |
| **Other** | [Relevant tools] |

**Integration Opportunity:** [How your product fits with their stack]

---

## Prior Relationship [If CRM Connected]

| Field | Detail |
|-------|--------|
| **Status** | [New / Prior prospect / Customer / Churned] |
| **Last Contact** | [Date and type] |
| **Previous Opps** | [Won/Lost and why] |
| **Known Contacts** | [Names already in CRM] |

**History:** [Summary of past relationship]

---

## Qualification Signals

### Positive Signals
- ✅ [Signal and evidence]
- ✅ [Signal and evidence]

### Potential Concerns
- ⚠️ [Concern and what to watch for]

### Unknown (Ask in Discovery)
- ❓ [Gap in understanding]

---

## Recommended Approach

**Best Entry Point:** [Person and why]

**Opening Hook:** [What to lead with based on research]

**Discovery Questions:**
1. [Question about their situation]
2. [Question about pain points]
3. [Question about decision process]

---

## Sources
- [Source 1](URL)
- [Source 2](URL)

---

Execution Flow

Step 1: Parse Request

Identify what to research:
- "Research Stripe" → Company research
- "Look up John Smith at Acme" → Person + company
- "Who is the CTO at Lark Wiki" → Role-based search
- "Intel on acme.com" → Domain-based lookup

Step 2: Web Search (Always)

Run these searches:
1. "[Company name]" → Homepage, about page
2. "[Company name] news" → Recent announcements
3. "[Company name] funding" → Investment history
4. "[Company name] careers" → Hiring signals
5. "[Person name] [Company] LinkedIn" → Profile info
6. "[Company name] product" → What they sell
7. "[Company name] customers" → Who they serve

Extract:

• Company description and positioning
• Recent news (last 90 days)
• Leadership team
• Open job postings
• Technology mentions
• Customer base

Step 3: Enrichment (If Connected)

If enrichment tools available:
1. Enrich company → Firmographics, funding, tech stack
2. Search people → Org chart, contact list
3. Enrich person → Email, phone, background
4. Get signals → Intent data, hiring velocity

Enrichment adds:

• Verified contact info
• Complete org chart
• Precise employee count
• Detailed tech stack
• Funding history with investors

Step 4: CRM Check — Lark Base (If Connected)

The CRM is a Lark Base (P5). Read it, don't hand-roll. NOTE: lark_base_search REQUIRES search_fields (the Bitable API mandates which field to match on) and does NOT support jq — narrow the result with select_fields / limit instead. If you don't know the field names, discover them first: lark_api GET /open-apis/bitable/v1/apps/{base}/tables/{table}/fields.

1. lark_base_search(base_token, table_id, query="<company / domain>",
     search_fields=["Account Name"],            # the field(s) to match against
     select_fields=["Account Name","Stage","Owner","Last Touch","Notes"],
     limit=5)                                    # find the account record (no jq)
2. Related contacts: search the Contacts table with search_fields on the account name.
3. Opportunity history: search the Deals/Opportunities table (search_fields on account).
4. Activity timeline: read the Activities table (or pull recent threads via
   lark_im_search / meetings via lark_minutes_search, participant_ids="me", P6).

For richer Base reads (field/view control, lookups) delegate to lark-base. If the org's CRM is an external system (HubSpot/Close), use that tool's MCP server instead.

CRM adds:

• Prior relationship context
• What happened before (won/lost deals)
• Who we've talked to
• Notes and history

Step 5: Synthesize

1. Combine all sources
2. Prioritize enrichment data over web (more accurate)
3. Add CRM context if exists
4. Identify qualification signals
5. Generate talking points
6. Recommend approach

---

Research Variations

Company Research

Focus on: Business overview, news, hiring, leadership

Person Research

Focus on: Background, role, LinkedIn activity, talking points

Competitor Research

Focus on: Product comparison, positioning, win/loss patterns

Pre-Meeting Research

Focus on: Attendee backgrounds, recent news, relationship history

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Tips for Better Research

1. Include the domain — "research acme.com" is more precise
2. Specify the person — "look up Jane Smith, VP Sales at Acme"
3. State your goal — "research Stripe before my demo call"
4. Ask for specifics — "what's their tech stack?" after initial research

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Deliver (Lark-native)

1. Land the brief in Wiki (P8): lark_wiki_node_create(space_id=..., title="Research: <Company>") → fill the docx body with the Output Format above (for non-trivial doc editing delegate to lark-doc). Durable research belongs in Wiki, not a chat message.
2. Surface the decision as a card (P4): post the Quick Take + Recommended Approach + a Talking Points row via lark_im_card_send (print_json: true → dry_run: true → send). Add an actions row ("Draft outreach" / "Prep the call") that routes to the related skills.
3. Resolve any teammate/owner mentioned to a real open_id via lark_contact_search (P1) before @-mentioning or assigning follow-up.

Related Skills

• call-prep — Full meeting prep with this research plus context
• draft-outreach — Write personalized message based on research
• contact-360 — Full 360° relationship dossier on a known person (delegate for depth)
• lark-base — Deep CRM/Base reads, lookups, dashboards