| name | lead-research-assistant |
| description | Researches and identifies potential customers, leads, and business opportunities for your product or service. Analyzes your offering, finds relevant companies and decision makers, provides contact information, and suggests outreach strategies. Use when looking for leads, researching target customers, identifying decision makers, or planning sales outreach. |
Lead Research Assistant
This skill helps find and qualify potential customers for your product or service through systematic research and analysis.
When to Use This Skill
Use this skill when you need to:
- Find companies that would benefit from your product
- Identify decision makers and their contact information
- Research specific market segments or industries
- Build targeted prospect lists
- Plan outreach strategies
- Qualify leads based on criteria
- Research competitor customers
- Find early adopters or beta users
Research Workflow
1. Understand the Product
First, analyze what you're selling:
- Read product description/repository
- Understand core value proposition
- Identify key features and benefits
- Determine ideal customer profile (ICP)
- Note technical requirements or integrations
2. Define Target Criteria
Establish search parameters:
- Industry: Which sectors benefit most?
- Company size: Startups, SMB, Enterprise?
- Geography: Location requirements?
- Technographics: What tech stack do they use?
- Budget indicators: Funding, revenue, growth stage?
- Pain points: What problems do they face?
3. Research Strategy
Use multiple research approaches:
Company Discovery:
- Industry-specific searches
- Tech stack searches (e.g., "companies using Cursor AI")
- Recent funding announcements (Crunchbase, TechCrunch)
- LinkedIn company searches
- Y Combinator batches
- Product Hunt launches
- Conference attendee lists
- Industry associations
Decision Maker Identification:
- LinkedIn profile searches
- Company org charts
- Apollo.io or similar databases
- GitHub contributor searches (for dev tools)
- Twitter/X for thought leaders
- Industry forum moderators
4. Lead Qualification Scoring
Score each lead on:
- Fit Score (1-10): How well do they match ICP?
- Intent Score (1-10): How likely are they to buy?
- Priority (High/Medium/Low): Overall ranking
Fit Criteria:
- Uses complementary tools (+2)
- In target industry (+2)
- Right company size (+2)
- Geographic fit (+1)
- Recent growth indicators (+2)
- Budget signals (+1)
Intent Criteria:
- Recent funding (+3)
- Hiring for relevant roles (+2)
- Posted about related problems (+3)
- Active in community (+1)
- Recent tech stack changes (+1)
5. Information Gathering
For each qualified lead, collect:
Company Information:
- Company name and website
- Industry and sector
- Employee count
- Location (HQ and offices)
- Funding status and amount
- Tech stack
- Recent news or milestones
Decision Maker Details:
- Name and title
- LinkedIn profile URL
- Email (if available)
- Twitter/X handle
- Recent activity or posts
- Shared connections
Context & Insights:
- Why they're a good fit
- Specific pain points your product solves
- Recent company changes or needs
- Mutual connections or warm intro paths
- Relevant content they've shared
6. Outreach Strategy
For each lead, suggest:
Messaging Approach:
- Personalization hooks (recent posts, company news)
- Value proposition specific to their situation
- Relevant case studies or social proof
- Call-to-action (demo, trial, conversation)
Conversation Starters:
- Reference specific pain points
- Mention mutual connections
- Comment on their recent work
- Share relevant insights
- Offer immediate value
Timing Considerations:
- Best time to reach out
- Seasonal factors
- Company fiscal calendar
- Product launch cycles
Output Format
Structure lead research as:
# Lead Research Results
## Overview
- Total leads found: [X]
- High priority: [Y]
- Medium priority: [Z]
- Industries covered: [list]
## High Priority Leads
### 1. [Company Name]
**Fit Score**: 9/10 | **Intent Score**: 8/10 | **Priority**: HIGH
**Company Details**:
- Industry: [industry]
- Size: [employees]
- Location: [city, country]
- Funding: [amount/stage]
- Website: [url]
**Why Good Fit**:
- [Specific reason 1]
- [Specific reason 2]
- [Specific reason 3]
**Decision Maker**:
- Name: [Full Name]
- Title: [Job Title]
- LinkedIn: [URL]
- Email: [if found]
**Outreach Strategy**:
- **Hook**: [Personalization element]
- **Value Prop**: [Specific benefit for them]
- **CTA**: [Suggested ask]
**Conversation Starter**:
"Hi [Name], noticed [specific observation]. We help companies like [theirs] [specific value]. Would [specific outcome] be valuable for your team?"
---
[Repeat for each high-priority lead]
Research Sources
Free Sources
- LinkedIn (company pages, people search)
- GitHub (contributor activity, org repositories)
- Twitter/X (company mentions, decision maker posts)
- Crunchbase (basic funding data)
- Product Hunt (new product launches)
- HackerNews (who's hiring, show HN)
- Company blogs and press pages
- Industry publications
Paid Sources (if available)
- Apollo.io (B2B contact database)
- ZoomInfo (company & contact data)
- LinkedIn Sales Navigator
- Crunchbase Pro
- BuiltWith (tech stack data)
- SimilarWeb (traffic data)
Domain-Specific Strategies
For Developer Tools
Target:
- Engineering managers on LinkedIn
- GitHub users in relevant ecosystems
- Stack Overflow contributors
- DevTool Twitter communities
- Engineering blogs
- Tech conference speakers
For B2B SaaS
Target:
- Department heads (VP Sales, VP Eng, etc.)
- Companies in growth stage
- Recent funding announcements
- Job posts indicating expansion
- LinkedIn groups for industry
For Real Estate Tech
Target:
- Real estate investors and fund managers
- Property management companies
- Real estate brokerages
- REITs and institutional investors
- Real estate tech adopters
- Industry conference attendees
For AI/ML Tools
Target:
- Companies hiring ML engineers
- Y Combinator AI companies
- Users of complementary AI tools
- AI research labs
- Companies with AI in job descriptions
- AI Twitter/X community
Quality Standards
Ensure each lead entry:
- ✅ Has verifiable company information
- ✅ Includes decision maker name and title
- ✅ Explains why they're a good fit
- ✅ Provides concrete outreach strategy
- ✅ Includes at least one contact method
- ✅ Has accurate fit/intent scoring
- ✅ Contains actionable next steps
Avoid:
- ❌ Generic "spray and pray" lists
- ❌ Outdated contact information
- ❌ Unclear value propositions
- ❌ Missing decision maker details
- ❌ No personalization hooks
Examples
Example 1: Developer Tool
Product: AI-powered foreclosure auction analysis platform
Research Strategy:
- Search: "real estate investment companies Brevard County"
- Search: "property investors Florida foreclosures"
- LinkedIn: Real estate fund managers in Florida
- Search: "real estate wholesalers central Florida"
Sample Lead:
- Company: Sunshine State Capital
- Decision Maker: John Smith, Managing Partner
- Fit: 9/10 - Active foreclosure investor, 50+ properties
- Hook: Recent LinkedIn post about deal analysis challenges
- Value Prop: Automated lien discovery saves 5-10 hours per auction
Example 2: SaaS Tool
Product: Project management for AI developers
Research Strategy:
- Y Combinator W25 AI companies
- Companies using Cursor AI (via job posts)
- "AI startup" + "hiring" searches
- GitHub organizations with AI repos
Sample Lead:
- Company: VectorAI Labs
- Decision Maker: Sarah Chen, CTO
- Fit: 8/10 - 15 engineers, AI-first company, using Cursor
- Hook: Just raised Series A, hiring 10 engineers
- Value Prop: Built specifically for AI development workflows
Tips for Success
- Start Broad, Then Narrow: Cast wide net initially, then filter rigorously
- Verify Information: Double-check contact details and job titles
- Find Warm Paths: Look for mutual connections or shared communities
- Timely Research: Prioritize leads with recent trigger events
- Batch Similar Leads: Group by industry or use case for efficient outreach
- Track Results: Note which research methods yield best leads
- Refresh Regularly: Update lead list as situations change
- Respect Privacy: Use publicly available information ethically
