When you're launching into a new vertical and need 20 accounts to work this quarter, build a ranked target list from your product plus ICP filters. — Claude Skill
Rank target accounts by fit score with decision-maker per row.
- Input: product description plus ICP filters (industry, size, geo, technologies they use, buying signals)
- Per-account fit score 1 to 10 with reasoning grounded in their business
- Decision-maker by role plus LinkedIn URL when available
- Conversation starters tied to recent company signals: job posts, leadership change, funding, news
- Output: ranked markdown report and CSV ready for Apollo, Outreach, or Salesforce
대상
Turn a product description and ICP filters into a ranked target-account list with decision-maker and 'why now' opener per row
이 역할의 스킬 보기Walk into every discovery call with a fit-scored briefing your SDR pulled the night before
이 역할의 스킬 보기Hand your team a quarter's worth of ICP-matched accounts in one prompt instead of an 8-hour Apollo session
이 역할의 스킬 보기기능
Your CEO just announced a new product line aimed at fintech. You have zero accounts in pipe. Drop the product description plus 'Series B+ fintechs with 50-300 engineers' and get back 20 fit-scored accounts with the VP Eng and 'why reach out' line per row.
End-of-quarter exercise: your AE handed you a new ICP definition (manufacturing companies, 200-1000 staff, west coast, on legacy Oracle). Drop the criteria, get a ranked list of 30 that match, sorted by recent buying signals (job posts, leadership change, funding).
Marketing announces UK launch in 6 weeks. You need 15 anchor accounts to seed the territory. Drop the product brief plus UK plus your target ICP and get back UK-headquartered accounts with decision-maker name, LinkedIn, and a 'why now' angle for each.
Your AE has a discovery call with Acme Co tomorrow morning. Drop the company name and get back the same fit-scored card: who's the economic buyer, recent signals, a 4-line opener tied to specific tools they use (Salesforce, HubSpot, Cursor) and last quarter's announcement.
작동 방식
Describe your product or paste a product brief. If you're in your product's codebase, the skill reads it directly.
Add ICP filters: industry, size, geo, technologies, growth-stage signals you care about.
The skill searches for companies that match, checking for hiring signals, recent news, funding rounds, and technology hits.
Each account is scored 1 to 10 against your ICP, with the reasoning surfaced and a decision-maker role identified.
Output drops as a ranked markdown report plus CSV ready for Apollo, Outreach, or Salesforce. Each row has a 'why now' line tied to specific recent signals.
예시
Product: data-masking tool for AI coding assistants (Copilot, Cursor). ICP: fintech or healthtech, Series B and above, 50-500 engineers, evidence of AI-coding-assistant usage in GitHub or job posts.
20 fit-scored accounts. 6 strong fits (8-10/10), 9 partial fits (5-7), 5 weak fits. Sectors: 14 fintech, 6 healthtech. Geos: 11 US, 5 EU, 4 APAC.
Series C fintech, 280 engineers, 4 active Cursor licenses (LinkedIn job post 2 weeks ago lists 'Cursor power-user' as desired skill). Just shipped a fraud product. Decision-maker: Head of Engineering. Why now: recent PCI compliance audit announcement plus active AI-coding adoption.
'Saw your Cursor adoption and the PCI audit announcement: we built data-masking for the exact gap between those two.' Compares to their currently public competitor on the dimension they care about.
Open results.csv, paste top 6 into Apollo as a new list. Use the 'why now' lines as the first-touch opener. Schedule a follow-up enrichment run in 2 weeks for the partial fits to flag any that moved to 8 and above after new signals.
개선되는 지표
지원 도구
Funding-round and growth-stage signal lookup
Alternative cold-outbound destination for the ranked account CSV
Import the CSV as new lead or account records with the fit score as a custom field
Paste the ranked CSV as a new list and the 'why now' lines as first-touch openers
Source for decision-maker LinkedIn URLs and the activity signals (job posts, leadership change, recent posts) that feed the fit score
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Lead Research Assistant
This skill helps you identify and qualify potential leads for your business by analyzing your product/service, understanding your ideal customer profile, and providing actionable outreach strategies.
When to Use This Skill
- Finding potential customers or clients for your product/service
- Building a list of companies to reach out to for partnerships
- Identifying target accounts for sales outreach
- Researching companies that match your ideal customer profile
- Preparing for business development activities
What This Skill Does
- Understands Your Business: Analyzes your product/service, value proposition, and target market
- Identifies Target Companies: Finds companies that match your ideal customer profile based on:
- Industry and sector
- Company size and location
- Technology stack and tools they use
- Growth stage and funding
- Pain points your product solves
- Prioritizes Leads: Ranks companies based on fit score and relevance
- Provides Contact Strategies: Suggests how to approach each lead with personalized messaging
- Enriches Data: Gathers relevant information about decision-makers and company context
How to Use
Basic Usage
Simply describe your product/service and what you're looking for:
I'm building [product description]. Find me 10 companies in [location/industry]
that would be good leads for this.
With Your Codebase
For even better results, run this from your product's source code directory:
Look at what I'm building in this repository and identify the top 10 companies
in [location/industry] that would benefit from this product.
Advanced Usage
For more targeted research:
My product: [description]
Ideal customer profile:
- Industry: [industry]
- Company size: [size range]
- Location: [location]
- Current pain points: [pain points]
- Technologies they use: [tech stack]
Find me 20 qualified leads with contact strategies for each.
Instructions
When a user requests lead research:
-
Understand the Product/Service
- If in a code directory, analyze the codebase to understand the product
- Ask clarifying questions about the value proposition
- Identify key features and benefits
- Understand what problems it solves
-
Define Ideal Customer Profile
- Determine target industries and sectors
- Identify company size ranges
- Consider geographic preferences
- Understand relevant pain points
- Note any technology requirements
-
Research and Identify Leads
- Search for companies matching the criteria
- Look for signals of need (job postings, tech stack, recent news)
- Consider growth indicators (funding, expansion, hiring)
- Identify companies with complementary products/services
- Check for budget indicators
-
Prioritize and Score
- Create a fit score (1-10) for each lead
- Consider factors like:
- Alignment with ICP
- Signals of immediate need
- Budget availability
- Competitive landscape
- Timing indicators
-
Provide Actionable Output
For each lead, provide:
- Company Name and website
- Why They're a Good Fit: Specific reasons based on their business
- Priority Score: 1-10 with explanation
- Decision Maker: Role/title to target (e.g., "VP of Engineering")
- Contact Strategy: Personalized approach suggestions
- Value Proposition: How your product solves their specific problem
- Conversation Starters: Specific points to mention in outreach
- LinkedIn URL: If available, for easy connection
-
Format the Output
Present results in a clear, scannable format:
# Lead Research Results ## Summary - Total leads found: [X] - High priority (8-10): [X] - Medium priority (5-7): [X] - Average fit score: [X] --- ## Lead 1: [Company Name] **Website**: [URL] **Priority Score**: [X/10] **Industry**: [Industry] **Size**: [Employee count/revenue range] **Why They're a Good Fit**: [2-3 specific reasons based on their business] **Target Decision Maker**: [Role/Title] **LinkedIn**: [URL if available] **Value Proposition for Them**: [Specific benefit for this company] **Outreach Strategy**: [Personalized approach - mention specific pain points, recent company news, or relevant context] **Conversation Starters**: - [Specific point 1] - [Specific point 2] --- [Repeat for each lead] -
Offer Next Steps
- Suggest saving results to a CSV for CRM import
- Offer to draft personalized outreach messages
- Recommend prioritization based on timing
- Suggest follow-up research for top leads
Examples
Example 1: From Lenny's Newsletter
User: "I'm building a tool that masks sensitive data in AI coding assistant queries. Find potential leads."
Output: Creates a prioritized list of companies that:
- Use AI coding assistants (Copilot, Cursor, etc.)
- Handle sensitive data (fintech, healthcare, legal)
- Have evidence in their GitHub repos of using coding agents
- May have accidentally exposed sensitive data in code
- Includes LinkedIn URLs of relevant decision-makers
Example 2: Local Business
User: "I run a consulting practice for remote team productivity. Find me 10 companies in the Bay Area that recently went remote."
Output: Identifies companies that:
- Recently posted remote job listings
- Announced remote-first policies
- Are hiring distributed teams
- Show signs of remote work challenges
- Provides personalized outreach strategies for each
Tips for Best Results
- Be specific about your product and its unique value
- Run from your codebase if applicable for automatic context
- Provide context about your ideal customer profile
- Specify constraints like industry, location, or company size
- Request follow-up research on promising leads for deeper insights
Related Use Cases
- Drafting personalized outreach emails after identifying leads
- Building a CRM-ready CSV of qualified prospects
- Researching specific companies in detail
- Analyzing competitor customer bases
- Identifying partnership opportunities