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Templates by Itamar

Enrich company profiles with Explorium MCP and Claude AI for GTM research

πŸ•΅οΈ Company Research Agent (n8n + Explorium + LLM) This n8n workflow automates company research by combining Explorium’s MCP server, web scraping tools, and an AI agent. Results are written to a Google Sheet for easy use in GTM, product analysis, or competitive research. --- πŸš€ What It Does Given a list of company domains or names, this workflow will: Look up company information using: 🧠 LLM Agent to guide the research πŸ”Ž Explorium MCP Server for firmographic & tech signals 🌐 Website content and SerpAPI scraping (optional) Extract key commercial details (see below) Format the output in a consistent JSON structure Update a connected Google Sheet with the enriched results --- 🧩 Extracted Fields Each company is enriched with: domain linkedinUrl hasfreetrial cheapest_plan hasenterpriseplan lastcasestudy_link market (e.g., B2B or B2C) integrations (e.g., Slack, Hubspot, MySQL) enrichment_status --- πŸ“₯ Input Sheet Format | input | |-------------| | Explorium | | n8n | | Apple | | ... | --- πŸ“€ Output Sheet Format | domain | linkedinUrl | hasfreetrial | cheapestplan | hasenterpriseplan | lastcasestudylink | market | integrations | enrichment_status | |--------------|----------------------------------|----------------|----------------|----------------------|-----------------------------|--------|---------------------------------------------------|-------------------| | Explorium.ai | https://linkedin.com/company/... | TRUE | 69 | TRUE | https://www.explorium.com | B2B | ["HubSpot", "Zapier", "Salesforce", ...] | done | | n8n.io | https://linkedin.com/company/... | TRUE | 20 | TRUE | https://n8n.io/case-studies | B2B | ["Slack", "Gmail", "MySQL", "Google Sheets", ...] | done | --- πŸ› οΈ Tools Used n8n (Automation platform) Explorium MCP Server – rich company enrichment via API Anthropic Claude or OpenAI – used by the AI researcher Google Sheets – stores output data Structured Output Parser – ensures clean, predictable JSON formatting --- πŸ“¦ How to Set It Up Add your company domains or names to the input sheet Configure your MCP and SerpAPI credentials in n8n Run the workflow using the Test Workflow trigger Watch the sheet populate with results You can adapt the system to output different formats or fields depending on your team's research goals. --- πŸ“Œ Use Cases Competitive landscape analysis Lead intelligence for outbound campaigns Feature benchmarking (e.g., who offers enterprise or free trial) VC/investment research --- 🧠 Notes This agent is easily customizable. Adjust the LLM prompt or Output Parser to extract different properties. Explorium MCP is leveraged as the core enrichment engine, ensuring signal accuracy and freshness.

ItamarBy Itamar
554

Automate company ICP scoring with Explorium data and Claude AI analysis

🧠 ICP Scoring Agent (n8n + Explorium + LLM) This workflow automates Ideal Customer Profile (ICP) scoring for any company using a combination of Explorium data and an LLM-driven evaluation framework. --- πŸ”§ How It Works Input: Company name is submitted via form. Data Enrichment: Explorium's MCP Server is used to fetch firmographic, hiring, and tech data about the company. Scoring Logic: An AI agent (LLM) applies a 3-pillar framework to assess and score the company. Output: A structured JSON or Google Doc summary is generated using the AgentGeeks formatter. --- πŸ“Š Scoring System (100 points total) | Pillar | Max Points | |------------------------------|------------| | Strategic Fit | 40 | | AI / Tech Readiness | 40 | | Engagement & Reachability | 20 | 🧠 Scoring Criteria Strategic Fit: Industry, size, use case, buyer roles Tech Readiness: AI maturity, hiring trends, stack visibility Reachability: Geography, contactability, data quality --- 🎯 Verdict Scale 🟩 90–100: Ideal ICP βœ… 70–89: Good Fit 🟨 40–69: Medium Fit ❌ < 40: Poor Fit --- πŸ“¦ Workflow Components Trigger: Form submission via webhook MCP Client: Pulls enriched company data via Explorium's MCP API AI Agent: Uses Anthropic Claude (or other LLM) to calculate scores Output: Results are posted to a structured endpoint (e.g. Google Doc or JSON API) --- 🧰 Dependencies n8n (self-hosted or cloud) Explorium MCP credentials and access LLM API (e.g., Anthropic Claude, OpenAI, etc.) Optional: AgentGeeks formatter or similar doc generator --- πŸ’Ό Use Case This ICP scoring system is designed for GTM and sales teams to: Automate lead prioritization Qualify accounts before outbounding Sync ICP data into CRMs, routing systems, or reporting layers --- πŸ“ˆ Example Output in Google Doc json { "company": "Acme Inc.", "score": 87, "verdict": "Good Fit", "pillars": { "strategic_fit": 35, "tech_readiness": 37, "reachability": 15 }, "summary": "Acme Inc. is a mid-sized SaaS company with strong AI hiring activity and a buyer profile aligned to enterprise IT. Moderate reachability via firmographic signals." }

ItamarBy Itamar
285
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