Score de l'ICP d'entreprise avec Explorium

Intermédiaire

Ceci est unLead Generation, AI Summarizationworkflow d'automatisation du domainecontenant 8 nœuds.Utilise principalement des nœuds comme FormTrigger, HttpRequest, Agent, McpClientTool, LmChatAnthropic. Automatisation du score ICP (Ideal Customer Profile) pour les entreprises avec les données Explorium et l'analyse Claude AI

Prérequis
  • Peut nécessiter les informations d'identification d'authentification de l'API cible
  • Clé API Anthropic
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
  "id": "9h9ppDLnWx1FriWK",
  "meta": {
    "instanceId": "0a70652f43c1b29dd16c35b61a38fd31c8004f58bc7e723bf43262a797407c77",
    "templateId": "4262",
    "templateCredsSetupCompleted": true
  },
  "name": "Score Company ICP with Explorium",
  "tags": [],
  "nodes": [
    {
      "id": "53ac44a9-4774-42f5-8b3d-d7c83272c1fa",
      "name": "On form submission",
      "type": "n8n-nodes-base.formTrigger",
      "position": [
        1300,
        880
      ],
      "webhookId": "2d5e3676-5284-4da1-bdf5-34f92d8d435f",
      "parameters": {
        "options": {},
        "formTitle": "Company ICP scoring",
        "formFields": {
          "values": [
            {
              "fieldLabel": "Company Name",
              "placeholder": "Apple",
              "requiredField": true
            }
          ]
        },
        "formDescription": "=This automation takes company's Linkedin Profile URL and Airtop Profile (authenticated for Linkedin) and returns the company's ICP score"
      },
      "typeVersion": 2.2
    },
    {
      "id": "376edace-c71d-40ca-a0e7-4cc6d11bed17",
      "name": "Note adhésive4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1100,
        720
      ],
      "parameters": {
        "width": 400,
        "height": 500,
        "content": "## Input Parameters\nRun this workflow using a form "
      },
      "typeVersion": 1
    },
    {
      "id": "8687eea7-1059-43e4-8575-f8a6ebeae0a2",
      "name": "Note adhésive",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1520,
        720
      ],
      "parameters": {
        "color": 5,
        "width": 960,
        "height": 500,
        "content": "## Calculate ICP"
      },
      "typeVersion": 1
    },
    {
      "id": "5f2723ea-8df0-430e-8a4c-a057b7e6081a",
      "name": "Note adhésive7",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        360,
        460
      ],
      "parameters": {
        "width": 700,
        "height": 880,
        "content": "# 🧠 ICP Scoring Agent (n8n + Explorium + LLM)\n\n## 🔧 How It Works\n1. Input: Company name\n2. MCP Server pulls firmographic & tech data\n3. LLM scores the company using 3-pillar framework\n4. Output: Structured Google doc created with leveraged @AgentGeeks formater \n\n## 📊 Scoring System (100 pts total)\n| Pillar                    | Max |\n|---------------------------|-----|\n| Strategic Fit             | 40  |\n| AI / Tech Readiness       | 40  |\n| Engagement & Reachability | 20  |\n\n## 🧠 Criteria\n- **Strategic Fit:** Industry, size, buyer roles, use case\n- **Tech Readiness:** AI focus, hiring, stack maturity\n- **Reachability:** Geography, contactability, data quality\n\n## 🏁 Verdicts\n- **90–100:** ⭐ Ideal ICP  \n- **70–89:** ✅ Good Fit  \n- **40–69:** ⚠️ Medium Fit  \n- **< 40:** ❌ Poor Fit  \n\n## 💼 Use Case\nScore and rank companies automatically for GTM prioritization. Use structured JSON to map into CRMs, Docs, or lead routing systems.\n"
      },
      "typeVersion": 1
    },
    {
      "id": "7c5a0104-f73c-42be-bb1b-6b335e81501f",
      "name": "Agent IA",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1620,
        880
      ],
      "parameters": {
        "text": "=Generate a clean Markdown report for the company \"{{ $json['Company Name'] }}\" based on the following:\n\n- Strategic Fit (score out of 40, summary, justification)\n- AI/Tech Readiness (score out of 40, summary, justification)\n- Engagement & Reachability (score out of 20, summary, justification)\n- Final Summary (1–2 sentence wrap-up)\n- Total ICP Score: Sum of the 3 categories (max = 100)\n- Verdict: Poor Fit, Medium Fit, Good Fit, or Ideal ICP\n\nThe output should be a clean Markdown document with headers and bold labels, like this:\n\n## 📌 Strategic Fit  \n**Score:** 36 / 40  \n**Summary:** ...  \n**Justification:** ...\n\nDo not include any explanation or JSON. Just return the report in Markdown.\n",
        "options": {
          "systemMessage": "=You are an AI business analyst tasked with generating clean Markdown reports summarizing ICP (Ideal Customer Profile) evaluations.\n\nUse this 3-pillar scoring system (max 100 points total):\n- Strategic Fit: 0–40 points\n- AI/Tech Readiness: 0–40 points\n- Engagement & Reachability: 0–20 points\n\nYour output must:\n- Be formatted in Markdown\n- Use headers (##) and bold labels (e.g., **Score:**)\n- Include only the report — no preamble, explanation, or extra intro\n- Always show the total score out of 100\n- Use one of the following verdicts: Poor Fit, Medium Fit, Good Fit, Ideal ICP\n\nNever scale the total to 300. Never include anything outside the report.\n"
        },
        "promptType": "define"
      },
      "typeVersion": 1.9
    },
    {
      "id": "53b09fbf-c8da-43a0-b7ac-ed9ebacd2dba",
      "name": "MCP Client",
      "type": "@n8n/n8n-nodes-langchain.mcpClientTool",
      "position": [
        1780,
        1080
      ],
      "parameters": {
        "sseEndpoint": "mcp.explorium.ai/sse",
        "authentication": "headerAuth"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "LZOE1nqmRk3X6r1J",
          "name": "Explorium"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "6f0c8ee4-5aad-4b49-9202-bb2071f6b933",
      "name": "Modèle de chat Anthropic",
      "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
      "position": [
        1620,
        1060
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "claude-3-7-sonnet-20250219",
          "cachedResultName": "Claude 3.7 Sonnet"
        },
        "options": {}
      },
      "credentials": {
        "anthropicApi": {
          "id": "FQdE6twB8nCJNoxV",
          "name": "Anthropic account"
        }
      },
      "typeVersion": 1.3
    },
    {
      "id": "3b60d56a-b305-40af-aea7-f9847bdc3aee",
      "name": "Requête HTTP",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        2060,
        880
      ],
      "parameters": {
        "url": "https://md2doc.n8n.aemalsayer.com",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "output",
              "value": "={{ $json.output }}"
            },
            {
              "name": "fileName",
              "value": "={{ $('On form submission').item.json['Company Name'] }} ICP Report"
            }
          ]
        },
        "nodeCredentialType": "googleDocsOAuth2Api"
      },
      "credentials": {
        "googleDocsOAuth2Api": {
          "id": "mZUWrRtmU1aouO4A",
          "name": "Google Docs account"
        }
      },
      "typeVersion": 4.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "d145e079-faa1-4302-b5c9-fb7ad2841560",
  "connections": {
    "AI Agent": {
      "main": [
        [
          {
            "node": "HTTP Request",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "53b09fbf-c8da-43a0-b7ac-ed9ebacd2dba": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "53ac44a9-4774-42f5-8b3d-d7c83272c1fa": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Anthropic Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}
Foire aux questions

Comment utiliser ce workflow ?

Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.

Dans quelles scénarios ce workflow est-il adapté ?

Intermédiaire - Génération de leads, Résumé IA

Est-ce payant ?

Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.

Informations sur le workflow
Niveau de difficulté
Intermédiaire
Nombre de nœuds8
Catégorie2
Types de nœuds6
Description de la difficulté

Adapté aux utilisateurs expérimentés, avec des workflows de complexité moyenne contenant 6-15 nœuds

Liens externes
Voir sur n8n.io

Partager ce workflow

Catégories

Catégories: 34