Unternehmens-ICP-Bewertung mit Explorium

Fortgeschritten

Dies ist ein Lead Generation, AI Summarization-Bereich Automatisierungsworkflow mit 8 Nodes. Hauptsächlich werden FormTrigger, HttpRequest, Agent, McpClientTool, LmChatAnthropic und andere Nodes verwendet. Automatisierung der ICP-Bewertung von Unternehmen durch Explorium-Daten und Claude AI-Analyse

Voraussetzungen
  • Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • Anthropic API Key
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "id": "9h9ppDLnWx1FriWK",
  "meta": {
    "instanceId": "0a70652f43c1b29dd16c35b61a38fd31c8004f58bc7e723bf43262a797407c77",
    "templateId": "4262",
    "templateCredsSetupCompleted": true
  },
  "name": "Score Company ICP with Explorium",
  "tags": [],
  "nodes": [
    {
      "id": "53ac44a9-4774-42f5-8b3d-d7c83272c1fa",
      "name": "Bei Formularübermittlung",
      "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": "Notiz4",
      "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": "Notiz",
      "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": "Notiz7",
      "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": "KI-Agent",
      "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": "Anthropic Chat-Modell",
      "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": "HTTP Anfrage",
      "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": {
    "7c5a0104-f73c-42be-bb1b-6b335e81501f": {
      "main": [
        [
          {
            "node": "3b60d56a-b305-40af-aea7-f9847bdc3aee",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "53b09fbf-c8da-43a0-b7ac-ed9ebacd2dba": {
      "ai_tool": [
        [
          {
            "node": "7c5a0104-f73c-42be-bb1b-6b335e81501f",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "53ac44a9-4774-42f5-8b3d-d7c83272c1fa": {
      "main": [
        [
          {
            "node": "7c5a0104-f73c-42be-bb1b-6b335e81501f",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "6f0c8ee4-5aad-4b49-9202-bb2071f6b933": {
      "ai_languageModel": [
        [
          {
            "node": "7c5a0104-f73c-42be-bb1b-6b335e81501f",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - Lead-Generierung, KI-Zusammenfassung

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes8
Kategorie2
Node-Typen6
Schwierigkeitsbeschreibung

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Kategorien: 34