Puntuación automática de ICP personal para LinkedIn (Airtop y Google Sheets)

Principiante

Este es unProduct, AIflujo de automatización del dominio deautomatización que contiene 5 nodos.Utiliza principalmente nodos como Code, Airtop, GoogleSheets, ManualTrigger, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Puntuación automática de ICP personal en LinkedIn (Airtop y Google Sheets)

Requisitos previos
  • Credenciales de API de Google Sheets
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
{
  "meta": {
    "instanceId": "257476b1ef58bf3cb6a46e65fac7ee34a53a5e1a8492d5c6e4da5f87c9b82833"
  },
  "nodes": [
    {
      "id": "45ae6e88-3fda-4e95-84db-085a895cc564",
      "name": "Al hacer clic en ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        260,
        -100
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "09f71a7c-1219-426d-8563-fa05654cab44",
      "name": "Calcular ICP PersonScoring",
      "type": "n8n-nodes-base.airtop",
      "position": [
        700,
        -100
      ],
      "parameters": {
        "url": "={{ $json['Linkedin_URL_Person'] }}",
        "prompt": "Please extract the following information from the LinkedIn profile page:\n\n1. **Full Name**: Extract the full name of the individual.\n2. **Current or Most Recent Job Title**: Identify the job title next to the logo of the current or last employer.\n3a. **Current or Most Recent Employer**: Extract the name of the first company in the employment experience block. \n3b. Linkedin Company URL of the Current or Most Recent Employer: Extract the link of the first company in the employment experience block\n4. **Location**: Extract the location of the individual.\n5. **Number of Connections**: Extract the number of connections the individual has.\n6. **Number of Followers**: Extract the number of followers the individual has.\n7. **About Section Text**: Extract the text from the 'About' section.\n8. **Interest Level in AI**: Determine the person's interest level in AI (e.g., beginner, intermediate, advanced, expert).\n9. **Seniority Level**: Determine the seniority level of the person (e.g., junior, mid-level, senior, executive).\n10. **Technical Depth**: Determine the technical depth of the person (e.g., basic, intermediate, advanced, expert).\n11. **ICP Score**: Calculate the ICP Score based on the following criteria:\n    - AI Interest: beginner-5 pts, intermediate-10 pts, advanced-25 pts, expert-35 pts\n    - Technical Depth: basic-5 pts, intermediate-15 pts, advanced-25 pts, expert-35 pts\n    - Seniority Level: junior-5 pts, mid-level-15 pts, senior-25 pts, executive-30 pts\n    - Sum the points to get the ICP Score.\n\nEnsure that the extracted information is accurate and formatted according to the specified output schema.\n\nFor example, if the LinkedIn profile is of a senior software engineer with a strong interest in AI, return the following output:\n{\n  \"full_name\": \"Jane Doe\",\n  \"current_or_last_employer\": \"Tech Innovations Inc.\",\n  \"current_or_last_title\": \"Senior Software Engineer\",\n  \"location\": \"San Francisco, CA\",\n  \"number_of_connections\": 500,\n  \"number_of_followers\": 300,\n  \"about_section_text\": \"Experienced software engineer with a passion for developing innovative programs that expedite the efficiency and effectiveness of organizational success.\",\n  \"ai_interest_level\": \"advanced\",\n  \"seniority_level\": \"senior\",\n  \"technical_depth\": \"advanced\",\n  \"icp_score\": 85\n}\n",
        "resource": "extraction",
        "operation": "query",
        "sessionMode": "new",
        "additionalFields": {
          "outputSchema": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"full_name\": {\n      \"type\": \"string\",\n      \"description\": \"The full name of the individual.\"\n    },\n    \"current_or_last_title\": {\n      \"type\": \"string\",\n      \"description\": \"The job title next to the logo of the current or last employer.\"\n    },\n    \"current_or_last_employer\": {\n      \"type\": \"string\",\n      \"description\": \"The name of the first company in the employment experience block.\"\n    },\n    \"linkedin_company_url\": {\n      \"type\": \"string\",\n      \"description\": \"The LinkedIn URL of the first company in the employment experience block.\"\n    },\n    \"location\": {\n      \"type\": \"string\",\n      \"description\": \"The location of the individual.\"\n    },\n    \"number_of_connections\": {\n      \"type\": \"integer\",\n      \"description\": \"The number of connections the individual has.\"\n    },\n    \"number_of_followers\": {\n      \"type\": \"integer\",\n      \"description\": \"The number of followers the individual has.\"\n    },\n    \"about_section_text\": {\n      \"type\": \"string\",\n      \"description\": \"The text from the 'About' section.\"\n    },\n    \"ai_interest_level\": {\n      \"type\": \"string\",\n      \"description\": \"The person's interest level in AI.\"\n    },\n    \"seniority_level\": {\n      \"type\": \"string\",\n      \"description\": \"The seniority level of the person.\"\n    },\n    \"technical_depth\": {\n      \"type\": \"string\",\n      \"description\": \"The technical depth of the person.\"\n    },\n    \"icp_score\": {\n      \"type\": \"integer\",\n      \"description\": \"The ICP Score calculated based on AI interest, technical depth, and seniority level.\"\n    }\n  },\n  \"required\": [\n    \"full_name\",\n    \"current_or_last_title\",\n    \"current_or_last_employer\",\n    \"linkedin_company_url\",\n    \"location\",\n    \"number_of_connections\",\n    \"number_of_followers\",\n    \"about_section_text\",\n    \"ai_interest_level\",\n    \"seniority_level\",\n    \"technical_depth\",\n    \"icp_score\"\n  ],\n  \"additionalProperties\": false,\n  \"$schema\": \"http://json-schema.org/draft-07/schema#\"\n}\n"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "28c2c1d4-f43f-46c6-b21d-fbaf5fed4efa",
      "name": "Formatear respuesta",
      "type": "n8n-nodes-base.code",
      "position": [
        900,
        -100
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const row_number = $('Get person').item.json.row_number\nconst Linkedin_URL_Person = $('Get person').item.json.Linkedin_URL_Person\nconst ICP_Score_Person = JSON.parse($input.item.json.data.modelResponse).icp_score\n\nreturn { json: {\n  row_number,\n  Linkedin_URL_Person,\n  ICP_Score_Person\n}};"
      },
      "typeVersion": 2
    },
    {
      "id": "1646b60c-21f2-4222-bc4c-8660184fa46a",
      "name": "Actualizar fila",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        1120,
        -100
      ],
      "parameters": {
        "columns": {
          "value": {},
          "schema": [
            {
              "id": "Linkedin_URL_Person",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Linkedin_URL_Person",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "ICP_Score_Person",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "ICP_Score_Person",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "row_number",
              "type": "string",
              "display": true,
              "removed": false,
              "readOnly": true,
              "required": false,
              "displayName": "row_number",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "autoMapInputData",
          "matchingColumns": [
            "row_number"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "update",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1WC_awgb-Ohtb0f4o_OJgRcvunTLuS8kFQgk6l8fkR2Q/edit#gid=0",
          "cachedResultName": "Person"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1WC_awgb-Ohtb0f4o_OJgRcvunTLuS8kFQgk6l8fkR2Q",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1WC_awgb-Ohtb0f4o_OJgRcvunTLuS8kFQgk6l8fkR2Q/edit?usp=drivesdk",
          "cachedResultName": "ICP Score for Template"
        }
      },
      "typeVersion": 4.5
    },
    {
      "id": "5a151773-1075-4a9f-9637-6241e7137638",
      "name": "Obtener persona",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        480,
        -100
      ],
      "parameters": {
        "options": {},
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1WC_awgb-Ohtb0f4o_OJgRcvunTLuS8kFQgk6l8fkR2Q/edit#gid=0",
          "cachedResultName": "Person"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1WC_awgb-Ohtb0f4o_OJgRcvunTLuS8kFQgk6l8fkR2Q",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1WC_awgb-Ohtb0f4o_OJgRcvunTLuS8kFQgk6l8fkR2Q/edit?usp=drivesdk",
          "cachedResultName": "ICP Score for Template"
        }
      },
      "typeVersion": 4.5
    }
  ],
  "pinData": {},
  "connections": {
    "5a151773-1075-4a9f-9637-6241e7137638": {
      "main": [
        [
          {
            "node": "09f71a7c-1219-426d-8563-fa05654cab44",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "28c2c1d4-f43f-46c6-b21d-fbaf5fed4efa": {
      "main": [
        [
          {
            "node": "1646b60c-21f2-4222-bc4c-8660184fa46a",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "09f71a7c-1219-426d-8563-fa05654cab44": {
      "main": [
        [
          {
            "node": "28c2c1d4-f43f-46c6-b21d-fbaf5fed4efa",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "45ae6e88-3fda-4e95-84db-085a895cc564": {
      "main": [
        [
          {
            "node": "5a151773-1075-4a9f-9637-6241e7137638",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
Preguntas frecuentes

¿Cómo usar este flujo de trabajo?

Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.

¿En qué escenarios es adecuado este flujo de trabajo?

Principiante - Producto, Inteligencia Artificial

¿Es de pago?

Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.

Información del flujo de trabajo
Nivel de dificultad
Principiante
Número de nodos5
Categoría2
Tipos de nodos4
Descripción de la dificultad

Adecuado para principiantes de n8n, flujos de trabajo simples con 1-5 nodos

Autor
Cesar @ Airtop AI

Cesar @ Airtop AI

@cesar-at-airtop

AI Engineer at Airtop AI

Enlaces externos
Ver en n8n.io

Compartir este flujo de trabajo

Categorías

Categorías: 34