LinkedIn 개인 ICP 점수 자동화 (Airtop과 Google Sheets)
초급
이것은Product, AI분야의자동화 워크플로우로, 5개의 노드를 포함합니다.주로 Code, Airtop, GoogleSheets, ManualTrigger 등의 노드를 사용하며인공지능 기술을 결합하여 스마트 자동화를 구현합니다. LinkedIn 개인 ICP 점수 자동화 (Airtop과 Google Sheets)
사전 요구사항
- •Google Sheets API 인증 정보
사용된 노드 (5)
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
"meta": {
"instanceId": "257476b1ef58bf3cb6a46e65fac7ee34a53a5e1a8492d5c6e4da5f87c9b82833"
},
"nodes": [
{
"id": "45ae6e88-3fda-4e95-84db-085a895cc564",
"name": "‘Test workflow’ 클릭 시",
"type": "n8n-nodes-base.manualTrigger",
"position": [
260,
-100
],
"parameters": {},
"typeVersion": 1
},
{
"id": "09f71a7c-1219-426d-8563-fa05654cab44",
"name": "ICP PersonScoring 계산",
"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": "응답 형식 지정",
"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": "행 업데이트",
"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": "개인 정보 가져오기",
"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
}
]
]
}
}
}자주 묻는 질문
이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
이 워크플로우는 어떤 시나리오에 적합한가요?
초급 - 제품, 인공지능
유료인가요?
이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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