연락처 정보 풍부화
고급
이것은Lead Generation, AI Summarization분야의자동화 워크플로우로, 24개의 노드를 포함합니다.주로 If, Set, Code, Sort, Limit 등의 노드를 사용하며. Apollo, LinkedIn 및 GPT-4o 기반의 전면적인 연락처 정보 풍부화, HubSpot에 적합
사전 요구사항
- •HubSpot API Key
- •대상 API의 인증 정보가 필요할 수 있음
- •OpenAI API Key
사용된 노드 (24)
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
{
"id": "t7e4sQzh96e0xaq7",
"meta": {
"instanceId": "219ad8a5631572c9ac16d4e2fec49250f591e94570ab0858fd2013d005c6d5c6",
"templateCredsSetupCompleted": true
},
"name": "contact enrichment",
"tags": [
{
"id": "0zTM91F1nQEHLKzN",
"name": "template_upload",
"createdAt": "2025-07-17T15:01:40.334Z",
"updatedAt": "2025-07-17T15:01:40.334Z"
}
],
"nodes": [
{
"id": "dbf704c3-2b0e-4158-b5d8-ca1d138d141a",
"name": "다른 워크플로우 실행 시",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
-336,
752
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "name"
},
{
"name": "email"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "747be8f0-cf2b-412d-b7a9-93051ff0a11b",
"name": "Apollo로 풍부화",
"type": "n8n-nodes-base.httpRequest",
"position": [
128,
752
],
"parameters": {
"url": "https://api.apollo.io/api/v1/people/match",
"method": "POST",
"options": {},
"sendQuery": true,
"sendHeaders": true,
"queryParameters": {
"parameters": [
{
"name": "reveal_personal_emails",
"value": "false"
},
{
"name": "reveal_phone_number",
"value": "false"
},
{
"name": "email",
"value": "={{ $json.email }}"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "Cache-Control",
"value": "no-cache"
},
{
"name": "accept",
"value": "application/json"
},
{
"name": "x-api-key",
"value": "YOUR-API-KEY"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "3630169c-2677-4124-a19b-f9d1a2bfdcce",
"name": "발견됨?",
"type": "n8n-nodes-base.if",
"position": [
352,
752
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "8037609c-e921-4ef9-9d34-375a6bd471ad",
"operator": {
"type": "string",
"operation": "exists",
"singleValue": true
},
"leftValue": "={{ $json.person && ($json.person.name || $json.person.email) }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "00a26c55-aa97-4255-b002-cb77bc1a8780",
"name": "HubSpot1에서 풍부화",
"type": "n8n-nodes-base.hubspot",
"position": [
3168,
752
],
"parameters": {
"email": "={{ $json.output.email }}",
"options": {},
"authentication": "oAuth2",
"additionalFields": {
"city": "={{ $json.output.city }}",
"country": "={{ $json.output.country_region }}",
"jobTitle": "={{ $json.output.job_title }}",
"customPropertiesUi": {
"customPropertiesValues": [
{
"value": "={{ $json.output.linkedin_url }}",
"property": "linkedin_account"
},
{
"value": "={{ $json.output.experience_summary }}",
"property": "experience_summary"
},
{
"value": "={{ $json.output.education_summary }}",
"property": "education_summary"
},
{
"value": "={{ Math.floor(Date.now() / 86400000) * 86400000 }}",
"property": "last_enrichment_date"
},
{
"value": "={{ $json.output.recent_linkedin_activity }}",
"property": "recent_linkedin_posts"
}
]
}
}
},
"credentials": {
"hubspotOAuth2Api": {
"id": "DAzRcQP1uXfOKZuC",
"name": "HubSpot account"
}
},
"retryOnFail": true,
"typeVersion": 2.1
},
{
"id": "01dd3096-dcb3-4e0d-97ac-581a7d08b55f",
"name": "자동 수정 출력 파서2",
"type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
"position": [
2672,
912
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "b819ac28-783c-49d5-8125-fb824fd30661",
"name": "구조화 출력 파서2",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
2832,
1040
],
"parameters": {
"jsonSchemaExample": "{\n \"email\": \"testuser1@companydomain.com\",\n \"linkedin_url\": \"http://www.linkedin.com/in/testuser1\",\n \"job_title\": \"CEO & Co-Founder\",\n \"city\": \"Denver\",\n \"state\": \"Colorado\",\n \"country_region\": \"United States\",\n \"experience_summary\": \"User experience content\",\n \"education_summary\": \"Education Level content\",\n \"recent_linkedin_activity\": \"• Posted about winning 82 % of competitive deals and key sales mantras (6 hours ago)\\n• Shared guidance on setting realistic expectations for a new VP Sales’ impact (1 day ago)\"\n}"
},
"typeVersion": 1.2
},
{
"id": "06391ddf-2071-4b80-86ad-85c922ae33c8",
"name": "OpenAI 채팅 모델5",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
2672,
1040
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "HH848Gw8QSS5TUKW",
"name": "OpenAi"
}
},
"typeVersion": 1.2
},
{
"id": "3aa928c0-6f12-4f5c-9acb-018b0b87667e",
"name": "풍부화 요약 에이전트",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
2528,
752
],
"parameters": {
"text": "=Here’s the person data to enrich for CRM: \n{{ JSON.stringify($json, null, 2) }}\n\nHere's the recent activity to summarize for the CRM:\n{{ $json.recent_activity }}",
"messages": {
"messageValues": [
{
"message": "=# Overview\nYou are “HubSpot-Enrichment-Agent”, a data-cleaning assistant that converts messy person JSON enrichment data into concise, human-friendly fields ready to upsert into HubSpot. \n\n## OBJECTIVE\nReturn **one** JSON object with exactly these keys:\n\n{\n \"email\": string|null,\n \"linkedin_url\": string|null,\n \"job_title\": string|null, // title at the company that matches the email domain\n \"city\": string|null,\n \"state\": string|null,\n \"country_region\": string|null,\n \"experience_summary\": string|null, // 3-4 recent roles, bullet list, newest → oldest\n \"education_summary\": string|null, // highest degree(s) & institution(s), 1-2 lines\n \"recent_linkedin_activity\": string|null\n}\n\n## RULES & LOGIC\n\n1. **Email, LinkedIn URL, City, Country/Region** \n *Pass through directly if present; else `null`.*\n\n2. **Job Title (relevant)** \n - Use the employment record whose `organization_name` (or website) shares the **same email domain** as `email`. \n - If no domain match, pick the most recent item where `current == true`. \n - Strip membership-only titles (“Member”, “Angel Investor”) unless no better option exists.\n\n3. **Experience Summary** \n - Sort `employment_history` by `start_date` DESC. \n - Select the first **3–4** roles that are either `current == true` _or_ have an `end_date` within the last 10 years. \n - Format each as: \n `• <Title>, <Org> — <YYYY-start> → <\"Present\" | YYYY-end>` \n - Join with line breaks. Return `null` if list is empty.\n\n4. **Education Summary** \n - Look for the highest‐level degree (Doctorate > MBA/Master’s > Bachelor’s > Associate > Other). \n - Summarise as: \n `<Degree>, <Institution> (<YYYY-end>)`. \n - If multiple relevant degrees, include up to two lines. \n - If no education data, return `null`.\n\n5. **Recent LinkedIn Activity** \n - If a `recent_activity` or similar field exists, pull the latest **1-3** public posts or updates. \n - Summarise in plain text, e.g., \n `“Commented on procurement AI article” (3 days ago)` \n - If no activity data, set to `null`. Do NOT make up activity.\n\n6. **Null handling** \n - Any missing or empty field **must** be literal `null` (not empty string).\n\n7. **Output style** \n - Pure JSON, no markdown. \n - No additional keys, comments, or nested objects.\n\n## Grammar and Punctuation\n - ensure that your output is cleanly formatted for readiness to import into CRM, including removing uneceesary spaces or other symbols and capitalizing names. (e.g., \"sales director\" should become \"Sales Director\")\n\nReturn only that final JSON. Example output:\n{\n \"email\": \"dustin.c@gatekeeperhq.com\",\n \"linkedin_url\": \"https://www.linkedin.com/in/dustinclinard\",\n \"job_title\": \"Chief Revenue Officer (CRO)\",\n \"city\": \"Concord\",\n \"country_region\": \"United States\",\n \"experience_summary\": \"• Chief Revenue Officer, Gatekeeper — 2024 → Present\\n• Founding Member, Revenue Collective — 2019 → Present\\n• Member, Partnership Leaders — 2020 → Present\\n• Founder & Growth Consultant, Sales Growth Musings — 2016 → Present\",\n \"education_summary\": null,\n \"recent_linkedin_activity\": null\n}"
}
]
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.6
},
{
"id": "f3d84acb-fe43-4d14-ab74-97a0e5a336a7",
"name": "스티키 노트",
"type": "n8n-nodes-base.stickyNote",
"position": [
48,
592
],
"parameters": {
"color": 5,
"width": 260,
"height": 400,
"content": "## Enrich with Apollo"
},
"typeVersion": 1
},
{
"id": "8f9f9c6c-e9b9-4502-97a2-b4bf3c5a396c",
"name": "스티키 노트2",
"type": "n8n-nodes-base.stickyNote",
"position": [
2448,
608
],
"parameters": {
"color": 4,
"width": 540,
"height": 620,
"content": "## Summarize enrichment data\nEnsure it's clean and matches our CRM needs"
},
"typeVersion": 1
},
{
"id": "9cc13aca-f660-470f-addb-f17f51f725e7",
"name": "스티키 노트3",
"type": "n8n-nodes-base.stickyNote",
"position": [
3104,
608
],
"parameters": {
"color": 5,
"width": 260,
"height": 400,
"content": "## Enrich HubSpot"
},
"typeVersion": 1
},
{
"id": "6c4e7437-9a58-4aad-956c-268bb23920e8",
"name": "병합",
"type": "n8n-nodes-base.merge",
"position": [
2048,
752
],
"parameters": {
"mode": "combine",
"options": {
"includeUnpaired": true
},
"combineBy": "combineByPosition"
},
"typeVersion": 3.1
},
{
"id": "5f3436aa-94d0-46f9-83fd-e60726b8821c",
"name": "OpenAI 채팅 모델6",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
2512,
912
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "o3",
"cachedResultName": "o3"
},
"options": {
"responseFormat": "json_object"
}
},
"credentials": {
"openAiApi": {
"id": "HH848Gw8QSS5TUKW",
"name": "OpenAi"
}
},
"typeVersion": 1.2
},
{
"id": "624d158e-08bc-42df-add7-9462b39cb8de",
"name": "최근 게시물 가져오기",
"type": "n8n-nodes-base.httpRequest",
"position": [
832,
912
],
"parameters": {
"url": "https://fresh-linkedin-profile-data.p.rapidapi.com/get-profile-posts",
"options": {},
"sendQuery": true,
"sendHeaders": true,
"queryParameters": {
"parameters": [
{
"name": "linkedin_url",
"value": "={{ $json.person.linkedin_url }}"
},
{
"name": "type",
"value": "posts"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "x-rapidapi-host",
"value": "fresh-linkedin-profile-data.p.rapidapi.com"
},
{
"name": "x-rapidapi-key",
"value": "<YOUR API KEY>"
}
]
}
},
"retryOnFail": true,
"typeVersion": 4.2,
"alwaysOutputData": true
},
{
"id": "45dfddb1-ad00-419b-8309-e91de878989d",
"name": "분할",
"type": "n8n-nodes-base.splitOut",
"position": [
1040,
912
],
"parameters": {
"options": {},
"fieldToSplitOut": "data"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "6b392b08-3dff-4201-ba66-a979ac7d301a",
"name": "리공유 및 오래된 게시물 필터링",
"type": "n8n-nodes-base.filter",
"position": [
1264,
912
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "44e79a7e-7ec9-4724-a53b-3e647b6a629a",
"operator": {
"type": "boolean",
"operation": "false",
"singleValue": true
},
"leftValue": "={{ $json.reshared }}",
"rightValue": ""
},
{
"id": "8da29df1-cbfb-42cd-a85f-62b2b4647802",
"operator": {
"type": "dateTime",
"operation": "afterOrEquals"
},
"leftValue": "={{ $json.posted }}",
"rightValue": "={{$now.minus({ days: 30 }).toISO()}}"
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2,
"alwaysOutputData": true
},
{
"id": "466bbf0f-54e8-4c2c-9637-f70925329b72",
"name": "3개로 제한",
"type": "n8n-nodes-base.limit",
"position": [
1680,
912
],
"parameters": {
"maxItems": 3
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "fa0bd77e-310e-4a64-83c9-c4f3b0fddb7a",
"name": "게시일 기준 정렬",
"type": "n8n-nodes-base.sort",
"position": [
1488,
912
],
"parameters": {
"options": {},
"sortFieldsUi": {
"sortField": [
{
"order": "descending",
"fieldName": "posted"
}
]
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "b45d1bb7-5a3f-43f6-ae9c-7a912e3b1114",
"name": "집계",
"type": "n8n-nodes-base.aggregate",
"position": [
1904,
912
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "c0e75ad6-08db-4bda-9c69-4067adcc4951",
"name": "항목 순환",
"type": "n8n-nodes-base.splitInBatches",
"position": [
624,
784
],
"parameters": {
"options": {}
},
"typeVersion": 3,
"alwaysOutputData": false
},
{
"id": "69bd14dd-f6d8-4220-ba6b-dd17d2d1ea8b",
"name": "필드 추출",
"type": "n8n-nodes-base.set",
"position": [
2272,
752
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "19c926c1-da4e-44e2-abce-6d7d172cb0bb",
"name": "person_data",
"type": "string",
"value": "={{ $json.person }}"
},
{
"id": "62615717-7bc7-44c4-9304-7177dfcf3ee8",
"name": "recent_activity",
"type": "string",
"value": "={{ $json.data }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "5b9ce241-42a6-468a-be87-2462248836af",
"name": "스티키 노트5",
"type": "n8n-nodes-base.stickyNote",
"position": [
768,
848
],
"parameters": {
"color": 5,
"width": 1260,
"height": 220,
"content": "## Grab Recent LinkedIn Posts"
},
"typeVersion": 1
},
{
"id": "f76caacf-bf40-4aa7-b48c-60ebf9c772a8",
"name": "정리",
"type": "n8n-nodes-base.code",
"position": [
-128,
752
],
"parameters": {
"jsCode": "/**********************************************************************\n * Deduplicate contacts by email & drop empties\n * Input: items[] (each item = { json: { … } })\n * Output: one item per unique, non-empty email\n **********************************************************************/\nconst normEmail = e => (typeof e === 'string' ? e.trim().toLowerCase() : '');\n\nconst seen = new Set();\nconst clean = [];\n\nfor (const itm of items) {\n // Handle both flat and nested structures\n const data = itm.json.output ?? itm.json; // supports {output:{…}} too\n const email = normEmail(data.email);\n\n if (!email || seen.has(email)) continue; // skip blanks & dupes\n\n seen.add(email);\n clean.push({\n json: {\n name: data.name ?? null,\n email // already normalised\n }\n });\n}\n\nreturn clean;"
},
"typeVersion": 2
},
{
"id": "e95c04cb-b9e3-433d-b510-77e1b9b7abf2",
"name": "스티키 노트1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1632,
848
],
"parameters": {
"height": 208,
"content": "Decide how many posts you want to analyse"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {
"When Executed by Another Workflow": [
{
"json": {
"name": "People of intereset 1",
"email": "test@companymail.com"
}
},
{
"json": {
"name": "People of intereset 2",
"email": "test2@companymail.com"
}
}
]
},
"settings": {
"executionOrder": "v1"
},
"versionId": "ad6478e5-597d-450d-ab64-d506159731f2",
"connections": {
"6c4e7437-9a58-4aad-956c-268bb23920e8": {
"main": [
[
{
"node": "69bd14dd-f6d8-4220-ba6b-dd17d2d1ea8b",
"type": "main",
"index": 0
}
]
]
},
"f76caacf-bf40-4aa7-b48c-60ebf9c772a8": {
"main": [
[
{
"node": "747be8f0-cf2b-412d-b7a9-93051ff0a11b",
"type": "main",
"index": 0
}
]
]
},
"3630169c-2677-4124-a19b-f9d1a2bfdcce": {
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[
{
"node": "6c4e7437-9a58-4aad-956c-268bb23920e8",
"type": "main",
"index": 0
},
{
"node": "c0e75ad6-08db-4bda-9c69-4067adcc4951",
"type": "main",
"index": 0
}
],
[]
]
},
"b45d1bb7-5a3f-43f6-ae9c-7a912e3b1114": {
"main": [
[
{
"node": "c0e75ad6-08db-4bda-9c69-4067adcc4951",
"type": "main",
"index": 0
}
]
]
},
"45dfddb1-ad00-419b-8309-e91de878989d": {
"main": [
[
{
"node": "6b392b08-3dff-4201-ba66-a979ac7d301a",
"type": "main",
"index": 0
}
]
]
},
"466bbf0f-54e8-4c2c-9637-f70925329b72": {
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[
{
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"type": "main",
"index": 0
}
]
]
},
"69bd14dd-f6d8-4220-ba6b-dd17d2d1ea8b": {
"main": [
[
{
"node": "3aa928c0-6f12-4f5c-9acb-018b0b87667e",
"type": "main",
"index": 0
}
]
]
},
"c0e75ad6-08db-4bda-9c69-4067adcc4951": {
"main": [
[
{
"node": "6c4e7437-9a58-4aad-956c-268bb23920e8",
"type": "main",
"index": 1
}
],
[
{
"node": "624d158e-08bc-42df-add7-9462b39cb8de",
"type": "main",
"index": 0
}
]
]
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"624d158e-08bc-42df-add7-9462b39cb8de": {
"main": [
[
{
"node": "45dfddb1-ad00-419b-8309-e91de878989d",
"type": "main",
"index": 0
}
]
]
},
"fa0bd77e-310e-4a64-83c9-c4f3b0fddb7a": {
"main": [
[
{
"node": "466bbf0f-54e8-4c2c-9637-f70925329b72",
"type": "main",
"index": 0
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]
]
},
"00a26c55-aa97-4255-b002-cb77bc1a8780": {
"main": [
[]
]
},
"747be8f0-cf2b-412d-b7a9-93051ff0a11b": {
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[
{
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"index": 0
}
]
]
},
"06391ddf-2071-4b80-86ad-85c922ae33c8": {
"ai_languageModel": [
[
{
"node": "01dd3096-dcb3-4e0d-97ac-581a7d08b55f",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"5f3436aa-94d0-46f9-83fd-e60726b8821c": {
"ai_languageModel": [
[
{
"node": "3aa928c0-6f12-4f5c-9acb-018b0b87667e",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"3aa928c0-6f12-4f5c-9acb-018b0b87667e": {
"main": [
[
{
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"type": "main",
"index": 0
}
]
]
},
"b819ac28-783c-49d5-8125-fb824fd30661": {
"ai_outputParser": [
[
{
"node": "01dd3096-dcb3-4e0d-97ac-581a7d08b55f",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"01dd3096-dcb3-4e0d-97ac-581a7d08b55f": {
"ai_outputParser": [
[
{
"node": "3aa928c0-6f12-4f5c-9acb-018b0b87667e",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"6b392b08-3dff-4201-ba66-a979ac7d301a": {
"main": [
[
{
"node": "fa0bd77e-310e-4a64-83c9-c4f3b0fddb7a",
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"index": 0
}
]
]
},
"dbf704c3-2b0e-4158-b5d8-ca1d138d141a": {
"main": [
[
{
"node": "f76caacf-bf40-4aa7-b48c-60ebf9c772a8",
"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?
고급 - 리드 생성, AI 요약
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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