Intuz This workflow corresponds to n8n.io template #8012 — we link there as the canonical source.
This workflow follows the Apifyn8N Nodes Apify → Google Sheets recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "xkdknceWGy7eT6B0",
"name": "Live-Automate LinkedIn Profile Research & AI Outreach with Apify, Gemini & Sheets",
"tags": [],
"nodes": [
{
"id": "ecbfc577-7f4d-448c-8c70-4c6a80ba7629",
"name": "Get row(s) in sheet",
"type": "n8n-nodes-base.googleSheets",
"position": [
-1792,
336
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1023079571,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
"cachedResultName": "Sheet10"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit?usp=drivesdk",
"cachedResultName": "MLOps CXOs Bay Area"
}
},
"typeVersion": 4.7
},
{
"id": "efe97c07-f2d4-4f90-9f21-a503ebbd4103",
"name": "Limit",
"type": "n8n-nodes-base.limit",
"position": [
-1360,
320
],
"parameters": {},
"typeVersion": 1
},
{
"id": "4f2e62e8-7e5e-434b-80f7-c2197ad1950c",
"name": "Get dataset items",
"type": "@apify/n8n-nodes-apify.apify",
"position": [
-944,
320
],
"parameters": {
"offset": {},
"resource": "Datasets",
"datasetId": "={{ $json.defaultDatasetId }}"
},
"typeVersion": 1
},
{
"id": "b8bdd09a-1e75-4a13-9fee-75ffc305fa67",
"name": "Append or update row in sheet",
"type": "n8n-nodes-base.googleSheets",
"position": [
-672,
320
],
"parameters": {
"columns": {
"value": {
"LinkedIn": "={{ $('Limit').item.json.LinkedIn }}",
"Profile Data": "=About : {{ $json.basic_info.about }}\n\n{{ $json.experience.map((exp, i) => \n \"Experience \" + (i+1) + \"\\n\" +\n \"Title: \" + exp.title + \"\\n\" +\n \"Company: \" + exp.company + \"\\n\" +\n \"Location: \" + exp.location + \"\\n\" +\n \"Description: \" + exp.description\n).join(\"\\n\\n\") }}\n\n"
},
"schema": [
{
"id": "First Name",
"type": "string",
"display": true,
"required": false,
"displayName": "First Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Last Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Last Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Job Title",
"type": "string",
"display": true,
"required": false,
"displayName": "Job Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Location",
"type": "string",
"display": true,
"required": false,
"displayName": "Location",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LinkedIn",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "LinkedIn",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Company Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Company Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Profile Data",
"type": "string",
"display": true,
"required": false,
"displayName": "Profile Data",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Subject",
"type": "string",
"display": true,
"required": false,
"displayName": "Subject",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Email Body",
"type": "string",
"display": true,
"required": false,
"displayName": "Email Body",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"LinkedIn"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1023079571,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
"cachedResultName": "Sheet10"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit?usp=drivesdk",
"cachedResultName": "MLOps CXOs Bay Area"
}
},
"typeVersion": 4.7
},
{
"id": "0d58b6ca-bd4d-442b-958a-6e54c8fcb9b0",
"name": "Get row(s) in sheet1",
"type": "n8n-nodes-base.googleSheets",
"position": [
-400,
320
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1023079571,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
"cachedResultName": "Sheet10"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit?usp=drivesdk",
"cachedResultName": "MLOps CXOs Bay Area"
}
},
"typeVersion": 4.7
},
{
"id": "0ca835dc-bc3f-49bf-85d8-08a8d41d3502",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
240,
512
],
"parameters": {
"jsonSchemaExample": "{\n \"subject\": \"A short, catchy, question-based subject line\",\n \"email_body\": \"The full email body, 100-120 words, without any salutation or sign-off.\"\n}"
},
"typeVersion": 1.3
},
{
"id": "d1412a37-4f94-4efa-aac8-ba7f129b2bb7",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
64,
512
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "6e9c4aac-17fc-4b21-a832-038b6571a52e",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-2000,
336
],
"parameters": {
"rule": {
"interval": [
{
"field": "minutes",
"minutesInterval": 2
}
]
}
},
"typeVersion": 1.2
},
{
"id": "27f7cb9e-f89a-4496-b2ff-0cd8fb0cf6af",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2048,
80
],
"parameters": {
"color": 2,
"width": 384,
"height": 416,
"content": "## \u23f0 Schedule Trigger & \ud83d\udcc4 Google Sheets (Input)\nThis part of the workflow runs every 2 minutes. \nIt fetches new rows (LinkedIn URLs and lead data) from the CRM sheet. \nOnly leads without Profile Data or Email drafts move forward.\n"
},
"typeVersion": 1
},
{
"id": "20b443fd-25df-4397-b167-cfa1ae1616fc",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1616,
80
],
"parameters": {
"color": 6,
"width": 384,
"height": 416,
"content": "## \ud83d\udd0d If Check & \u2696\ufe0f Limit\n1. The **If node** ensures only leads missing Profile Data and Subject are processed. \n\n2. The **Limit node** controls batch size to prevent Apify overload or LinkedIn blocks. \n\nKeeps the workflow safe & efficient.\n"
},
"typeVersion": 1
},
{
"id": "fd519317-971a-4cbf-a891-dcb61965c30f",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1200,
80
],
"parameters": {
"color": 4,
"width": 384,
"height": 416,
"content": "## \ud83e\udd16 Apify Actor & \ud83d\udcc2 Dataset\n1. Runs the **LinkedIn Profile Scraper** actor on Apify for each LinkedIn URL. \n\n2. The Dataset node fetches structured results (About, Experience, Roles, Companies). \n\nThis enriches leads with detailed career data.\n"
},
"typeVersion": 1
},
{
"id": "5b2af68b-9acb-4021-9211-ea9f947cffbf",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-768,
64
],
"parameters": {
"color": 5,
"width": 288,
"height": 432,
"content": "## \ud83d\udcbe Google Sheets (Profile Data)\nAppends enriched profile details into the \"Profile Data\" column in Google Sheets. \nNow each lead row includes About + Experience insights, ready for email personalisation.\n\n"
},
"typeVersion": 1
},
{
"id": "5fbf3fc9-7a32-46b3-92a1-95758b9a1337",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-432,
80
],
"parameters": {
"color": 3,
"width": 368,
"height": 384,
"content": "## \ud83d\udcc4 Get Rows Again & \ud83d\udd0d If Check (Email)\n1. Pulls updated rows after scraping. \n\n2. Checks if Profile Data exists but \nSubject + Email Body are still empty. \n\nEnsures only complete profiles go into email generation.\n"
},
"typeVersion": 1
},
{
"id": "6b63c91d-a436-4c1d-8d1c-3e5b3f84194e",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
0
],
"parameters": {
"width": 368,
"height": 464,
"content": "## \ud83e\udde0 LLM Chain (Gemini via LangChain)\n1. Gemini is instructed to act as an expert B2B cold email copywriter. \n\n2. It generates personalised subject lines & email bodies using career insights, achievements, and context. \n\n3. Parser ensures Gemini\u2019s response is valid JSON with \"subject\" + \"email_body\".\n\nResult: high-relevance outreach emails.\n \n"
},
"typeVersion": 1
},
{
"id": "36ffcba7-23b8-45fc-b7dd-612f8537c293",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
416,
80
],
"parameters": {
"color": 5,
"width": 320,
"height": 384,
"content": "## \ud83d\udcbe Google Sheets (Final Email)\nFinal email drafts are stored in Google Sheets alongside LinkedIn URL & Profile Data. \nEach lead row is now fully ready for outreach \ud83d\ude80.\n"
},
"typeVersion": 1
},
{
"id": "6bcd2902-cf7c-4235-ad92-d8ea28392af4",
"name": "Check Profiles with no Data",
"type": "n8n-nodes-base.if",
"position": [
-1568,
336
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b8ddddfc-54ae-4815-aea8-edc05959cc11",
"operator": {
"type": "string",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json[\"Profile Data\"] }}",
"rightValue": ""
},
{
"id": "5b0584d8-cfe8-4758-b097-cb0ecd87f5e4",
"operator": {
"type": "string",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json.Subject }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "77f3dbf8-9218-44cf-a03f-feacfa4a1906",
"name": "Runs Profile Extraction Actor",
"type": "@apify/n8n-nodes-apify.apify",
"position": [
-1152,
320
],
"parameters": {
"actorId": {
"__rl": true,
"mode": "list",
"value": "VhxlqQXRwhW8H5hNV",
"cachedResultUrl": "https://console.apify.com/actors/VhxlqQXRwhW8H5hNV/input",
"cachedResultName": "Linkedin Profile Details Scraper + EMAIL (No Cookies Required) (apimaestro/linkedin-profile-detail)"
},
"timeout": {},
"customBody": "={\n \"includeEmail\": false,\n \"username\": \"{{ $json.LinkedIn }}\"\n}"
},
"typeVersion": 1
},
{
"id": "02725c27-8264-4b8d-a725-18947a0c8b6b",
"name": "Check Profiles with No Email Drafts",
"type": "n8n-nodes-base.if",
"position": [
-208,
320
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "dcf02764-abdc-4eca-8022-b0c585301927",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json[\"Profile Data\"] }}",
"rightValue": ""
},
{
"id": "87fc4d1b-97e7-4fcd-af85-f1414d476b67",
"operator": {
"type": "string",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json.Subject }}",
"rightValue": ""
},
{
"id": "4a7ddabd-14bd-429f-97e3-513abf6c62f8",
"operator": {
"type": "string",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json[\"Email Body\"] }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "f81e7880-4ae7-4f32-864a-05bb176a9e58",
"name": "Hyper Personalised Email Generator",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
80,
304
],
"parameters": {
"text": "=**Act as an expert B2B cold email copywriter.** Your specialty is writing highly personalized, concise, and compelling emails that get replies from busy executives. Your style is peer-to-peer, respectful, and avoids generic sales jargon.\n\n\n\n**Your Goal:** Generate 1 distinct email draft to a prospect based on their professional profile. Each email must feel like I have personally researched them and understood their career journey.\n\n\n\n**My Context:**\n\n\n* **My Company/Service:** We offer MLOps solutions that help companies significantly reduce their cloud costs for AI and machine learning workloads without sacrificing performance.\n\n\n* **My Core Value Proposition:** We help tech leaders ship AI features faster and more profitably by optimizing their infrastructure.\n\n\n* **My Call to Action (CTA):** An offer for a complimentary, no-obligation audit of their current ML infrastructure to identify immediate cost-saving opportunities.\n\n\n\n**Prospect's Profile:**\n\n\nFULL PROFILE DETAILS HERE \nFirst Name: {{ $json['First Name'] }}\nLast Name: {{ $json['Last Name'] }}\nJob Title: {{ $json['Job Title'] }}\nCompany Name: {{ $json['Company Name'] }}\nProfile Data: {{ $json['Profile Data'] }}\n\n**Instructions for Crafting the Emails:**\n\n\n\n1. **Scrutinize the Profile:** Read the entire profile provided. Do not just look at the current job title. Instead, identify the most unique and compelling \"nuggets\" of information. Look for:\n\n\n * **Unusual Career Paths:** (e.g., from SysAdmin to VP of Product, or Trader to COO).\n\n\n * **Long Tenure / Promotions:** (e.g., spending 9+ years at one company and rising through the ranks).\n\n\n * **Specific, Quantifiable Achievements:** (e.g., \"scaled to 4M members\").\n\n\n * **\"Boomerang\" Employment:** (e.g., leaving a company and returning later in a more senior role).\n\n\n * **Consistent Themes:** (e.g., a career-long focus on \"health and wealth outcomes\").\n\n\n * **Past Roles at well-known companies** that are relevant to their current role.\n\n\n\n2. **Create a \"Hook\" from a Nugget:** Start each email with a genuine, specific observation based on one of these nuggets. This is the most critical step.\n\n\n * **Good Example:** \"Your 9-year journey at Wanderu, from Director to leading both Product & Technology, is incredibly impressive.\"\n\n\n * **Bad Example:** \"I saw on your LinkedIn profile that you are the VP at Wanderu.\"\n\n\n\n3. **Build a \"Bridge\":** Immediately connect your observation (the Hook) to a relevant business problem that the prospect likely faces in their *current* role. The problem should be tailored to their title:\n\n\n * **For a CTO/VP Engineering:** Frame the problem around infrastructure complexity, scalability, and technical debt.\n\n\n * **For a COO/GM:** Frame the problem around operational efficiency, P&L, gross margins, and profitability (COGS).\n\n\n * **For a VP Product:** Frame the problem around speed-to-market, feature ROI, and the budget for new initiatives.\n\n\n\n4. **Introduce the Solution:** Seamlessly introduce my service (MLOps for cost reduction) as the direct solution to the problem you just framed. Use my Core Value Proposition here.\n\n\n\n5. **Deliver the Call to Action:** End with the specific, low-friction CTA I provided.\n\n\n\n**Final Output Requirements:**\n\n\n* Provide 1 distinct drafts, each using a different \"nugget\" or angle for the hook.\n\n\n* Keep each email under 150 words.\n\n\n* Use a confident, peer-level tone. Avoid overly formal or submissive language.\n\n\n* Create a compelling, short subject line for each draft.\n\nCritical Information:\n- The output should be divided into \nsubject: \"Subject line\"\nBody: \"Content for email\"\n- Each mail should be different to other one.",
"batching": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.7
},
{
"id": "556499f4-f086-45bf-aad7-90e78c4dfc5b",
"name": "Final Output",
"type": "n8n-nodes-base.googleSheets",
"position": [
512,
304
],
"parameters": {
"columns": {
"value": {
"Subject": "={{ $json.output.subject }}",
"LinkedIn": "={{ $('Check Profiles with No Email Drafts').item.json.LinkedIn }}",
"Email Body": "={{ $json.output.email_body }}"
},
"schema": [
{
"id": "First Name",
"type": "string",
"display": true,
"required": false,
"displayName": "First Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Last Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Last Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Job Title",
"type": "string",
"display": true,
"required": false,
"displayName": "Job Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Location",
"type": "string",
"display": true,
"required": false,
"displayName": "Location",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LinkedIn",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "LinkedIn",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Company Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Company Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Profile Data",
"type": "string",
"display": true,
"required": false,
"displayName": "Profile Data",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Subject",
"type": "string",
"display": true,
"required": false,
"displayName": "Subject",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Email Body",
"type": "string",
"display": true,
"required": false,
"displayName": "Email Body",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"LinkedIn"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1023079571,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit#gid=1023079571",
"cachedResultName": "Sheet10"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1nIGlVREvoz7iyCsOmCgqRXgKFFQZIVckV6a1KnDGpjM/edit?usp=drivesdk",
"cachedResultName": "MLOps CXOs Bay Area"
}
},
"typeVersion": 4.7
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "2d96068c-2cd4-48c7-adb3-f5139666adc1",
"connections": {
"Limit": {
"main": [
[
{
"node": "Runs Profile Extraction Actor",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Get row(s) in sheet",
"type": "main",
"index": 0
}
]
]
},
"Get dataset items": {
"main": [
[
{
"node": "Append or update row in sheet",
"type": "main",
"index": 0
}
]
]
},
"Get row(s) in sheet": {
"main": [
[
{
"node": "Check Profiles with no Data",
"type": "main",
"index": 0
}
]
]
},
"Get row(s) in sheet1": {
"main": [
[
{
"node": "Check Profiles with No Email Drafts",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Hyper Personalised Email Generator",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Hyper Personalised Email Generator",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Check Profiles with no Data": {
"main": [
[
{
"node": "Limit",
"type": "main",
"index": 0
}
]
]
},
"Append or update row in sheet": {
"main": [
[
{
"node": "Get row(s) in sheet1",
"type": "main",
"index": 0
}
]
]
},
"Runs Profile Extraction Actor": {
"main": [
[
{
"node": "Get dataset items",
"type": "main",
"index": 0
}
]
]
},
"Hyper Personalised Email Generator": {
"main": [
[
{
"node": "Final Output",
"type": "main",
"index": 0
}
]
]
},
"Check Profiles with No Email Drafts": {
"main": [
[
{
"node": "Hyper Personalised Email Generator",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
It transforms a basic list of LinkedIn profiles into a campaign-ready database by first enriching contacts with detailed career data and then using AI to craft unique, context-aware emails based on each individual's professional journey. Sales Development Representatives (SDRs)…
Source: https://n8n.io/workflows/8012/ — original creator credit. Request a take-down →
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