{ "meta": { "templateCredsSetupCompleted": true }, "nodes": [ { "id": "02b63fb0-168a-47a5-abf3-aaf883760221", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -720, 144 ], "parameters": { "color": 5, "width": 500, "height": 1160, "content": "## Lookalike Company Enrichment & Lead Scoring\n\n### How it works\n1. You trigger the workflow manually and it reads your best customer domains from a Google Sheet.\n2. For each customer domain, PredictLeads finds lookalike companies with similar profiles.\n3. Each lookalike is enriched with real-time signals: recent news events, job openings, and technology stack.\n4. A growth detection step analyzes news events to flag high-growth companies based on positive signals like launches, partnerships, and new hires.\n5. All signals are combined into a composite score (0-100) weighing news recency, hiring volume, tech stack overlap, similarity, and region.\n6. High-scoring leads (above 70) trigger a Slack alert, get saved to Google Sheets, and receive an AI-generated outreach email via Gmail.\n\n### Setup\n1. Connect your **Google Sheets** credential and point the input node to a sheet with a `domain` column listing your best client domains.\n2. Connect your **PredictLeads API** credential (get one at [predictleads.com](https://predictleads.com)).\n3. Connect your **Slack** credential and select the alert channel for growth and high-score notifications.\n4. Connect your **Gmail** credential for automated outreach emails.\n5. Set the `OPENAI_API_KEY` environment variable for AI-generated email copy.\n6. Create a second sheet tab named \"Scored Lookalikes\" for output.\n\n### Customization\n- Adjust the score threshold in the Filter node (default is 70).\n- Edit target technologies in the scoring Code node (default: HubSpot, Salesforce, Marketo).\n- Modify growth signal categories in the Detect Growth Signals node.\n- Change target regions for the regional scoring bonus." }, "typeVersion": 1 }, { "id": "20a41666-7378-4985-93c6-3d7dbac98d1a", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 80, 480 ], "parameters": { "width": 492, "height": 312, "content": "## Trigger & Input\nManually starts the workflow and loads your best customer domains from Google Sheets." }, "typeVersion": 1 }, { "id": "0369b151-0582-4b45-99ef-e431483713f1", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 592, 512 ], "parameters": { "width": 732, "height": 296, "content": "## Lookalike Discovery\nLoops through each client domain, queries PredictLeads for similar companies, and extracts structured lookalike data." }, "typeVersion": 1 }, { "id": "f5f99be7-a521-46a2-9890-8d80d3f1beab", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 1376, 288 ], "parameters": { "width": 1244, "height": 536, "content": "## Signal Enrichment & Growth Detection\nEnriches each lookalike with news, jobs, and tech data. Detects growth patterns and sends Slack alerts for high-growth companies." }, "typeVersion": 1 }, { "id": "7e2841f4-82d4-4fb4-80b2-6c77cfd33b17", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ 2768, 528 ], "parameters": { "width": 524, "height": 296, "content": "## Lead Scoring\nCombines news, hiring, tech, similarity, and region signals into a composite score (0-100) and filters high-scoring leads." }, "typeVersion": 1 }, { "id": "f1f50fdb-7377-4fff-8614-5baef541b9f7", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 3472, 256 ], "parameters": { "width": 732, "height": 792, "content": "## Alerts, Outreach & Storage\nSends Slack alerts for top leads, saves scored results to Google Sheets, and generates AI-powered outreach emails via Gmail." }, "typeVersion": 1 }, { "id": "51a6d6d6-1ce7-4013-99af-b60dd61709e4", "name": "When clicking 'Execute workflow'", "type": "n8n-nodes-base.manualTrigger", "position": [ 144, 640 ], "parameters": {}, "typeVersion": 1 }, { "id": "d0bb1298-c7a2-47ca-bcad-0626dd8a574c", "name": "Read Best Client Domains", "type": "n8n-nodes-base.googleSheets", "position": [ 336, 640 ], "parameters": { "options": {}, "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1KDGtZcPjGlSN5OuSG5TxtTIE1BPLIDIAyTs-yIjExTo/edit#gid=0", "cachedResultName": "Sheet1" }, "documentId": { "__rl": true, "mode": "list", "value": "1KDGtZcPjGlSN5OuSG5TxtTIE1BPLIDIAyTs-yIjExTo", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1KDGtZcPjGlSN5OuSG5TxtTIE1BPLIDIAyTs-yIjExTo/edit?usp=drivesdk", "cachedResultName": "09" } }, "typeVersion": 4.5 }, { "id": "d477b025-b330-4517-861b-68b5c4650ac9", "name": "Loop Clients", "type": "n8n-nodes-base.splitInBatches", "position": [ 656, 640 ], "parameters": { "options": {} }, "typeVersion": 3 }, { "id": "03ba160d-2fd0-4273-8aaf-86521010a07e", "name": "Retrieve Company", "type": "@predictleads/n8n-nodes-predictleads.predictLeads", "position": [ 880, 656 ], "parameters": { "domain": "={{ $json.domain }}", "operation": "retrieveCompany", "requestOptions": {} }, "credentials": {}, "typeVersion": 1 }, { "id": "3efadf54-da4f-4b67-a0b3-fb53281135b8", "name": "Extract Lookalikes", "type": "n8n-nodes-base.code", "position": [ 1088, 656 ], "parameters": { "jsCode": "const items = $input.all();\nconst results = [];\n\nfor (const item of items) {\n\n const mainData = item.json.data?.[0] || {};\n const included = item.json.included || [];\n\n // get lookalike company IDs\n const lookalikeIds = mainData.relationships?.lookalike_companies?.data || [];\n\n for (const rel of lookalikeIds) {\n\n // match ID with included array\n const match = included.find(c => c.id === rel.id);\n\n if (!match) continue;\n\n const domain = match.attributes?.domain || '';\n\n // skip invalid / empty domains\n if (!domain) continue;\n\n results.push({\n json: {\n domain: domain,\n company_name: match.attributes?.company_name || '',\n source_domain: mainData.attributes?.domain || '',\n similarity_score: 0.9, \n }\n });\n }\n}\n\nreturn results;" }, "typeVersion": 2 }, { "id": "6ea58fa3-7bb2-4c8d-a04b-830df40b5796", "name": "Loop Lookalikes", "type": "n8n-nodes-base.splitInBatches", "position": [ 1440, 656 ], "parameters": { "options": {} }, "typeVersion": 3 }, { "id": "62508496-cb11-43fd-b0b6-1b4e35dc34d6", "name": "Retrieve Company News Events", "type": "@predictleads/n8n-nodes-predictleads.predictLeads", "position": [ 1648, 672 ], "parameters": { "domain": "={{ $json.domain }}", "resource": "newsEvents", "operation": "retrieveCompanyNewsEvents", "requestOptions": {} }, "credentials": {}, "typeVersion": 1 }, { "id": "6edc2b02-d228-437e-a0fb-48aef4129ba3", "name": "Retrieve Company Job Openings", "type": "@predictleads/n8n-nodes-predictleads.predictLeads", "position": [ 1904, 672 ], "parameters": { "domain": "={{ $('Extract Lookalikes').item.json.domain }}", "resource": "jobOpenings", "operation": "retrieveCompanyJobOpenings", "requestOptions": {} }, "credentials": {}, "typeVersion": 1 }, { "id": "9c9843cc-24e3-46e2-b12d-9c967b63c598", "name": "Retrieve Technologies", "type": "@predictleads/n8n-nodes-predictleads.predictLeads", "position": [ 2128, 672 ], "parameters": { "domain": "={{ $('Extract Lookalikes').item.json.domain }}", "resource": "technologyDetections", "operation": "retrieveTechnologiesUsedByCompany", "requestOptions": {} }, "credentials": {}, "typeVersion": 1 }, { "id": "dc8db35b-9fce-4163-95a2-0758ca7b20b7", "name": "Detect Growth Signals", "type": "n8n-nodes-base.code", "position": [ 1904, 432 ], "parameters": { "jsCode": "const items = $input.all();\nconst results = [];\n\nconst now = new Date();\nconst thirtyDaysAgo = new Date(now - 30 * 24 * 60 * 60 * 1000);\n\n// Growth categories (IMPORTANT)\nconst positiveSignals = [\n 'launches',\n 'partners_with',\n 'integrates_with',\n 'acquires',\n 'hires',\n 'invests_into',\n 'signs_new_client'\n];\n\nconst negativeSignals = [\n 'has_issues_with',\n 'files_suit_against'\n];\n\nfor (const item of items) {\n\n const data = item.json.data || [];\n\n let growthSignals = [];\n let negativeEvents = [];\n let recentSignals = [];\n\n for (const event of data) {\n const attr = event.attributes || {};\n const category = attr.category || '';\n const date = attr.found_at ? new Date(attr.found_at) : null;\n\n // Recent filter (last 30 days)\n const isRecent = date && date > thirtyDaysAgo;\n\n // Positive signals\n if (positiveSignals.includes(category)) {\n growthSignals.push({\n category,\n summary: attr.summary || '',\n date: attr.found_at\n });\n\n if (isRecent) {\n recentSignals.push(category);\n }\n }\n\n // Negative signals\n if (negativeSignals.includes(category)) {\n negativeEvents.push({\n category,\n summary: attr.summary || ''\n });\n }\n }\n\n // Score logic\n let growth_score = 0;\n\n growth_score += recentSignals.length * 2; // recent signals strong\n growth_score += growthSignals.length; // total signals\n\n if (negativeEvents.length > 0) {\n growth_score -= negativeEvents.length * 2; // penalize\n }\n\n results.push({\n json: {\n growth_signal_count: growthSignals.length,\n recent_signal_count: recentSignals.length,\n negative_signal_count: negativeEvents.length,\n\n growth_signal_categories: [...new Set(growthSignals.map(s => s.category))],\n\n growth_signal_summary: growthSignals\n .slice(0, 3)\n .map(s => s.summary)\n .join(' | '),\n\n growth_score: growth_score,\n\n is_high_growth: growth_score >= 5,\n\n analyzed_at: now.toISOString()\n }\n });\n}\n\nreturn results;" }, "typeVersion": 2 }, { "id": "c3ef931d-6b50-4c4a-b001-5f0118d2102e", "name": "High Growth Detected?", "type": "n8n-nodes-base.if", "position": [ 2128, 432 ], "parameters": { "options": {}, "conditions": { "options": { "version": 3, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "031153cf-5b56-459a-a72e-23f48a8bf5c7", "operator": { "type": "boolean", "operation": "equals" }, "leftValue": "={{ $json.is_high_growth }}", "rightValue": true } ] } }, "typeVersion": 2.3 }, { "id": "aaab9380-ac2e-4ff2-86b5-7b0e34630e13", "name": "Send Growth Alert", "type": "n8n-nodes-base.slack", "position": [ 2384, 416 ], "parameters": { "text": "=...", "select": "channel", "channelId": { "__rl": true, "mode": "list", "value": "C0AEEATQQEP", "cachedResultName": "buddieslab-umer" }, "otherOptions": {}, "authentication": "oAuth2" }, "typeVersion": 2.4 }, { "id": "c18397f1-3dad-45ca-bfdb-03ed568e543a", "name": "Calculate Composite Score", "type": "n8n-nodes-base.code", "position": [ 2832, 672 ], "parameters": { "jsCode": "const items = $input.all();\nconst results = [];\n\nfor (const item of items) {\n\n const now = new Date();\n const thirtyDaysAgo = new Date(now - 30 * 24 * 60 * 60 * 1000);\n\n // node outputs\n const newsRes = $('Retrieve Company News Events').first().json;\n const jobsRes = $('Retrieve Company Job Openings').first().json;\n const techRes = $('Retrieve Technologies').first().json;\n\n const lookalike = $('Loop Lookalikes').first().json;\n\n const news = newsRes.data || [];\n const jobs = jobsRes.data || [];\n const tech = techRes.data || [];\n const included = techRes.included || [];\n\n let score = 0;\n\n // +30 Recent News\n const recentNews = news.filter(n => {\n const date = n.attributes?.found_at;\n return date && new Date(date) > thirtyDaysAgo;\n });\n\n if (recentNews.length > 0) score += 30;\n\n // +30 Hiring\n const jobCount = jobs.length;\n if (jobCount >= 5) score += 30;\n\n // FIXED TECH NAME RESOLUTION\n const targetTech = ['hubspot', 'salesforce', 'marketo'];\n\n // map techId -> actual name\n const techMap = {};\n for (const inc of included) {\n if (inc.type === 'technology') {\n techMap[inc.id] = (inc.attributes?.name || '').toLowerCase();\n }\n }\n\n // extract real tech names\n const techNames = tech.map(t => {\n const techId = t.relationships?.technology?.data?.id;\n return techMap[techId] || '';\n }).filter(Boolean);\n\n const techMatch = targetTech.some(t =>\n techNames.some(name => name.includes(t))\n );\n\n if (techMatch) score += 20;\n\n // +10 similarity\n const similarityScore = lookalike.similarity_score || 0;\n if (similarityScore > 0.7) score += 10;\n\n // country\n let country = '';\n const locEvent = news.find(n => n.attributes?.location_data?.length);\n if (locEvent) {\n country = locEvent.attributes.location_data[0]?.country || '';\n }\n\n // +10 region\n const targetRegions = ['United States', 'United Kingdom', 'Canada'];\n if (targetRegions.includes(country)) score += 10;\n\n results.push({\n json: {\n domain: lookalike.domain || '',\n company_name: lookalike.company_name || '',\n source_domain: lookalike.source_domain || '',\n similarity_score: similarityScore,\n news_count: recentNews.length,\n job_count: jobCount,\n tech_names: techNames.join(', '),\n tech_match: techMatch,\n composite_score: score,\n scored_at: now.toISOString()\n }\n });\n}\n\nreturn results;" }, "typeVersion": 2 }, { "id": "15aef871-aa65-4455-a7ee-4175c304b6a7", "name": "Filter High Scores", "type": "n8n-nodes-base.if", "disabled": true, "position": [ 3056, 672 ], "parameters": { "options": {}, "conditions": { "options": { "version": 3, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "4d0d80b2-ffde-4835-af87-23a69d458a22", "operator": { "type": "number", "operation": "gt" }, "leftValue": "={{ $json.composite_score }}", "rightValue": 70 } ] } }, "typeVersion": 2.3 }, { "id": "7312d2c1-1273-45e4-bd29-a0fffcc8ad50", "name": "Send High Score Alert", "type": "n8n-nodes-base.slack", "position": [ 3536, 656 ], "parameters": { "text": "=...", "select": "channel", "channelId": { "__rl": true, "mode": "list", "value": "C0AEEATQQEP", "cachedResultName": "buddieslab-umer" }, "otherOptions": {}, "authentication": "oAuth2" }, "typeVersion": 2.4 }, { "id": "dca9ac0c-96cc-49c1-8af3-b788fe5c76b3", "name": "Write Scored Output", "type": "n8n-nodes-base.googleSheets", "position": [ 3536, 896 ], "parameters": { "columns": { "value": { "domain": "={{ $json.domain }}", "job_count": "={{ $json.job_count }}", "scored_at": "={{ $json.scored_at }}", "news_count": "={{ $json.news_count }}", "tech_match": "={{ $json.tech_match }}", "tech_names": "={{ $json.tech_names }}", "company_name": "={{ $json.company_name }}", "source_domain": "={{ $json.source_domain }}", "composite_score": "={{ $json.composite_score }}", "similarity_score": "={{ $json.similarity_score }}" }, "schema": [ { "id": "domain", "type": "string", "display": true, "required": false, "displayName": "domain", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "company_name", "type": "string", "display": true, "required": false, "displayName": "company_name", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "source_domain", "type": "string", "display": true, "required": false, "displayName": "source_domain", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "similarity_score", "type": "string", "display": true, "required": false, "displayName": "similarity_score", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "news_count", "type": "string", "display": true, "required": false, "displayName": "news_count", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "job_count", "type": "string", "display": true, "required": false, "displayName": "job_count", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "tech_names", "type": "string", "display": true, "required": false, "displayName": "tech_names", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "tech_match", "type": "string", "display": true, "required": false, "displayName": "tech_match", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "composite_score", "type": "string", "display": true, "required": false, "displayName": "composite_score", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "scored_at", "type": "string", "display": true, "required": false, "displayName": "scored_at", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": 153216757, "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1KDGtZcPjGlSN5OuSG5TxtTIE1BPLIDIAyTs-yIjExTo/edit#gid=153216757", "cachedResultName": "Scored Lookalikes" }, "documentId": { "__rl": true, "mode": "list", "value": "1KDGtZcPjGlSN5OuSG5TxtTIE1BPLIDIAyTs-yIjExTo", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1KDGtZcPjGlSN5OuSG5TxtTIE1BPLIDIAyTs-yIjExTo/edit?usp=drivesdk", "cachedResultName": "09" } }, "typeVersion": 4.5 }, { "id": "f214607b-3076-4134-bceb-04f8aea2b373", "name": "Build Outreach Prompt", "type": "n8n-nodes-base.code", "position": [ 3536, 432 ], "parameters": { "jsCode": "const company = $json.company_name;\nconst domain = $json.domain;\nconst score = $json.composite_score;\n\n// SAFE email generation (fix for your error)\nconst recipientEmail = domain ? `contact@${domain}` : '';\n\nconst prompt = `Write a short B2B cold email.\n\nCompany: ${company}\nDomain: ${domain}\nLead Score: ${score}\n\nContext:\n- This company is similar to our best customers\n- Shows strong buying signals (hiring, news, tech)\n\nWrite a concise outreach email (max 120 words)\nInclude:\n- Personalized intro\n- Mention growth signals\n- CTA for quick call\n\nFormat:\nSubject: ...\nBody: ...`;\n\nreturn [{\n json: {\n ...$json,\n ai_prompt: prompt,\n recipient_email: recipientEmail\n }\n}];" }, "typeVersion": 2 }, { "id": "48724616-76e1-4780-a61e-4c59f301a2a9", "name": "Generate Outreach Email", "type": "n8n-nodes-base.httpRequest", "position": [ 3744, 432 ], "parameters": { "url": "https://api.openai.com/v1/chat/completions", "method": "POST", "options": {}, "jsonBody": "={\n \"model\": \"gpt-4o-mini\",\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are a professional B2B sales email writer. Write concise, personalized outreach emails.\"\n },\n {\n \"role\": \"user\",\n \"content\": {{ JSON.stringify($json.ai_prompt) }}\n }\n ],\n \"temperature\": 0.7,\n \"max_tokens\": 500\n}", "sendBody": true, "sendHeaders": true, "specifyBody": "json", "headerParameters": { "parameters": [ { "name": "Authorization", "value": "={{ $env.OPENAI_API_KEY ? 'Bearer ' + $env.OPENAI_API_KEY : '' }}" }, { "name": "Content-Type", "value": "application/json" } ] } }, "typeVersion": 4.2 }, { "id": "5dcd7765-37cd-4a49-b76f-885b9d152d6a", "name": "Send Outreach Email", "type": "n8n-nodes-base.gmail", "position": [ 3968, 432 ], "parameters": { "sendTo": "={{ $('Build Outreach Prompt').item.json.recipient_email }}", "message": "={{ $json.choices[0].message.content\n .replace(/Subject:\\s*.+\\n\\n/, '')\n .replace(/^Body:\\s*/i, '')\n}}", "options": {}, "subject": "={{ $json.choices[0].message.content.match(/Subject:\\s*(.+)/)?.[1] || 'Quick idea for your team' }}", "emailType": "text" }, "typeVersion": 2.2 } ], "connections": { "Loop Clients": { "main": [ [], [ { "node": "Retrieve Company", "type": "main", "index": 0 } ] ] }, "Loop Lookalikes": { "main": [ [ { "node": "Loop Clients", "type": "main", "index": 0 } ], [ { "node": "Retrieve Company News Events", "type": "main", "index": 0 } ] ] }, "Retrieve Company": { "main": [ [ { "node": "Extract Lookalikes", "type": "main", "index": 0 } ] ] }, "Extract Lookalikes": { "main": [ [ { "node": "Loop Lookalikes", "type": "main", "index": 0 } ] ] }, "Filter High Scores": { "main": [ [ { "node": "Send High Score Alert", "type": "main", "index": 0 }, { "node": "Write Scored Output", "type": "main", "index": 0 }, { "node": "Build Outreach Prompt", "type": "main", "index": 0 } ] ] }, "Write Scored Output": { "main": [ [ { "node": "Loop Lookalikes", "type": "main", "index": 0 } ] ] }, "Build Outreach Prompt": { "main": [ [ { "node": "Generate Outreach Email", "type": "main", "index": 0 } ] ] }, "Detect Growth Signals": { "main": [ [ { "node": "High Growth Detected?", "type": "main", "index": 0 } ] ] }, "High Growth Detected?": { "main": [ [ { "node": "Send Growth Alert", "type": "main", "index": 0 } ] ] }, "Retrieve Technologies": { "main": [ [ { "node": "Calculate Composite Score", "type": "main", "index": 0 } ] ] }, "Generate Outreach Email": { "main": [ [ { "node": "Send Outreach Email", "type": "main", "index": 0 } ] ] }, "Read Best Client Domains": { "main": [ [ { "node": "Loop Clients", "type": "main", "index": 0 } ] ] }, "Calculate Composite Score": { "main": [ [ { "node": "Filter High Scores", "type": "main", "index": 0 } ] ] }, "Retrieve Company News Events": { "main": [ [ { "node": "Retrieve Company Job Openings", "type": "main", "index": 0 }, { "node": "Detect Growth Signals", "type": "main", "index": 0 } ] ] }, "Retrieve Company Job Openings": { "main": [ [ { "node": "Retrieve Technologies", "type": "main", "index": 0 } ] ] }, "When clicking 'Execute workflow'": { "main": [ [ { "node": "Read Best Client Domains", "type": "main", "index": 0 } ] ] } } }