{ "name": "AI-Powered Lead Qualification & Routing System", "nodes": [ { "parameters": { "jsCode": "// Normalize different payload structures into unified format\nconst incomingData = $input.all();\nconst normalizedLeads = [];\n\nfor (const item of incomingData) {\n const payload = item.json;\n let normalized = {\n lead_id: `lead_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`,\n source: payload.source || 'unknown',\n raw_payload: payload,\n created_at: new Date().toISOString()\n };\n\n // Normalize based on source\n switch(payload.source) {\n case 'web_form':\n normalized.first_name = payload.data?.firstName;\n normalized.last_name = payload.data?.lastName;\n normalized.email = payload.data?.email;\n normalized.phone = payload.data?.phone;\n normalized.company_name = payload.data?.company;\n normalized.job_title = payload.data?.jobTitle;\n normalized.company_website = payload.data?.website;\n break;\n \n case 'linkedin':\n normalized.first_name = payload.lead_data?.first_name;\n normalized.last_name = payload.lead_data?.last_name;\n normalized.email = payload.lead_data?.email;\n normalized.phone = payload.lead_data?.phone;\n normalized.company_name = payload.lead_data?.company_name;\n normalized.job_title = payload.lead_data?.job_title;\n break;\n \n case 'calendly':\n const fullName = payload.payload?.invitee?.name?.split(' ') || [];\n normalized.first_name = fullName[0];\n normalized.last_name = fullName.slice(1).join(' ');\n normalized.email = payload.payload?.invitee?.email;\n normalized.phone = payload.payload?.invitee?.phone;\n normalized.company_name = payload.payload?.invitee?.custom_answers?.company;\n normalized.job_title = payload.payload?.invitee?.custom_answers?.job_title;\n normalized.company_website = payload.payload?.invitee?.custom_answers?.website;\n break;\n \n case 'hubspot':\n const fields = payload.fields || [];\n const getField = (name) => fields.find(f => f.name === name)?.value;\n \n normalized.first_name = getField('firstname');\n normalized.last_name = getField('lastname');\n normalized.email = getField('email');\n normalized.phone = getField('phone');\n normalized.company_name = getField('company');\n normalized.job_title = getField('jobtitle');\n normalized.company_website = getField('website');\n break;\n }\n\n // Validation - reject if missing critical fields\n if (!normalized.email || !normalized.company_name) {\n normalized.status = 'error';\n normalized.error_message = 'Missing required fields: email or company_name';\n } else {\n normalized.status = 'new';\n }\n\n normalizedLeads.push({ json: normalized });\n}\n\nreturn normalizedLeads;" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2320, -64 ], "id": "47f5bb60-fe79-4662-aff4-298642dbf051", "name": "Normalize Lead Data" }, { "parameters": { "httpMethod": "POST", "path": "YOUR_WEBHOOK_ID_HERE", "responseMode": "lastNode", "options": {} }, "type": "n8n-nodes-base.webhook", "typeVersion": 2.1, "position": [ -2544, -64 ], "id": "3ca3b9f5-b4c7-4e03-9153-e559c1306e53", "name": "lead-intake" }, { "parameters": { "jsCode": "// Basic email validation and spam detection\nconst items = $input.all();\nconst validatedItems = [];\n\nconst disposableEmailDomains = [\n 'tempmail.com', 'guerrillamail.com', '10minutemail.com', \n 'throwaway.email', 'mailinator.com', 'yopmail.com'\n];\n\nconst companyEmailPatterns = [\n '@gmail.com', '@yahoo.com', '@hotmail.com', '@outlook.com',\n '@aol.com', '@icloud.com', '@mail.com'\n];\n\nfor (const item of items) {\n const lead = item.json;\n \n // Skip if already has error\n if (lead.status === 'error') {\n validatedItems.push(item);\n continue;\n }\n \n const email = lead.email?.toLowerCase();\n const domain = email?.split('@')[1];\n \n // Check for disposable email\n if (disposableEmailDomains.includes(domain)) {\n lead.status = 'error';\n lead.error_message = 'Disposable email detected';\n validatedItems.push({ json: lead });\n continue;\n }\n \n // Flag personal emails (lower priority, not rejection)\n lead.is_personal_email = companyEmailPatterns.some(pattern => \n email?.includes(pattern)\n );\n \n // Basic email format validation\n const emailRegex = /^[^\\s@]+@[^\\s@]+\\.[^\\s@]+$/;\n if (!emailRegex.test(email)) {\n lead.status = 'error';\n lead.error_message = 'Invalid email format';\n validatedItems.push({ json: lead });\n continue;\n }\n \n // Phone validation (basic)\n if (lead.phone) {\n const phoneClean = lead.phone.replace(/\\D/g, '');\n if (phoneClean.length < 10) {\n lead.phone = null; // Remove invalid phone, don't reject lead\n }\n }\n \n validatedItems.push({ json: lead });\n}\n\nreturn validatedItems;" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2096, -64 ], "id": "ea18748e-165f-4c97-8dea-63b9b2458299", "name": "Validate Email" }, { "parameters": { "operation": "get", "tableId": "leads", "filters": { "conditions": [ { "keyName": "email", "keyValue": "={{ $json.email }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ -1648, -64 ], "id": "4c416a3b-a367-492b-86a9-a3e3af9619dc", "name": "Check Duplicate Email", "alwaysOutputData": true, "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "5ce48a04-d221-4263-a935-183e4ae61284", "leftValue": "={{ $json.created_at }}", "rightValue": "True", "operator": { "type": "string", "operation": "exists", "singleValue": true } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.2, "position": [ -1424, -64 ], "id": "35481782-681b-4789-8813-10e2a0c5ff85", "name": "If" }, { "parameters": { "jsCode": "const newLead = $('Validate Email').first().json;\nconst existingLead = $('Check Duplicate Email').first().json;\n\n// Mark as duplicate\nnewLead.is_duplicate = true;\nnewLead.duplicate_of = existingLead.id;\nnewLead.status = 'duplicate';\n\n// Log that we found a duplicate within 24 hours\nconsole.log(`Duplicate lead found: ${newLead.email} - Original: ${existingLead.lead_id}`);\n\nreturn { json: newLead };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1200, -160 ], "id": "44d7f065-37a2-4245-bd55-3355a57ef750", "name": "Mark as Duplicate" }, { "parameters": { "tableId": "leads", "fieldsUi": { "fieldValues": [ { "fieldId": "lead_id", "fieldValue": "={{ $('Validate Email').item.json.lead_id }}" }, { "fieldId": "source", "fieldValue": "={{ $('Validate Email').item.json.source }}" }, { "fieldId": "first_name", "fieldValue": "={{ $('Clean Data').item.json.first_name }}" }, { "fieldId": "last_name", "fieldValue": "={{ $('Clean Data').item.json.last_name }}" }, { "fieldId": "email", "fieldValue": "={{ $('Clean Data').item.json.email }}" }, { "fieldId": "phone", "fieldValue": "={{ $('Clean Data').item.json.phone }}" }, { "fieldId": "company_name", "fieldValue": "={{ $('Clean Data').item.json.company_name }}" }, { "fieldId": "job_title", "fieldValue": "={{ $('Clean Data').item.json.job_title }}" }, { "fieldId": "company_website", "fieldValue": "={{ $('Clean Data').item.json.company_website }}" }, { "fieldId": "status", "fieldValue": "={{ $('Validate Email').item.json.status }}" }, { "fieldId": "is_duplicate", "fieldValue": "=false" }, { "fieldId": "raw_payload", "fieldValue": "={{ $('Clean Data').item.json.raw_payload.payload }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ -1200, 32 ], "id": "1a6fcbf1-e28f-4e16-b0d0-434aa387ff5e", "name": "Insert New Lead", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "useCustomSchema": true, "tableId": "lead_audit_log", "fieldsUi": { "fieldValues": [ { "fieldId": "id", "fieldValue": "={{ $json.id }}" }, { "fieldId": "action", "fieldValue": "={{ $json.is_duplicate }} : {{ $json.duplicate_of }} : {{ $json.created_at }}" }, { "fieldId": "details", "fieldValue": "={{ $json.source }} : {{ $json.email }} : {{ $json.company_name }}\n" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ -752, -64 ], "id": "8fa61cc6-04f1-4443-9a7c-7df26554c412", "name": "Log Audit Trail", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "assignments": { "assignments": [ { "id": "1d621dd5-9411-4c1b-b40c-1f74e3d9e46f", "name": "created_at", "value": "={{ $json.created_at }}", "type": "string" }, { "id": "53171672-48dd-43f9-8cb9-c76d82530975", "name": "first_name", "value": "={{ $json.first_name }}", "type": "string" }, { "id": "dd72f0f8-e818-461c-ba3f-0e92716f670d", "name": "last_name", "value": "={{ $json.last_name }}", "type": "string" }, { "id": "4c4fb185-75c1-4715-9257-25d7ba8f5766", "name": "email", "value": "={{ $json.email }}", "type": "string" }, { "id": "abc3f9ef-eb16-431d-8ea3-5b33701ff0dc", "name": "phone", "value": "={{ $json.phone }}", "type": "string" }, { "id": "c23316a0-d651-4253-9128-782bd55c1d71", "name": "company_name", "value": "={{ $json.company_name }}", "type": "string" }, { "id": "8fb501c4-af8f-44eb-a79f-b8f965564c8b", "name": "job_title", "value": "={{ $json.job_title }}", "type": "string" }, { "id": "bce0c8ed-af83-4244-adaf-4be7336f866f", "name": "company_website", "value": "={{ $json.company_website }}", "type": "string" }, { "id": "1e6377ca-ecd6-482d-84be-d5fa2c0a5800", "name": "status", "value": "={{ $json.status }}", "type": "string" }, { "id": "ef33fe99-2202-4d16-bd34-d7b8d1a57cf2", "name": "is_personal_email", "value": "={{ $json.is_personal_email }}", "type": "boolean" }, { "id": "ccb1f68d-b0a7-4cde-965b-33be206706ff", "name": "raw_payload.payload", "value": "={{ $json.raw_payload.payload }}", "type": "object" } ] }, "options": {} }, "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ -1872, -64 ], "id": "f3226d09-d2e1-42dc-8809-89e8fc6e4aea", "name": "Clean Data" }, { "parameters": { "jsCode": "// Get the inserted lead\nconst lead = $input.first().json;\n\n// Add fields we'll need for enrichment\nconst enrichmentPayload = {\n id: lead.id,\n lead_id: lead.lead_id,\n email: lead.email,\n company_name: lead.company_name,\n company_website: lead.company_website,\n first_name: lead.first_name,\n last_name: lead.last_name,\n job_title: lead.job_title,\n phone: lead.phone,\n \n // Extract domain from email if no website provided\n email_domain: lead.email ? lead.email.split('@')[1] : null,\n \n // Set status\n status: 'enriching',\n enrichment_started_at: new Date().toISOString()\n};\n\n// Try to extract company domain from website or email\nif (lead.company_website) {\n try {\n const url = new URL(lead.company_website.startsWith('http') ? lead.company_website : 'https://' + lead.company_website);\n enrichmentPayload.company_domain = url.hostname.replace('www.', '');\n } catch (e) {\n enrichmentPayload.company_domain = lead.company_website.replace('www.', '').replace('https://', '').replace('http://', '').split('/')[0];\n }\n} else if (enrichmentPayload.email_domain) {\n // Use email domain as fallback\n enrichmentPayload.company_domain = enrichmentPayload.email_domain;\n}\n\nreturn { json: enrichmentPayload };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -128, 0 ], "id": "eaf41002-a3af-401a-9b66-723abf13a3c9", "name": "Prepare for Enrichment" }, { "parameters": { "jsCode": "// Get the original lead data\nconst originalLead = $('Prepare for Enrichment').first().json;\n\n// Initialize enriched data structure\nlet enrichedData = {\n id: originalLead.id,\n lead_id: originalLead.lead_id,\n company_domain: originalLead.company_domain,\n enrichment_source: 'none',\n enrichment_confidence: 0.0,\n tech_stack: [],\n buying_signals: {}\n};\n\n// Check if we have Clearbit data\nconst clearbitData = $('Clearbit Company Enrichment').all();\nif (clearbitData.length > 0 && clearbitData[0].json) {\n const cb = clearbitData[0].json;\n \n enrichedData.enrichment_source = 'clearbit';\n enrichedData.enrichment_confidence = 0.95;\n \n enrichedData.company_size = cb.metrics?.employees || null;\n enrichedData.company_employees_range = cb.metrics?.employeesRange || null;\n enrichedData.company_industry = cb.category?.industry || null;\n enrichedData.company_founded_year = cb.foundedYear || null;\n enrichedData.company_revenue_range = cb.metrics?.estimatedAnnualRevenue || null;\n enrichedData.company_funding_total = cb.metrics?.raised || null;\n enrichedData.company_location = cb.location ? `${cb.location.city}, ${cb.location.country}` : null;\n enrichedData.company_description = cb.description || null;\n enrichedData.company_linkedin_url = cb.linkedin?.handle ? `https://linkedin.com/company/${cb.linkedin.handle}` : null;\n enrichedData.company_twitter_url = cb.twitter?.handle ? `https://twitter.com/${cb.twitter.handle}` : null;\n \n // Tech stack from Clearbit\n if (cb.tech && Array.isArray(cb.tech)) {\n enrichedData.tech_stack = cb.tech;\n }\n \n console.log('\u2705 Clearbit enrichment successful');\n}\n// Check if we have Apollo data (fallback)\nelse {\n const apolloData = $('Apollo Company Lookup').all();\n if (apolloData.length > 0 && apolloData[0].json?.organization) {\n const org = apolloData[0].json.organization;\n \n enrichedData.enrichment_source = 'apollo';\n enrichedData.enrichment_confidence = 0.85;\n \n enrichedData.company_size = org.estimated_num_employees || null;\n enrichedData.company_employees_range = org.employee_range || null;\n enrichedData.company_industry = org.industry || null;\n enrichedData.company_founded_year = org.founded_year || null;\n enrichedData.company_revenue_range = org.estimated_annual_revenue || null;\n enrichedData.company_location = org.city && org.country ? `${org.city}, ${org.country}` : null;\n enrichedData.company_description = org.short_description || null;\n enrichedData.company_linkedin_url = org.linkedin_url || null;\n enrichedData.company_twitter_url = org.twitter_url || null;\n \n // Apollo doesn't provide tech stack directly\n enrichedData.tech_stack = [];\n \n console.log('\u2705 Apollo enrichment successful (Clearbit fallback)');\n } else {\n console.log('\u26a0\ufe0f Both Clearbit and Apollo enrichment failed');\n enrichedData.enrichment_source = 'failed';\n enrichedData.enrichment_confidence = 0.0;\n }\n}\n\n// Add buying signals detection\nenrichedData.buying_signals = {\n has_funding: !!enrichedData.company_funding_total,\n is_growing: enrichedData.company_size && parseInt(enrichedData.company_size) > 50,\n has_tech_stack: enrichedData.tech_stack.length > 0,\n recent_activity: false // We'll enhance this later\n};\n\nreturn { json: enrichedData };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 704, -16 ], "id": "8959539c-1414-4378-b29b-d68638f12bfa", "name": "Normalize Enrichment Data" }, { "parameters": { "jsCode": "const enrichedData = $('Normalize Enrichment Data').first().json;\nconst originalLead = $('Prepare for Enrichment').first().json;\n\n// Initialize email validation data\nlet emailValidation = {\n email_valid: false,\n email_deliverable: false,\n email_type: 'unknown',\n email_quality_score: 0,\n email_verification_details: {}\n};\n\n// Get Emailable validation result\nconst emailableData = $('Emailable - Verify Email').all();\n\nif (emailableData.length > 0 && emailableData[0].json) {\n const validation = emailableData[0].json;\n \n // Map Emailable state to our boolean fields\n emailValidation.email_valid = ['deliverable', 'risky'].includes(validation.state);\n emailValidation.email_deliverable = validation.state === 'deliverable';\n emailValidation.email_quality_score = validation.score || 0;\n \n // Determine email type\n if (validation.disposable) {\n emailValidation.email_type = 'disposable';\n emailValidation.email_valid = false;\n } else if (validation.role) {\n emailValidation.email_type = 'role_based';\n } else if (validation.free) {\n emailValidation.email_type = 'personal';\n } else {\n emailValidation.email_type = 'corporate';\n }\n \n // Store additional details\n emailValidation.email_verification_details = {\n state: validation.state,\n reason: validation.reason,\n is_role_account: validation.role,\n is_free_email: validation.free,\n is_disposable: validation.disposable,\n accept_all_domain: validation.accept_all,\n smtp_provider: validation.smtp_provider,\n suggested_correction: validation.did_you_mean\n };\n \n if (validation.did_you_mean) {\n emailValidation.email_suggested_correction = validation.did_you_mean;\n }\n \n console.log(`\u2705 Emailable validation: ${originalLead.email} - State: ${validation.state}, Score: ${validation.score}`);\n \n} else {\n // Fallback validation\n console.log('\u26a0\ufe0f Emailable API failed, using basic validation');\n \n const email = originalLead.email;\n const emailDomain = email.split('@')[1]?.toLowerCase();\n \n const emailRegex = /^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$/;\n emailValidation.email_valid = emailRegex.test(email);\n \n const personalDomains = ['gmail.com', 'yahoo.com', 'hotmail.com', 'outlook.com', 'icloud.com'];\n const disposableDomains = ['tempmail.com', 'guerrillamail.com', '10minutemail.com'];\n \n if (disposableDomains.includes(emailDomain)) {\n emailValidation.email_type = 'disposable';\n emailValidation.email_valid = false;\n } else if (personalDomains.includes(emailDomain)) {\n emailValidation.email_type = 'personal';\n } else {\n emailValidation.email_type = 'corporate';\n }\n \n emailValidation.email_deliverable = emailValidation.email_valid;\n emailValidation.email_quality_score = emailValidation.email_valid ? 50 : 0;\n}\n\n// Merge everything together\nconst finalData = {\n ...enrichedData,\n ...emailValidation,\n enrichment_completed_at: new Date().toISOString()\n};\n\nreturn { json: finalData };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1184, -16 ], "id": "140f288f-73d5-47bf-bb2e-21fd54ebfb15", "name": "Process Email Validation" }, { "parameters": { "jsCode": "const data = $input.first().json;\nconst originalLead = $('Prepare for Enrichment').first().json;\n\n// Decision maker title patterns\nconst cLevelTitles = ['ceo', 'cto', 'cfo', 'coo', 'cio', 'cmo', 'chief', 'founder', 'president', 'owner'];\nconst vpTitles = ['vp', 'vice president', 'v.p.', 'svp', 'evp'];\nconst directorTitles = ['director', 'head of', 'lead'];\nconst managerTitles = ['manager', 'senior manager'];\n\nconst jobTitle = (originalLead.job_title || '').toLowerCase();\n\nlet seniority = 'individual_contributor';\nlet isDecisionMaker = false;\nlet likelihood = 0.0;\n\nif (cLevelTitles.some(title => jobTitle.includes(title))) {\n seniority = 'c_level';\n isDecisionMaker = true;\n likelihood = 0.95;\n} else if (vpTitles.some(title => jobTitle.includes(title))) {\n seniority = 'vp';\n isDecisionMaker = true;\n likelihood = 0.90;\n} else if (directorTitles.some(title => jobTitle.includes(title))) {\n seniority = 'director';\n isDecisionMaker = true;\n likelihood = 0.75;\n} else if (managerTitles.some(title => jobTitle.includes(title))) {\n seniority = 'manager';\n isDecisionMaker = false;\n likelihood = 0.45;\n}\n\n// Boost likelihood if company is small (decision makers easier to reach)\nif (data.company_size && parseInt(data.company_size) < 50) {\n likelihood = Math.min(0.95, likelihood + 0.15);\n if (likelihood > 0.60) isDecisionMaker = true;\n}\n\nconsole.log(`Decision maker analysis: ${originalLead.job_title} \u2192 ${seniority} (${likelihood})`);\n\nconst finalData = {\n ...data,\n seniority_level: seniority,\n is_decision_maker: isDecisionMaker,\n decision_maker_likelihood: likelihood\n};\n\nreturn { json: finalData };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1392, -16 ], "id": "ca498f32-a702-44db-9c6d-f3e02127ded2", "name": "Analyze Decision Maker" }, { "parameters": { "jsCode": "const data = $input.first().json;\n\n// If we already have tech stack from Clearbit, enhance it\nlet techStack = data.tech_stack || [];\n\n// Add common tech signals based on company domain\nconst commonTechSignals = {\n 'aws': ['amazon', 'aws'],\n 'google_cloud': ['google', 'gcp'],\n 'azure': ['microsoft', 'azure'],\n 'stripe': ['stripe'],\n 'salesforce': ['salesforce'],\n 'hubspot': ['hubspot']\n};\n\n// Check if domain suggests tech usage\nif (data.company_domain) {\n const domain = data.company_domain.toLowerCase();\n \n Object.keys(commonTechSignals).forEach(tech => {\n const patterns = commonTechSignals[tech];\n if (patterns.some(pattern => domain.includes(pattern))) {\n if (!techStack.includes(tech)) {\n techStack.push(tech);\n }\n }\n });\n}\n\n// Industry-based tech predictions\nconst industryTechMapping = {\n 'software': ['aws', 'github', 'jira', 'slack'],\n 'saas': ['aws', 'stripe', 'intercom', 'segment'],\n 'fintech': ['aws', 'stripe', 'plaid', 'twilio'],\n 'ecommerce': ['shopify', 'stripe', 'klaviyo'],\n 'marketing': ['hubspot', 'marketo', 'segment', 'google_analytics']\n};\n\nif (data.company_industry) {\n const industry = data.company_industry.toLowerCase();\n \n Object.keys(industryTechMapping).forEach(key => {\n if (industry.includes(key)) {\n const predictedTech = industryTechMapping[key];\n predictedTech.forEach(tech => {\n if (!techStack.includes(tech)) {\n techStack.push(tech);\n }\n });\n }\n });\n}\n\n// Update buying signals with tech info\nconst buyingSignals = data.buying_signals || {};\nbuyingSignals.tech_stack_detected = techStack.length > 0;\nbuyingSignals.uses_cloud_platform = techStack.some(t => ['aws', 'google_cloud', 'azure'].includes(t));\nbuyingSignals.uses_modern_stack = techStack.some(t => ['react', 'vue', 'node', 'python', 'kubernetes'].includes(t));\n\nconsole.log(`Tech stack detected: ${techStack.join(', ')}`);\n\nreturn {\n json: {\n ...data,\n tech_stack: techStack,\n buying_signals: buyingSignals\n }\n};" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1600, -16 ], "id": "806eb272-6914-4319-97a6-8d0572e208bb", "name": "Detect Tech Stack Signals" }, { "parameters": { "jsCode": "const data = $input.first().json;\n\n// Calculate enrichment completeness score (0-100)\nlet score = 0;\nconst maxScore = 100;\nconst weights = {\n company_domain: 5,\n company_size: 10,\n company_industry: 10,\n company_revenue_range: 15,\n company_location: 5,\n company_description: 5,\n tech_stack: 15,\n email_verified: 10,\n is_decision_maker: 15,\n company_linkedin_url: 5,\n company_funding_total: 5\n};\n\n// ... existing code ...\n\n// Add special handling for email quality after the forEach loop\nif (data.email_quality_score) {\n const emailScore = data.email_quality_score;\n if (emailScore >= 80) {\n score += weights.email_verified;\n } else if (emailScore >= 60) {\n score += weights.email_verified * 0.7;\n } else if (emailScore >= 40) {\n score += weights.email_verified * 0.4;\n }\n}\n\nObject.keys(weights).forEach(field => {\n if (field === 'tech_stack') {\n if (data[field] && data[field].length > 0) {\n score += weights[field];\n }\n } else if (data[field] !== null && data[field] !== undefined && data[field] !== '') {\n score += weights[field];\n }\n});\n\n// Add quality indicators\nconst enrichmentQuality = {\n score: score,\n completeness: `${score}%`,\n missing_critical_fields: [],\n has_decision_maker: data.is_decision_maker || false,\n has_company_data: !!(data.company_size && data.company_industry),\n has_tech_signals: data.tech_stack && data.tech_stack.length > 0,\n email_quality: data.email_quality_score >= 70 ? 'high' : data.email_quality_score >= 40 ? 'medium' : 'low',\n email_verified: data.email_deliverable || false\n};\n\n// Identify missing critical fields\nconst criticalFields = ['company_size', 'company_industry', 'company_revenue_range'];\ncriticalFields.forEach(field => {\n if (!data[field]) {\n enrichmentQuality.missing_critical_fields.push(field);\n }\n});\n\nconsole.log(`Enrichment quality score: ${score}/100`);\n\nreturn {\n json: {\n ...data,\n enrichment_quality: enrichmentQuality,\n status: 'enriched' // Update status\n }\n};" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1808, -16 ], "id": "ab1889d2-9964-416c-b0de-d52188d05a34", "name": "Calculate Enrichment Score" }, { "parameters": { "operation": "update", "tableId": "leads", "filters": { "conditions": [ { "keyName": "id", "condition": "eq", "keyValue": "={{ $json.id }}" } ] }, "fieldsUi": { "fieldValues": [ { "fieldId": "status", "fieldValue": "={{ $json.status }}" }, { "fieldId": "company_domain", "fieldValue": "={{ $json.company_domain }}" }, { "fieldId": "company_size", "fieldValue": "={{ $json.company_size }}" }, { "fieldId": "company_industry", "fieldValue": "={{ $json.company_industry }}" }, { "fieldId": "company_founded_year", "fieldValue": "={{ $json.company_founded_year }}" }, { "fieldId": "company_employees_range", "fieldValue": "={{ $json.company_employees_range }}" }, { "fieldId": "company_funding_total", "fieldValue": "={{ $json.buying_signals.has_funding }}" }, { "fieldId": "company_revenue_range", "fieldValue": "={{ $json.company_revenue_range }}" }, { "fieldId": "company_location", "fieldValue": "={{ $json.company_location }}" }, { "fieldId": "company_description", "fieldValue": "={{ $json.company_description }}" }, { "fieldId": "company_linkedin_url", "fieldValue": "={{ $json.company_linkedin_url }}" }, { "fieldId": "company_twitter_url", "fieldValue": "={{ $json.company_twitter_url }}" }, { "fieldId": "tech_stack", "fieldValue": "={{ $json.buying_signals.tech_stack_detected }}" }, { "fieldId": "buying_signals", "fieldValue": "={{ $json.buying_signals }}" }, { "fieldId": "is_decision_maker", "fieldValue": "={{ $json.is_decision_maker }}" }, { "fieldId": "decision_maker_likelihood", "fieldValue": "={{ $json.decision_maker_likelihood }}" }, { "fieldId": "seniority_level", "fieldValue": "={{ $json.seniority_level }}" }, { "fieldId": "email_valid", "fieldValue": "={{ $json.email_valid }}" }, { "fieldId": "email_deliverable", "fieldValue": "={{ $json.email_deliverable }}" }, { "fieldId": "email_type", "fieldValue": "={{ $json.email_type }}" }, { "fieldId": "enrichment_data", "fieldValue": "={{ $json.enrichment_quality }}" }, { "fieldId": "enrichment_completed_at", "fieldValue": "={{ $json.enrichment_completed_at }}" }, { "fieldId": "enrichment_source", "fieldValue": "={{ $json.enrichment_source }}" }, { "fieldId": "enrichment_confidence", "fieldValue": "={{ $json.enrichment_confidence }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 2016, -16 ], "id": "65ee12c4-2961-4466-b3af-fa904ea2e33e", "name": "Save Enriched Data", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "url": "https://api.apollo.io/api/v1/organizations/enrich", "sendQuery": true, "queryParameters": { "parameters": [ { "name": "domain", "value": "={{ $json.company_website }}" } ] }, "sendHeaders": true, "headerParameters": { "parameters": [ { "name": "Cache-Control", "value": "no-cache" }, { "name": "accept", "value": "application/json" }, { "name": "x-api-key", "value": "xZ-8vx7w-7bJZ_-SXHOteQ" } ] }, "sendBody": true, "bodyParameters": { "parameters": [ {} ] }, "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.3, "position": [ 368, -16 ], "id": "78d4e9a0-4c30-4e4d-bdb7-0091ddce5398", "name": "Apollo Company Lookup" }, { "parameters": { "url": "=https://company.clearbit.com/v2/companies/find?domain={{ $json.company_domain }}", "authentication": "YOUR_API_KEY_HERE", "genericAuthType": "YOUR_API_KEY_HERE", "options": { "allowUnauthorizedCerts": false, "response": { "response": { "responseFormat": "json" } } } }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.3, "position": [ 112, -32 ], "id": "f2af06d1-886e-4dc1-9e86-131590ede9a1", "name": "Clearbit Company Enrichment", "credentials": { "httpHeaderAuth": { "name": "" } }, "onError": "continueErrorOutput" }, { "parameters": { "url": "https://api.emailable.com/v1/verify", "sendQuery": true, "queryParameters": { "parameters": [ { "name": "email", "value": "={{ $('Prepare for Enrichment').item.json.email }}" }, { "name": "api_key", "value": "live_7374ab6e9683eac86a2c" } ] }, "options": {} }, "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.3, "position": [ 960, -16 ], "id": "b02b58ee-a13f-42c2-83f7-14da07904b62", "name": "Emailable - Verify Email" }, { "parameters": { "tableId": "lead_audit_log", "fieldsUi": { "fieldValues": [ { "fieldId": "lead_id", "fieldValue": "={{ $json.id }}" }, { "fieldId": "action", "fieldValue": "enrichment_completed" }, { "fieldId": "details", "fieldValue": "=Source: {{ $('Calculate Enrichment Score').item.json.enrichment_source }}\nscore: {{ $('Calculate Enrichment Score').item.json.enrichment_quality.score }}\nConfidence: {{ $('Calculate Enrichment Score').item.json.enrichment_confidence }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 2224, -16 ], "id": "a00eb1e1-ae3e-423c-a6c9-5293e7921525", "name": "Log Enrichment Complete", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "content": "## Foundation & Data Flow \n", "height": 560, "width": 2064, "color": 2 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -2608, -320 ], "id": "9b46f814-e457-4909-a89a-dee86a818ffd", "name": "Sticky Note" }, { "parameters": { "content": "## Enrichment Pipeline\n", "height": 544, "width": 2672, "color": 3 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -240, -272 ], "id": "8198893f-0840-4f19-9ef2-186c9f2518ad", "name": "Sticky Note1" }, { "parameters": {}, "type": "n8n-nodes-base.merge", "typeVersion": 3.2, "position": [ -976, -64 ], "id": "3ec8a08c-831e-411f-bab9-0ea76de9799d", "name": "Merge" }, { "parameters": { "jsCode": "// Get the enriched lead data\nconst lead = $input.first().json;\n\n// Compile all data for AI analysis\nconst icpData = {\n // Lead identification\n lead_id: lead.lead_id,\n id: lead.id,\n \n // Contact info\n contact: {\n name: `${lead.first_name || ''} ${lead.last_name || ''}`.trim(),\n email: lead.email,\n job_title: lead.job_title || 'Unknown',\n seniority_level: lead.seniority_level || 'unknown',\n is_decision_maker: lead.is_decision_maker || false,\n decision_maker_likelihood: lead.decision_maker_likelihood || 0\n },\n \n // Company data\n company: {\n name: lead.company_name,\n domain: lead.company_domain,\n website: lead.company_website,\n size: lead.company_size || 'Unknown',\n employees_range: lead.company_employees_range || 'Unknown',\n industry: lead.company_industry || 'Unknown',\n location: lead.company_location || 'Unknown',\n founded_year: lead.company_founded_year,\n description: (lead.company_description || 'No description available').substring(0, 500), // Truncate for API limits\n revenue_range: lead.company_revenue_range || 'Unknown',\n funding_total: lead.company_funding_total || 'Unknown',\n funding_stage: lead.company_funding_stage || 'Unknown'\n },\n \n // Tech stack (ensure it's an array)\n tech_stack: Array.isArray(lead.tech_stack) ? lead.tech_stack : [],\n \n // Buying signals\n buying_signals: lead.buying_signals || {},\n \n // Email quality\n email_quality: {\n valid: lead.email_valid || false,\n deliverable: lead.email_deliverable || false,\n type: lead.email_type || 'unknown',\n quality_score: lead.email_quality_score || 0\n },\n \n // Enrichment quality\n enrichment: {\n source: lead.enrichment_source || 'none',\n confidence: lead.enrichment_confidence || 0,\n completed_at: lead.enrichment_completed_at\n },\n \n // Lead source\n source: lead.source,\n original_message: lead.raw_payload?.data?.message || lead.raw_payload?.payload?.invitee?.custom_answers?.challenge || null\n};\n\nconsole.log(`\u2705 Prepared ICP analysis for: ${icpData.company.name} (${icpData.contact.job_title})`);\n\nreturn { json: icpData };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -2400, 592 ], "id": "7b46b2d7-bfb5-49d9-bbd9-e57e653b4f94", "name": "Prepare ICP Analysis" }, { "parameters": { "modelId": { "__rl": true, "value": "gpt-5-mini", "mode": "list", "cachedResultName": "GPT-5-MINI" }, "responses": { "values": [ { "content": "=Evaluate this lead against our ICP criteria.\\n\\n## LEAD DATA\\n**Contact:**\\n- Name: {{ $json.contact.name }}\\n- Title: {{ $json.contact.job_title }}\\n- Seniority: {{ $json.contact.seniority_level }}\\n- Decision Maker: {{ $json.contact.is_decision_maker }} (likelihood: {{ $json.contact.decision_maker_likelihood }})\\n- Email Type: {{ $json.email_quality.type }} (score: {{ $json.email_quality.quality_score }}/100)\\n\\n**Company:**\\n- Name: {{ $json.company.name }}\\n- Industry: {{ $json.company.industry }}\\n- Size: {{ $json.company.size }} employees ({{ $json.company.employees_range }})\\n- Revenue: {{ $json.company.revenue_range }}\\n- Location: {{ $json.company.location }}\\n- Founded: {{ $json.company.founded_year }}\\n- Description: {{ $json.company.description }}\\n\\n**Tech Stack:** {{ $json.tech_stack.join(', ') || 'Unknown' }}\\n**Buying Signals:** {{ JSON.stringify($json.buying_signals) }}\\n**Lead Source:** {{ $json.source }}\\n{{ $json.original_message ? '**Message:** ' + $json.original_message : '' }}\\n\\n## OUR ICP\\n- Company Size: 50-500 employees (will consider 10-1000)\\n- Industries: SaaS, FinTech, E-commerce, MarTech, B2B Tech\\n- Decision Maker: VP+ or C-level preferred\\n- Revenue: $1M+ annual revenue\\n- Tech: Modern cloud platforms (AWS, GCP, Azure)\\n\\n## SCORING (100 points)\\n1. Company Size Fit (0-10)\\n2. Industry Alignment (0-15)\\n3. Revenue/Budget Fit (0-20)\\n4. Tech Stack Compatibility (0-10)\\n5. Decision Maker Authority (0-15)\\n6. Timeline Signals (0-10)\\n7. Competitive Threat (0-10)\\n8. Deal Size Potential (0-20)\\n\\n## TIERS\\n- A (85-100): Perfect fit, immediate outreach\\n- B (65-84): Good fit, standard qualification\\n- C (45-64): Partial fit, long-term nurture\\n- DISQUALIFIED (<45): Poor fit\\n\\nRespond with ONLY this JSON structure:\\n{\\n \\\"tier\\\": \\\"A\\\"|\\\"B\\\"|\\\"C\\\"|\\\"DISQUALIFIED\\\",\\n \\\"overall_score\\\": 0-100,\\n \\\"confidence_score\\\": 0.0-1.0,\\n \\\"component_scores\\\": {\\n \\\"company_size_fit\\\": 0-10,\\n \\\"industry_alignment\\\": 0-15,\\n \\\"revenue_budget_fit\\\": 0-20,\\n \\\"tech_stack_fit\\\": 0-10,\\n \\\"decision_maker_fit\\\": 0-15,\\n \\\"timeline_signals\\\": 0-10,\\n \\\"competitive_threat\\\": 0-10,\\n \\\"deal_size_potential\\\": 0-20\\n },\\n \\\"tier_reasoning\\\": \\\"1-2 sentence explanation\\\",\\n \\\"key_strengths\\\": [\\\"strength 1\\\", \\\"strength 2\\\"],\\n \\\"concerns\\\": [\\\"concern 1\\\"],\\n \\\"recommended_talking_points\\\": [\\n \\\"Specific point 1 about their company\\\",\\n \\\"Specific point 2 addressing pain point\\\",\\n \\\"Specific point 3 with social proof\\\"\\n ],\\n \\\"suggested_follow_up_angle\\\": \\\"Specific product feature or use case\\\",\\n \\\"predicted_deal_size\\\": \\\"$X,XXX-$X,XXX/month\\\",\\n \\\"predicted_close_timeline\\\": \\\"X-Y days\\\"\\n}\"\n " }, { "role": "system", "content": "You are an expert B2B SaaS sales analyst. Evaluate leads against ICP criteria and provide detailed scoring with reasoning. Always respond with valid JSON only." } ] }, "builtInTools": {}, "options": {} }, "type": "@n8n/n8n-nodes-langchain.openAi", "typeVersion": 2.1, "position": [ -2160, 592 ], "id": "3263bd51-071e-4213-894b-2e72a17659e3", "name": "OpenAI - Qualify Lead", "retryOnFail": true, "waitBetweenTries": 2000, "credentials": { "openAiApi": { "name": "" } }, "onError": "continueRegularOutput" }, { "parameters": { "jsCode": "const icpData = $('Prepare ICP Analysis').first().json;\n\n// Get AI response\nconst rawResponse = $input.first().json;\n\nlet aiResponse;\nlet modelUsed = 'gpt-5-mini';\n\n// Debug: Log the FULL raw response to see exact structure\nconsole.log('=== FULL RAW RESPONSE ===');\nconsole.log(JSON.stringify(rawResponse, null, 2));\nconsole.log('=== END RAW RESPONSE ===');\n\ntry {\n let content;\n \n // Check if rawResponse is the array directly\n if (Array.isArray(rawResponse)) {\n console.log('Response is an array with length:', rawResponse.length);\n \n if (rawResponse.length > 0) {\n const firstItem = rawResponse[0];\n console.log('First item keys:', Object.keys(firstItem));\n \n // Navigate to output\n if (firstItem.output) {\n console.log('Found output, type:', typeof firstItem.output);\n \n if (Array.isArray(firstItem.output)) {\n console.log('Output is array with length:', firstItem.output.length);\n \n if (firstItem.output.length > 0) {\n const firstOutput = firstItem.output[0];\n console.log('First output keys:', Object.keys(firstOutput));\n \n // Navigate to content\n if (firstOutput.content) {\n console.log('Found content, type:', typeof firstOutput.content);\n \n if (Array.isArray(firstOutput.content)) {\n console.log('Content is array with length:', firstOutput.content.length);\n \n if (firstOutput.content.length > 0) {\n const firstContent = firstOutput.content[0];\n console.log('First content keys:', Object.keys(firstContent));\n \n // Get the text\n if (firstContent.text) {\n content = firstContent.text;\n console.log('\u2705 Successfully extracted text from GPT-5 mini format');\n }\n }\n }\n }\n }\n }\n }\n }\n }\n // Handle if rawResponse has the output property directly\n else if (rawResponse.output) {\n console.log('Response has output property directly');\n \n if (Array.isArray(rawResponse.output) && rawResponse.output[0]?.content?.[0]?.text) {\n content = rawResponse.output[0].content[0].text;\n console.log('\u2705 Extracted text from direct output property');\n }\n }\n // Handle standard OpenAI format\n else if (rawResponse.choices && rawResponse.choices[0]?.message?.content) {\n console.log('Detected standard OpenAI format');\n content = rawResponse.choices[0].message.content;\n modelUsed = rawResponse.model || 'gpt-4o-mini';\n }\n \n if (!content) {\n throw new Error('Could not extract content. Top-level keys: ' + Object.keys(rawResponse).join(', '));\n }\n\n console.log('Extracted content length:', content.length);\n console.log('Content preview:', content.substring(0, 300));\n\n // Parse JSON (handle potential markdown wrapping)\n content = content.trim();\n \n const jsonMatch = content.match(/```json\\s*([\\s\\S]*?)\\s*```/);\n if (jsonMatch) {\n aiResponse = JSON.parse(jsonMatch[1]);\n console.log('\u2705 Parsed JSON from markdown block');\n } else {\n aiResponse = JSON.parse(content);\n console.log('\u2705 Parsed raw JSON');\n }\n \n console.log('Parsed AI response tier:', aiResponse.tier);\n console.log('Parsed AI response score:', aiResponse.overall_score);\n \n} catch (error) {\n console.error('\u274c Parsing failed:', error.message);\n console.error('Error stack:', error.stack);\n \n // Use fallback response\n aiResponse = {\n tier: 'C',\n overall_score: 50,\n confidence_score: 0.3,\n component_scores: {\n company_size_fit: 5,\n industry_alignment: 5,\n revenue_budget_fit: 10,\n tech_stack_fit: 5,\n decision_maker_fit: 5,\n timeline_signals: 5,\n competitive_threat: 5,\n deal_size_potential: 10\n },\n tier_reasoning: 'AI parsing failed - manual review needed: ' + error.message,\n key_strengths: ['Requires manual review'],\n concerns: ['AI qualification failed: ' + error.message],\n recommended_talking_points: [\n 'Manual qualification required',\n 'Review lead details',\n 'Schedule qualification call'\n ],\n suggested_follow_up_angle: 'Manual qualification needed',\n predicted_deal_size: 'Unknown',\n predicted_close_timeline: 'Unknown'\n };\n \n console.warn('\u26a0\ufe0f Using fallback qualification data');\n}\n\n// Validate AI response structure\nif (!aiResponse || !aiResponse.tier || aiResponse.overall_score === undefined) {\n console.error('Invalid AI response structure:', JSON.stringify(aiResponse));\n throw new Error('Invalid AI response: Missing required fields');\n}\n\n// Validate tier value\nconst validTiers = ['A', 'B', 'C', 'DISQUALIFIED'];\nif (!validTiers.includes(aiResponse.tier)) {\n console.warn(`\u26a0\ufe0f Invalid tier \"${aiResponse.tier}\", defaulting to C`);\n aiResponse.tier = 'C';\n}\n\n// Ensure score is within bounds\naiResponse.overall_score = Math.max(0, Math.min(100, Math.round(aiResponse.overall_score)));\n\n// Ensure confidence is decimal\nif (aiResponse.confidence_score > 1) {\n aiResponse.confidence_score = aiResponse.confidence_score / 100;\n}\n\n// Ensure arrays exist\naiResponse.key_strengths = Array.isArray(aiResponse.key_strengths) ? aiResponse.key_strengths : [];\naiResponse.concerns = Array.isArray(aiResponse.concerns) ? aiResponse.concerns : [];\naiResponse.recommended_talking_points = Array.isArray(aiResponse.recommended_talking_points) ? aiResponse.recommended_talking_points : [];\n\n// Build final qualification data\nconst qualificationData = {\n id: icpData.id,\n lead_id: icpData.lead_id,\n ai_score: aiResponse.overall_score,\n ai_tier: aiResponse.tier,\n ai_tier_reasoning: aiResponse.tier_reasoning || 'No reasoning provided',\n ai_confidence: aiResponse.confidence_score,\n ai_component_scores: aiResponse.component_scores,\n ai_key_strengths: aiResponse.key_strengths,\n ai_concerns: aiResponse.concerns,\n ai_talking_points: aiResponse.recommended_talking_points,\n ai_suggested_angle: aiResponse.suggested_follow_up_angle || 'Standard approach',\n ai_predicted_deal_size: aiResponse.predicted_deal_size || 'Unknown',\n ai_predicted_close_timeline: aiResponse.predicted_close_timeline || 'Unknown',\n ai_qualified_at: new Date().toISOString(),\n ai_model_used: modelUsed,\n status: 'qualified'\n};\n\nconsole.log(`\u2705 Lead qualified: ${icpData.company.name} - Tier ${aiResponse.tier} (${aiResponse.overall_score}/100)`);\n\nreturn { json: qualificationData };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1808, 592 ], "id": "ab417aac-a95d-40d4-8de1-a544f2e0dbcc", "name": "Parse AI Qualification" }, { "parameters": { "operation": "update", "tableId": "leads", "filters": { "conditions": [ { "keyName": "id", "condition": "eq", "keyValue": "={{ $json.id }}" } ] }, "fieldsUi": { "fieldValues": [ { "fieldId": "status", "fieldValue": "={{ $json.status }}" }, { "fieldId": "ai_score", "fieldValue": "={{ $json.ai_score }}" }, { "fieldId": "ai_tier", "fieldValue": "={{ $json.ai_tier }}" }, { "fieldId": "ai_tier_reasoning", "fieldValue": "={{ $json.ai_tier_reasoning }}" }, { "fieldId": "ai_confidence", "fieldValue": "={{ $json.ai_confidence }}" }, { "fieldId": "ai_component_scores", "fieldValue": "={{ $json.ai_component_scores }}" }, { "fieldId": "ai_key_strengths", "fieldValue": "={{ $json.ai_key_strengths }}" }, { "fieldId": "ai_concerns", "fieldValue": "={{ $json.ai_concerns }}" }, { "fieldId": "ai_talking_points", "fieldValue": "={{ $json.ai_talking_points }}" }, { "fieldId": "ai_suggested_angle", "fieldValue": "={{ $json.ai_suggested_angle }}" }, { "fieldId": "ai_predicted_deal_size", "fieldValue": "={{ $json.ai_predicted_deal_size }}" }, { "fieldId": "ai_predicted_close_timeline", "fieldValue": "={{ $json.ai_predicted_close_timeline }}" }, { "fieldId": "ai_qualified_at", "fieldValue": "={{ $json.ai_qualified_at }}" }, { "fieldId": "ai_model_used", "fieldValue": "={{ $json.ai_model_used }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ -1600, 592 ], "id": "9f56cf45-a9ef-4a9e-b50a-28a3edca9714", "name": "Save AI Qualification", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "content": "## AI Qualification Engine\n", "height": 496, "width": 1680, "color": 4 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -2496, 288 ], "id": "d0afd8fd-6464-4b6e-a380-5b565c0378ec", "name": "Sticky Note2" }, { "parameters": { "tableId": "lead_audit_log", "fieldsUi": { "fieldValues": [ { "fieldId": "lead_id", "fieldValue": "={{ $json.id }}" }, { "fieldId": "action", "fieldValue": "ai_qualified" }, { "fieldId": "details", "fieldValue": "=tier: {{ $json.ai_tier }} \nscore: {{ $json.ai_score }}\nconfidence: {{ $json.ai_confidence }}\nmodel: {{ $json.ai_model_used }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ -1392, 592 ], "id": "ab6d80bb-d012-4066-981b-ca8b2ce926b5", "name": "Log AI Qualification", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "da454196-b829-43f9-ba54-39548d5a46b4", "leftValue": "={{ $('Parse AI Qualification').item.json.ai_tier }}", "rightValue": "A", "operator": { "type": "string", "operation": "equals", "name": "filter.operator.equals" } }, { "id": "fd5b3a84-e324-4b59-8069-9c6eb1e27de0", "leftValue": "={{ $('Parse AI Qualification').item.json.ai_tier }}", "rightValue": "B", "operator": { "type": "string", "operation": "equals", "name": "filter.operator.equals" } } ], "combinator": "or" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.2, "position": [ -144, 592 ], "id": "b0e938da-3327-4b99-b3b5-5d988ad01402", "name": "Route by Tier" }, { "parameters": { "operation": "get", "tableId": "leads", "filters": { "conditions": [ { "keyName": "lead_id", "keyValue": "={{ $('Save AI Qualification').item.json.lead_id }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 64, 496 ], "id": "3a4f2bc9-5bd1-4dff-89db-5cf90b88d91c", "name": "Get Full Lead Data", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "operation": "get", "tableId": "sales_reps", "filters": { "conditions": [ { "keyName": "status", "keyValue": "active" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 272, 496 ], "id": "a79b26c9-1ca4-4816-9756-b3b188c4d64c", "name": "Find Available Sales Rep", "executeOnce": false, "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "jsCode": "// Get all active sales reps from previous node\nconst items = $input.all();\n\n// Sort by current_load ascending (lowest first)\nconst sortedItems = items.sort((a, b) => {\n const loadA = a.json.current_load || 0;\n const loadB = b.json.current_load || 0;\n return loadA - loadB;\n});\n\n// Return only the first item (rep with lowest load)\nreturn sortedItems.slice(0, 1);" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 480, 496 ], "id": "139b0b05-5cec-40d6-ad3f-ff9207a41c98", "name": "Filter and Sort Sales Reps" }, { "parameters": { "jsCode": "const lead = $('Get Full Lead Data').first().json;\nconst salesRep = $('Find Available Sales Rep').first().json;\n\n// Build assignment data\nconst assignment = {\n lead_id: lead.id,\n lead_data: {\n name: `${lead.first_name} ${lead.last_name}`,\n email: lead.email,\n company: lead.company_name,\n job_title: lead.job_title,\n ai_tier: lead.ai_tier,\n ai_score: lead.ai_score,\n ai_talking_points: lead.ai_talking_points,\n ai_predicted_deal_size: lead.ai_predicted_deal_size,\n company_industry: lead.company_industry,\n company_size: lead.company_size\n },\n sales_rep: {\n id: salesRep.id,\n name: salesRep.name,\n email: salesRep.email,\n territory: salesRep.territory\n },\n assignment_reason: `Auto-assigned based on availability (current load: ${salesRep.current_load}/${salesRep.max_capacity})`\n};\n\nconsole.log(`\u2705 Assigned ${lead.company_name} to ${salesRep.name}`);\n\nreturn { json: assignment };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 688, 496 ], "id": "3b1c8503-9a77-4a1c-b190-b7e22630609d", "name": "Assign Sales Rep" }, { "parameters": { "operation": "update", "tableId": "leads", "filters": { "conditions": [ { "keyName": "id", "condition": "eq", "keyValue": "={{ $json.lead_id }}" } ] }, "fieldsUi": { "fieldValues": [ { "fieldId": "assigned_to_rep_id", "fieldValue": "={{ $json.sales_rep.id }}" }, { "fieldId": "assigned_at", "fieldValue": "={{ new Date().toISOString() }}" }, { "fieldId": "assignment_reason", "fieldValue": "={{ $json.assignment_reason }}" }, { "fieldId": "hubspot_contact_id", "fieldValue": "={{ $('Extract HubSpot IDs').item.json.hubspot_contact_id }}" }, { "fieldId": "hubspot_deal_id", "fieldValue": "={{ $('Extract HubSpot IDs').item.json.hubspot_deal_id }}" }, { "fieldId": "hubspot_deal_stage", "fieldValue": "={{ $('Extract HubSpot IDs').item.json.hubspot_deal_stage }}" }, { "fieldId": "hubspot_deal_amount", "fieldValue": "={{ $('Extract HubSpot IDs').item.json.hubspot_deal_amount }}" }, { "fieldId": "hubspot_synced_at", "fieldValue": "={{ $('Extract HubSpot IDs').item.json.hubspot_synced_at }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 2256, 496 ], "id": "390686ff-946f-4583-90cb-250d7d352e03", "name": "Update Lead Assignment", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "operation": "update", "tableId": "sales_reps", "filters": { "conditions": [ { "keyName": "id", "condition": "eq", "keyValue": "={{ $json.assigned_to_rep_id }}" } ] }, "fieldsUi": { "fieldValues": [ { "fieldId": "current_load", "fieldValue": "={{ $('Find Available Sales Rep').item.json.current_load + 1 }}" } ] } }, "type": "n8n-nodes-base.supabase", "typeVersion": 1, "position": [ 2464, 496 ], "id": "65a518ad-d5cf-4810-9a13-e812a5331629", "name": "Increment Rep Load", "credentials": { "supabaseApi": { "name": "" } } }, { "parameters": { "authentication": "YOUR_API_KEY_HERE", "select": "channel", "channelId": { "__rl": true, "value": "C0A31HAH125", "mode": "list", "cachedResultName": "all-first-p-roject" }, "text": "=\ud83d\udd25 NEW {{ $('Assign Sales Rep').item.json.lead_data.ai_tier }}-TIER LEAD - IMMEDIATE ACTION\n\nCompany: {{ $('Assign Sales Rep').item.json.lead_data.company }}\nContact: {{ $('Assign Sales Rep').item.json.lead_data.name }} | {{ $('Assign Sales Rep').item.json.lead_data.job_title }}\nEmail: {{ $('Assign Sales Rep').item.json.lead_data.email }}\nAI Qualification Score:* {{ $('Assign Sales Rep').item.json.lead_data.ai_score }}/100 ({{ $('Assign Sales Rep').item.json.lead_data.ai_tier }}-Tier)\nPredicted Deal Size: {{ $('Assign Sales Rep').item.json.lead_data.ai_predicted_deal_size }}\nIndustry:{{ $('Assign Sales Rep').item.json.lead_data.company_industry }}\nCompany Size:* {{ $('Assign Sales Rep').item.json.lead_data.company_size }} employees\n\ud83c\udfaf Assigned To:* {{ $('Assign Sales Rep').item.json.sales_rep.name }}\nAI TALKING POINTS:{{ $('Assign Sales Rep').item.json.lead_data.ai_talking_points[0] ? '1\ufe0f\u20e3 ' + $('Assign Sales Rep').item.json.lead_data.ai_talking_points[0] : '' }} {{ $('Assign Sales Rep').item.json.lead_data.ai_talking_points[1] ? '2\ufe0f\u20e3 ' + $('Assign Sales Rep').item.json.lead_data.ai_talking_points[1] : '' }} {{ $('Assign Sales Rep').item.json.lead_data.ai_talking_points[2] ? '3\ufe0f\u20e3 ' + $('Assign Sales Rep').item.json.lead_data.ai_talking_points[2] : '' }}\n\u23f0 Action: Call within 30 minutes for A-tier, 24 hours for B-tier\n", "otherOptions": {} }, "type": "n8n-nodes-base.slack", "typeVersion": 2.3, "position": [ 2672, 496 ], "id": "8345ed22-3f22-450f-a3ef-0eaa9621db5e", "name": "Slack - Notify Sales Team", "credentials": { "slackOAuth2Api": { "name": "" } } }, { "parameters": { "jsCode": "const lead = $('Parse AI Qualification').first().json;\n\nconsole.log(`\ud83d\udccb Low priority lead: ${lead.ai_tier} tier - No immediate action needed`);\n\nreturn { \n json: {\n lead_id: lead.id,\n tier: lead.ai_tier,\n action: 'logged_only',\n message: `${lead.ai_tier}-tier lead logged for future nurture`\n }\n};" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 64, 688 ], "id": "58cefe9c-440d-44ef-b185-d71a2c8983ba", "name": "Log Low Priority Lead" }, { "parameters": { "authentication": "YOUR_API_KEY_HERE", "select": "channel", "channelId": { "__rl": true, "value": "C0A31HAH125", "mode": "list", "cachedResultName": "all-first-p-roject" }, "text": "=\ud83d\udcca New {{ $('Parse AI Qualification').item.json.ai_tier }}-Tier Lead (No immediate action)\nCompany: {{ $('Prepare ICP Analysis').item.json.company.name }}\nContact: {{ $('Prepare ICP Analysis').item.json.contact.name }}\nScore: {{ $('Parse AI Qualification').item.json.ai_score }}/100\n\nAdded to nurture sequence - no sales action required\n", "otherOptions": {} }, "type": "n8n-nodes-base.slack", "typeVersion": 2.3, "position": [ 272, 688 ], "id": "35ca85d9-a887-4659-a8da-bf2ae03db649", "name": "Slack - Log C-Tier Lead", "credentials": { "slackOAuth2Api": { "name": "" } } }, { "parameters": { "authentication": "YOUR_API_KEY_HERE", "operation": "search", "limit": 1, "filterGroupsUi": { "filterGroupsValues": [ { "filtersUi": { "filterValues": [ { "propertyName": "email|string", "value": "={{ $json.lead_data.email }}" } ] } } ] }, "additionalFields": {} }, "type": "n8n-nodes-base.hubspot", "typeVersion": 2.2, "position": [ 896, 496 ], "id": "d27ec3e6-f9de-4244-8c9c-6df955f6eeb5", "name": "Check Existing Contact", "alwaysOutputData": true, "credentials": { "hubspotOAuth2Api": { "name": "" } } }, { "parameters": { "conditions": { "options": { "caseSensitive": true, "leftValue": "", "typeValidation": "strict", "version": 2 }, "conditions": [ { "id": "1246a38b-2d9b-443d-9328-12ed4964e3c0", "leftValue": "={{ $json.id }}", "rightValue": "", "operator": { "type": "string", "operation": "notEmpty", "singleValue": true } } ], "combinator": "and" }, "options": {} }, "type": "n8n-nodes-base.if", "typeVersion": 2.2, "position": [ 1120, 496 ], "id": "467b71d4-0a30-47b5-a62a-8d6c92011809", "name": "Contact Exists?" }, { "parameters": { "authentication": "YOUR_API_KEY_HERE", "email": "={{ $('Assign Sales Rep').item.json.lead_data.email }}", "additionalFields": { "companyName": "={{ $('Assign Sales Rep').item.json.lead_data.company }}", "firstName": "={{ $('Assign Sales Rep').item.json.lead_data.name.split(' ')[0] }}", "jobTitle": "={{ $('Assign Sales Rep').item.json.lead_data.job_title }}", "lastName": "={{ $('Assign Sales Rep').item.json.lead_data.name.split(' ').slice(1).join(' ') }}", "leadStatus": "OPEN" }, "options": {} }, "type": "n8n-nodes-base.hubspot", "typeVersion": 2.2, "position": [ 1344, 368 ], "id": "07adce25-9169-45a1-937e-ae72fc797eea", "name": "Update Contact", "credentials": { "hubspotOAuth2Api": { "name": "" } } }, { "parameters": { "authentication": "YOUR_API_KEY_HERE", "email": "={{ $('Assign Sales Rep').item.json.lead_data.email }}", "additionalFields": { "companyName": "={{ $('Assign Sales Rep').item.json.lead_data.company }}", "firstName": "={{ $('Assign Sales Rep').item.json.lead_data.name.split(' ')[0] }}", "jobTitle": "={{ $('Assign Sales Rep').item.json.lead_data.job_title }}", "lastName": "={{ $('Assign Sales Rep').item.json.lead_data.name.split(' ').slice(1).join(' ') }}", "leadStatus": "OPEN", "phoneNumber": "={{ $('Get Full Lead Data').item.json.phone }}", "websiteUrl": "={{ $('Get Full Lead Data').item.json.company_website }}" }, "options": {} }, "type": "n8n-nodes-base.hubspot", "typeVersion": 2.2, "position": [ 1344, 624 ], "id": "a961bbcb-789d-4d51-8f40-a198a755106e", "name": "Create Contact", "credentials": { "hubspotOAuth2Api": { "name": "" } } }, { "parameters": {}, "type": "n8n-nodes-base.merge", "typeVersion": 3.2, "position": [ 1600, 496 ], "id": "99cd35c2-9dda-429b-992c-66b294778837", "name": "erge HubSpot Contact" }, { "parameters": { "authentication": "YOUR_API_KEY_HERE", "resource": "deal", "stage": "appointmentscheduled", "additionalFields": { "amount": "={{ $('Assign Sales Rep').item.json.lead_data.ai_predicted_deal_size.match(/\\\\d+/g) ? parseInt($('Assign Sales Rep').item.json.lead_data.ai_predicted_deal_size.match(/\\\\d+/g)[0]) * 12 : 0 }}", "closeDate": "={{ new Date(Date.now() + 30*24*60*60*1000).toISOString() }}", "description": "=AI Qualification Score: {{ $('Assign Sales Rep').item.json.lead_data.ai_score }}/100\nTier: {{ $('Assign Sales Rep').item.json.lead_data.ai_tier }}\n\nCompany Details:\n- Industry: {{ $('Assign Sales Rep').item.json.lead_data.company_industry }}\n- Size: {{ $('Assign Sales Rep').item.json.lead_data.company_size }} employees\n\nAI Talking Points:\n1. {{ $('Assign Sales Rep').item.json.lead_data.ai_talking_points[0] }}\n2. {{ $('Assign Sales Rep').item.json.lead_data.ai_talking_points[1] }}\n3. {{ $('Assign Sales Rep').item.json.lead_data.ai_talking_points[2] }}", "dealName": "={{ $('Assign Sales Rep').item.json.lead_data.company }} - {{ $('Assign Sales Rep').item.json.lead_data.ai_tier }} Tier", "pipeline": "default" } }, "type": "n8n-nodes-base.hubspot", "typeVersion": 2.2, "position": [ 1808, 496 ], "id": "45c1e258-4de0-4ab6-9145-76581bcfe7d3", "name": "Create Deal", "credentials": { "hubspotOAuth2Api": { "name": "" } } }, { "parameters": { "jsCode": "const lead = $('Assign Sales Rep').first().json;\nconst contact = $('Merge HubSpot Contact').first().json;\nconst deal = $('HubSpot - Create Deal').first().json;\n\nconst hubspotData = {\n lead_id: lead.lead_id,\n hubspot_contact_id: contact.id || contact.vid || null,\n hubspot_deal_id: deal.id || null,\n hubspot_deal_stage: deal.properties?.dealstage || 'appointmentscheduled',\n hubspot_deal_amount: deal.properties?.amount || 0,\n hubspot_synced_at: new Date().toISOString()\n};\n\nconsole.log(`\u2705 HubSpot sync complete - Contact: ${hubspotData.hubspot_contact_id}, Deal: ${hubspotData.hubspot_deal_id}`);\n\nreturn { json: hubspotData };" }, "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 2016, 496 ], "id": "6b47733d-6869-4467-987e-731ea6b70b69", "name": "Extract HubSpot IDs" }, { "parameters": { "content": "## CRM Integration & Intelligent Routing", "height": 704, "width": 3248, "color": 5 }, "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -368, 320 ], "id": "eb480aa4-b43d-45b1-8756-5da62d3ba16a", "name": "Sticky Note3" } ], "connections": { "lead-intake": { "main": [ [ { "node": "Normalize Lead Data", "type": "main", "index": 0 } ] ] }, "Normalize Lead Data": { "main": [ [ { "node": "Validate Email", "type": "main", "index": 0 } ] ] }, "Validate Email": { "main": [ [ { "node": "Clean Data", "type": "main", "index": 0 } ] ] }, "Check Duplicate Email": { "main": [ [ { "node": "If", "type": "main", "index": 0 } ] ] }, "If": { "main": [ [ { "node": "Mark as Duplicate", "type": "main", "index": 0 } ], [ { "node": "Insert New Lead", "type": "main", "index": 0 } ] ] }, "Mark as Duplicate": { "main": [ [ { "node": "Merge", "type": "main", "index": 0 } ] ] }, "Insert New Lead": { "main": [ [ { "node": "Prepare for Enrichment", "type": "main", "index": 0 }, { "node": "Merge", "type": "main", "index": 1 } ] ] }, "Clean Data": { "main": [ [ { "node": "Check Duplicate Email", "type": "main", "index": 0 } ] ] }, "Prepare for Enrichment": { "main": [ [ { "node": "Clearbit Company Enrichment", "type": "main", "index": 0 } ] ] }, "Normalize Enrichment Data": { "main": [ [ { "node": "Emailable - 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