{ "id": "HwjLSOZT3wBzXHIX", "meta": { "templateCredsSetupCompleted": true }, "name": "B2B Lead Generation", "tags": [], "nodes": [ { "id": "55f22d58-5f9b-4642-ad6e-48a1d2e81070", "name": "When clicking \u2018Execute workflow\u2019", "type": "n8n-nodes-base.manualTrigger", "position": [ -2220, 20 ], "parameters": {}, "typeVersion": 1 }, { "id": "f89824ee-e8e5-4417-8cd2-465a9b4241e6", "name": "Split Out", "type": "n8n-nodes-base.splitOut", "position": [ -1780, 20 ], "parameters": { "options": {}, "fieldToSplitOut": "organic_results" }, "typeVersion": 1 }, { "id": "dfc26b49-1a53-46b7-8240-d9987b42be1d", "name": "AI Agent", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ -1120, 20 ], "parameters": { "text": "={{ $json }}", "options": { "systemMessage": "Analyze this processed company website content and extract B2B lead information. Return ONLY valid JSON:\n\nCompany URL: {{ $json.url }}\nCompany Name: {{ $json.company_name }}\nProcessed Website Content: {{ $json.content }}\nContent Quality Assessment: {{ $json.content_quality }}\nPre-extracted Contact Information: \n- Emails: {{ $json.extracted_emails }}\n- Phones: {{ $json.extracted_phones }}\nMetadata Information: {{ $json.metadata_info }}\nProcessing Details:\n- Raw content length: {{ $json.raw_content_length }} characters\n- Processed content length: {{ $json.processed_content_length }} characters\n- Processing status: {{ $json.processing_status }}\n\nBased on this structured data, extract and qualify this B2B lead. Return ONLY valid JSON:\n\n{\n \"company_name\": \"Official company name from content\",\n \"industry\": \"Primary industry/sector identified\", \n \"company_size\": \"Employee count or size category (startup/SMB/mid-market/enterprise)\",\n \"location\": \"Headquarters location or primary market\",\n \"contact_email\": \"Best general or sales email from extracted emails\",\n \"phone\": \"Primary phone number from extracted phones\",\n \"key_services\": [\"Main services/products offered based on content\"],\n \"target_market\": \"Who they serve (B2B/B2C, SMB/Enterprise, specific industries)\",\n \"technologies\": [\"Tech stack, platforms, or tools mentioned\"],\n \"funding_stage\": \"Funding stage if mentioned (seed/series A/B/C/public/private)\",\n \"business_model\": \"Revenue model (SaaS/consulting/product/marketplace)\",\n \"social_presence\": {\n \"linkedin\": \"LinkedIn company URL if found in content\",\n \"twitter\": \"Twitter handle if found\"\n },\n \"lead_score\": 8.5,\n \"qualification_reasons\": [\"Specific reasons why this lead is qualified or not\"],\n \"decision_makers\": [\"Names and titles of key contacts found\"],\n \"next_actions\": [\"Recommended follow-up strategies based on company profile\"],\n \"content_insights\": {\n \"website_quality\": \"Professional/Basic/Poor based on content richness\",\n \"recent_activity\": \"Any recent news, funding, or updates mentioned\",\n \"competitive_positioning\": \"How they position vs competitors\"\n }\n}\n\nEnhanced Scoring Criteria (1-10):\n- 9-10: Perfect ICP fit + complete contact info + high growth signals + professional content\n- 7-8: Good ICP fit + some contact info + stable company + quality content \n- 5-6: Moderate fit + limited contact info + basic content + needs research\n- 3-4: Poor fit + minimal info + low-quality content + wrong target market\n- 1-2: Not qualified + no contact info + processing failed + irrelevant\n\nScoring Factors to Consider:\n- Content Quality Score: {{ $json.content_quality.content_richness_score }}/10\n- Contact Information: {{ $json.content_quality.email_count }} emails, {{ $json.content_quality.phone_count }} phones\n- Content Completeness: {{ $json.content_quality.has_about_section }}, {{ $json.content_quality.has_services_section }}\n- Processing Success: {{ $json.processing_status }}\n- Content Volume: {{ $json.content_quality.word_count }} words\n\nInstructions:\n- Use ONLY the pre-extracted contact information from extracted_emails and extracted_phones\n- Base company_name on the processed company_name field, not the raw content\n- Factor in the content_quality metrics when determining lead_score\n- If processing_status is not \"SUCCESS\", lower the score significantly\n- Use null for any missing information - do not hallucinate data\n- Be conservative with scoring - better to underscore than overscore\n- Focus on B2B relevance and ICP fit based on the structured content provided" }, "promptType": "define" }, "typeVersion": 2 }, { "id": "824b3e22-552e-4147-a2ba-119d3a912846", "name": "Anthropic Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic", "position": [ -1140, 200 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "claude-sonnet-4-20250514", "cachedResultName": "Claude 4 Sonnet" }, "options": {} }, "credentials": { "anthropicApi": { "name": "" } }, "typeVersion": 1.3 }, { "id": "efd84a24-ecdf-4aa9-9d4a-93a9aed13af6", "name": "HTTP Request", "type": "n8n-nodes-base.httpRequest", "position": [ -80, 0 ], "parameters": { "url": "", "method": "POST", "options": {}, "jsonBody": "={\n \"embeds\": [\n {\n \"title\": \"\ud83c\udfaf New Qualified Lead Found!\",\n \"description\": \"**{{ $json.company_name || 'Unknown Company' }}** (Score: {{ $json.lead_score || 0 }}/10)\",\n \"color\": 3066993,\n \"fields\": [\n {\n \"name\": \"Industry\",\n \"value\": \"{{ $json.industry || 'Not specified' }}\",\n \"inline\": true\n },\n {\n \"name\": \"Size\",\n \"value\": \"{{ $json.company_size || 'Not specified' }}\",\n \"inline\": true\n },\n {\n \"name\": \"Location\", \n \"value\": \"{{ $json.location || 'Not specified' }}\",\n \"inline\": true\n },\n {\n \"name\": \"Contact\",\n \"value\": \"{{ $json.contact_email || 'No email found' }}\",\n \"inline\": false\n },\n {\n \"name\": \"Phone\",\n \"value\": \"{{ $json.phone || 'No phone found' }}\",\n \"inline\": false\n },\n {\n \"name\": \"Services\",\n \"value\": \"{{ $json.key_services && $json.key_services.length > 0 ? $json.key_services.slice(0, 3).join(', ') : 'Not specified' }}\",\n \"inline\": false\n },\n {\n \"name\": \"Website\",\n \"value\": \"[Visit Website]({{ $node['Analyze and Clean the data'].json.url || '#' }})\",\n \"inline\": false\n },\n {\n \"name\": \"Why Qualified\",\n \"value\": \"{{ $json.qualification_reasons && $json.qualification_reasons.length > 0 ? $json.qualification_reasons.slice(0, 2).join(' \u2022 ') : 'Standard qualification criteria met' }}\",\n \"inline\": false\n }\n ],\n \"footer\": {\n \"text\": \"Generated by n8n Lead Generation Workflow\"\n },\n \"timestamp\": \"\"\n }\n ]\n}", "sendBody": true, "sendHeaders": true, "specifyBody": "json", "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] } }, "typeVersion": 4.2 }, { "id": "a60059d8-8826-4d9c-9e4a-8f0050056293", "name": "scrape the keywords data", "type": "n8n-nodes-scrapeless.scrapeless", "position": [ -2000, 20 ], "parameters": { "q": "\"software companies\" \"enterprise clients\" employees:50-200 \"marketing agencies\" \"B2B services\" \"digital transformation\" \"SaaS startups\" \"Series A\" \"venture backed\" \"manufacturing companies\" \"digital solutions\" ISO" }, "credentials": { "scrapelessApi": { "name": "" } }, "typeVersion": 1 }, { "id": "bf7b8159-dff3-47b1-8d97-c7f6e0e25964", "name": "Crawl every link", "type": "n8n-nodes-scrapeless.scrapeless", "position": [ -1560, 20 ], "parameters": { "url": "={{ $json.link }}", "resource": "crawler", "operation": "crawl", "limitCrawlPages": 1 }, "credentials": { "scrapelessApi": { "name": "" } }, "typeVersion": 1 }, { "id": "c6e18faa-e649-46c4-878e-59a781c45f67", "name": "Check the results correct or not", "type": "n8n-nodes-base.if", "position": [ -440, 20 ], "parameters": { "options": {}, "conditions": { "options": { "version": 2, "leftValue": "", "caseSensitive": true, "typeValidation": "loose" }, "combinator": "and", "conditions": [ { "id": "b1f2df5e-f171-4394-aadd-5085fdc912f6", "operator": { "type": "number", "operation": "gte" }, "leftValue": "={{ $json.lead_score }}", "rightValue": "=6" }, { "id": "f353fe0c-8e12-4b73-a34d-2987158eafca", "operator": { "name": "filter.operator.equals", "type": "string", "operation": "equals" }, "leftValue": "={{ $json.claude_processing_status }}", "rightValue": "SUCCESS" } ] }, "looseTypeValidation": true }, "typeVersion": 2.2 }, { "id": "bed1a04d-035f-42ef-9c41-8dc1c97eb970", "name": "Extract needed info", "type": "n8n-nodes-base.code", "position": [ -1320, 20 ], "parameters": { "mode": "runOnceForEachItem", "jsCode": "// Code pour traiter les donn\u00e9es du Scrapeless Crawler\n// Structure r\u00e9elle: TABLEAU d'objets avec propri\u00e9t\u00e9 \"markdown\"\n\nconsole.log(\"=== PROCESSING SCRAPELESS CRAWLER DATA ===\");\n\ntry {\n // Les donn\u00e9es arrivent sous forme de tableau\n const crawlerDataArray = $json;\n \n console.log(\"Data type:\", typeof crawlerDataArray);\n console.log(\"Is array:\", Array.isArray(crawlerDataArray));\n console.log(\"Array length:\", crawlerDataArray?.length || 0);\n \n // V\u00e9rifier si le tableau est vide\n if (!Array.isArray(crawlerDataArray) || crawlerDataArray.length === 0) {\n console.log(\"\u274c Empty or invalid crawler data\");\n return {\n url: \"unknown\",\n company_name: \"No Data\",\n content: \"\",\n error: \"Empty crawler response\",\n processing_failed: true,\n skip_reason: \"No data returned from crawler\"\n };\n }\n \n // Prendre le premier \u00e9l\u00e9ment du tableau\n const crawlerResponse = crawlerDataArray[0];\n \n // Extraction du contenu markdown\n const markdownContent = crawlerResponse?.markdown || \"\";\n \n // Extraction des m\u00e9tadonn\u00e9es (si disponibles)\n const metadata = crawlerResponse?.metadata || {};\n \n // Informations de base\n const sourceURL = metadata.sourceURL || metadata.url || extractURLFromContent(markdownContent);\n const companyName = metadata.title || metadata.ogTitle || extractCompanyFromContent(markdownContent);\n const description = metadata.description || metadata.ogDescription || \"\";\n \n console.log(`Processing: ${companyName}`);\n console.log(`URL: ${sourceURL}`);\n console.log(`Content length: ${markdownContent.length} characters`);\n \n // V\u00e9rification de la qualit\u00e9 du contenu\n if (!markdownContent || markdownContent.length < 100) {\n return {\n url: sourceURL,\n company_name: companyName,\n content: \"\",\n error: \"Insufficient content from crawler\",\n processing_failed: true,\n raw_content_length: markdownContent.length,\n skip_reason: \"Content too short or empty\"\n };\n }\n \n // Nettoyage et structuration du contenu markdown\n let cleanedContent = cleanMarkdownContent(markdownContent);\n \n // Extraction des informations de contact\n const contactInfo = extractContactInformation(cleanedContent);\n \n // Extraction des sections business importantes\n const businessSections = extractBusinessSections(cleanedContent);\n \n // Construction du contenu pour Claude AI\n const contentForAI = buildContentForAI({\n companyName,\n sourceURL,\n description,\n businessSections,\n contactInfo,\n cleanedContent\n });\n \n // M\u00e9triques de qualit\u00e9 du contenu\n const contentQuality = assessContentQuality(cleanedContent, contactInfo);\n \n const result = {\n url: sourceURL,\n company_name: companyName,\n content: contentForAI,\n raw_content_length: markdownContent.length,\n processed_content_length: contentForAI.length,\n extracted_emails: contactInfo.emails,\n extracted_phones: contactInfo.phones,\n content_quality: contentQuality,\n metadata_info: {\n has_title: !!metadata.title,\n has_description: !!metadata.description,\n site_name: metadata.ogSiteName || \"\",\n page_title: metadata.title || \"\"\n },\n processing_timestamp: new Date().toISOString(),\n processing_status: \"SUCCESS\"\n };\n \n console.log(`\u2705 Successfully processed ${companyName}`);\n return result;\n \n} catch (error) {\n console.error(\"\u274c Error processing crawler data:\", error);\n return {\n url: \"unknown\",\n company_name: \"Processing Error\",\n content: \"\",\n error: error.message,\n processing_failed: true,\n processing_timestamp: new Date().toISOString()\n };\n}\n\n// ========== FONCTIONS UTILITAIRES ==========\n\nfunction extractURLFromContent(content) {\n // Tenter d'extraire l'URL du contenu markdown\n const urlMatch = content.match(/https?:\\/\\/[^\\s\\)]+/);\n return urlMatch ? urlMatch[0] : \"unknown\";\n}\n\nfunction extractCompanyFromContent(content) {\n // Tenter d'extraire le nom de la compagnie du contenu\n const titleMatch = content.match(/^#\\s+(.+)$/m);\n if (titleMatch) return titleMatch[1];\n \n // Rechercher des emails pour extraire le domaine\n const emailMatch = content.match(/@([a-zA-Z0-9.-]+\\.[a-zA-Z]{2,})/);\n if (emailMatch) {\n const domain = emailMatch[1].replace('www.', '');\n return domain.split('.')[0].charAt(0).toUpperCase() + domain.split('.')[0].slice(1);\n }\n \n return \"Unknown Company\";\n}\n\nfunction cleanMarkdownContent(markdown) {\n return markdown\n // Suppression des \u00e9l\u00e9ments de navigation\n .replace(/^\\[Skip to content\\].*$/gmi, '')\n .replace(/^\\[.*\\]\\(#.*\\)$/gmi, '')\n // Suppression des liens markdown mais conservation du texte\n .replace(/\\[([^\\]]+)\\]\\([^)]+\\)/g, '$1')\n // Suppression des images et base64\n .replace(/!\\[([^\\]]*)\\]\\([^)]*\\)/g, '')\n .replace(//g, '')\n // Suppression des mentions de cookies/privacy\n .replace(/.*?(cookie|privacy policy|terms of service).*?\\n/gi, '')\n // Nettoyage des espaces multiples\n .replace(/\\s+/g, ' ')\n // Suppression des lignes vides multiples\n .replace(/\\n\\s*\\n\\s*\\n/g, '\\n\\n')\n .trim();\n}\n\nfunction extractContactInformation(content) {\n // Regex pour emails\n const emailRegex = /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}/g;\n \n // Regex pour t\u00e9l\u00e9phones (avec support international)\n const phoneRegex = /(?:\\+\\d{1,3}\\s?)?\\d{3}\\s?\\d{3}\\s?\\d{3,4}|\\(\\d{3}\\)\\s?\\d{3}-?\\d{4}/g;\n \n const emails = [...new Set((content.match(emailRegex) || [])\n .filter(email => !email.includes('example.com'))\n .slice(0, 3))];\n \n const phones = [...new Set((content.match(phoneRegex) || [])\n .filter(phone => phone.replace(/\\D/g, '').length >= 9)\n .slice(0, 2))];\n \n return { emails, phones };\n}\n\nfunction extractBusinessSections(content) {\n const sections = {};\n \n // Recherche de sections importantes\n const lines = content.split('\\n');\n let currentSection = '';\n let currentContent = '';\n \n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n \n // D\u00e9tection des titres (headers)\n if (line.startsWith('#')) {\n // Sauvegarder la section pr\u00e9c\u00e9dente\n if (currentSection && currentContent) {\n sections[currentSection] = currentContent.trim().substring(0, 500);\n }\n \n // Nouvelle section\n const title = line.replace(/^#+\\s*/, '').toLowerCase();\n if (title.includes('about') || title.includes('service') || \n title.includes('contact') || title.includes('company')) {\n currentSection = title.includes('about') ? 'about' :\n title.includes('service') ? 'services' :\n title.includes('contact') ? 'contact' : 'company';\n currentContent = '';\n } else {\n currentSection = '';\n }\n } else if (currentSection && line) {\n currentContent += line + '\\n';\n }\n }\n \n // Sauvegarder la derni\u00e8re section\n if (currentSection && currentContent) {\n sections[currentSection] = currentContent.trim().substring(0, 500);\n }\n \n return sections;\n}\n\nfunction buildContentForAI({ companyName, sourceURL, description, businessSections, contactInfo, cleanedContent }) {\n let aiContent = `COMPANY ANALYSIS REQUEST\\n\\n`;\n aiContent += `Company: ${companyName}\\n`;\n aiContent += `Website: ${sourceURL}\\n`;\n \n if (description) {\n aiContent += `Description: ${description}\\n`;\n }\n \n aiContent += `\\nCONTACT INFORMATION:\\n`;\n if (contactInfo.emails.length > 0) {\n aiContent += `Emails: ${contactInfo.emails.join(', ')}\\n`;\n }\n if (contactInfo.phones.length > 0) {\n aiContent += `Phones: ${contactInfo.phones.join(', ')}\\n`;\n }\n \n aiContent += `\\nBUSINESS SECTIONS:\\n`;\n for (const [section, content] of Object.entries(businessSections)) {\n if (content) {\n aiContent += `\\n${section.toUpperCase()}:\\n${content}\\n`;\n }\n }\n \n // Ajout du contenu principal (limit\u00e9)\n aiContent += `\\nFULL CONTENT PREVIEW:\\n`;\n aiContent += cleanedContent.substring(0, 2000);\n \n // Limitation finale pour Claude API\n return aiContent.substring(0, 6000);\n}\n\nfunction assessContentQuality(content, contactInfo) {\n const wordCount = content.split(/\\s+/).length;\n \n return {\n word_count: wordCount,\n has_contact_info: contactInfo.emails.length > 0 || contactInfo.phones.length > 0,\n has_about_section: /about|company|who we are/gi.test(content),\n has_services_section: /services|products|solutions/gi.test(content),\n has_team_section: /team|leadership|staff/gi.test(content),\n content_richness_score: Math.min(10, Math.floor(wordCount / 50)),\n email_count: contactInfo.emails.length,\n phone_count: contactInfo.phones.length,\n estimated_quality: wordCount > 200 && contactInfo.emails.length > 0 ? \"HIGH\" : \n wordCount > 100 ? \"MEDIUM\" : \"LOW\"\n };\n}" }, "typeVersion": 2 }, { "id": "423238c5-5438-4362-8fdb-3043a258cac5", "name": "Analyze and Clean the data", "type": "n8n-nodes-base.code", "position": [ -740, 20 ], "parameters": { "mode": "runOnceForEachItem", "jsCode": "// Code pour parser la r\u00e9ponse JSON de Claude AI\nconsole.log(\"=== PARSING CLAUDE AI RESPONSE ===\");\n\ntry {\n // La r\u00e9ponse de Claude arrive dans le champ \"output\"\n const claudeOutput = $json.output || \"\";\n \n console.log(\"Claude output length:\", claudeOutput.length);\n console.log(\"Claude output preview:\", claudeOutput.substring(0, 200));\n \n // Extraction du JSON depuis la r\u00e9ponse markdown de Claude\n let jsonString = claudeOutput;\n \n // Suppression des backticks markdown si pr\u00e9sents\n if (jsonString.includes('```json')) {\n const jsonMatch = jsonString.match(/```json\\s*([\\s\\S]*?)\\s*```/);\n if (jsonMatch && jsonMatch[1]) {\n jsonString = jsonMatch[1].trim();\n }\n } else if (jsonString.includes('```')) {\n // Fallback pour les cas o\u00f9 il n'y a que ```\n const jsonMatch = jsonString.match(/```\\s*([\\s\\S]*?)\\s*```/);\n if (jsonMatch && jsonMatch[1]) {\n jsonString = jsonMatch[1].trim();\n }\n }\n \n // Nettoyage suppl\u00e9mentaire\n jsonString = jsonString.trim();\n \n console.log(\"Extracted JSON string:\", jsonString.substring(0, 300));\n \n // Parse du JSON\n const leadData = JSON.parse(jsonString);\n \n console.log(\"Successfully parsed lead data for:\", leadData.company_name);\n console.log(\"Lead score:\", leadData.lead_score);\n console.log(\"Contact email:\", leadData.contact_email);\n \n // Validation et nettoyage des donn\u00e9es\n const cleanedLead = {\n company_name: leadData.company_name || \"Unknown\",\n industry: leadData.industry || null,\n company_size: leadData.company_size || null,\n location: leadData.location || null,\n contact_email: leadData.contact_email || null,\n phone: leadData.phone || null,\n key_services: Array.isArray(leadData.key_services) ? leadData.key_services : [],\n target_market: leadData.target_market || null,\n technologies: Array.isArray(leadData.technologies) ? leadData.technologies : [],\n funding_stage: leadData.funding_stage || null,\n business_model: leadData.business_model || null,\n social_presence: leadData.social_presence || { linkedin: null, twitter: null },\n lead_score: typeof leadData.lead_score === 'number' ? leadData.lead_score : 0,\n qualification_reasons: Array.isArray(leadData.qualification_reasons) ? leadData.qualification_reasons : [],\n decision_makers: Array.isArray(leadData.decision_makers) ? leadData.decision_makers : [],\n next_actions: Array.isArray(leadData.next_actions) ? leadData.next_actions : [],\n content_insights: leadData.content_insights || {},\n \n // M\u00e9ta-informations pour le filtrage\n is_qualified: leadData.lead_score >= 6 && leadData.contact_email !== null,\n has_contact_info: !!(leadData.contact_email || leadData.phone),\n processing_timestamp: new Date().toISOString(),\n claude_processing_status: \"SUCCESS\"\n };\n \n console.log(`\u2705 Lead processed: ${cleanedLead.company_name} (Score: ${cleanedLead.lead_score}, Qualified: ${cleanedLead.is_qualified})`);\n \n return cleanedLead;\n \n} catch (error) {\n console.error(\"\u274c Error parsing Claude response:\", error);\n console.error(\"Raw output:\", $json.output);\n \n // Retour d'erreur structur\u00e9\n return {\n company_name: \"Claude Parsing Error\",\n industry: null,\n company_size: null,\n location: null,\n contact_email: null,\n phone: null,\n key_services: [],\n target_market: null,\n technologies: [],\n funding_stage: null,\n business_model: null,\n social_presence: { linkedin: null, twitter: null },\n lead_score: 0,\n qualification_reasons: [`Claude parsing failed: ${error.message}`],\n decision_makers: [],\n next_actions: [\"Fix Claude response parsing\", \"Check JSON format\"],\n content_insights: {},\n is_qualified: false,\n has_contact_info: false,\n processing_timestamp: new Date().toISOString(),\n claude_processing_status: \"FAILED\",\n parsing_error: error.message,\n raw_claude_output: $json.output || \"No output received\"\n };\n}" }, "typeVersion": 2 } ], "active": false, "settings": { "executionOrder": "v1" }, "versionId": "c52dc85a-4797-499c-aa17-b9166415530a", "connections": { "AI Agent": { "main": [ [ { "node": "Analyze and Clean the data", "type": "main", "index": 0 } ] ] }, "Split Out": { "main": [ [ { "node": "Crawl every link", "type": "main", "index": 0 } ] ] }, "Crawl every link": { "main": [ [ { "node": "Extract needed info", "type": "main", "index": 0 } ] ] }, "Extract needed info": { "main": [ [ { "node": "AI Agent", "type": "main", "index": 0 } ] ] }, "Anthropic Chat Model": { "ai_languageModel": [ [ { "node": "AI Agent", "type": "ai_languageModel", "index": 0 } ] ] }, "scrape the keywords data": { "main": [ [ { "node": "Split Out", "type": "main", "index": 0 } ] ] }, "Analyze and Clean the data": { "main": [ [ { "node": "Check the results correct or not", "type": "main", "index": 0 } ] ] }, "Check the results correct or not": { "main": [ [ { "node": "HTTP Request", "type": "main", "index": 0 } ] ] }, "When clicking \u2018Execute workflow\u2019": { "main": [ [ { "node": "scrape the keywords data", "type": "main", "index": 0 } ] ] } } }