AI駆動のLinkedInコンタクトレコメンダー
中級
これはLead Generation, Multimodal AI分野の自動化ワークフローで、10個のノードを含みます。主にSet, Code, EmailSend, HttpRequest, EmailReadImapなどのノードを使用。 AIベースのLinkedInコンタクトレコメンダー
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "fnSWZ5XCdbq6snzS",
"meta": {
"instanceId": "dd69efaf8212c74ad206700d104739d3329588a6f3f8381a46a481f34c9cc281",
"templateCredsSetupCompleted": true
},
"name": "AI-Powered LinkedIn Connection Recommender",
"tags": [],
"nodes": [
{
"id": "ef9e2f3b-c06a-484a-8903-2f37b35728f3",
"name": "LinkedIn プロフィールの検索",
"type": "n8n-nodes-base.httpRequest",
"position": [
-600,
4.76293103448279
],
"parameters": {
"url": "https://serpapi.com/search.json",
"options": {},
"sendQuery": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpBasicAuth",
"queryParameters": {
"parameters": [
{
"name": "engine",
"value": "google"
},
{
"name": "q",
"value": "=site:linkedin.com/in \"{{ $json.Position }}\" \"{{ $json.Location }}\" {{ $json.Skills.split(',')[0] }}"
},
{
"name": "api_key",
"value": "="
},
{
"name": "num",
"value": "200"
},
{
"name": "start",
"value": "0"
}
]
}
},
"credentials": {
"httpBasicAuth": {
"id": "SS8MHWya3vb8KVFr",
"name": "temporary cred"
},
"httpQueryAuth": {
"id": "xA2e6hA40RZ8bzrI",
"name": "Query Auth account - test"
}
},
"typeVersion": 4
},
{
"id": "34999f59-ae4b-4ef6-9603-bc5f6b2798d0",
"name": "AIによるプロフィール分析",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
-160,
4.76293103448279
],
"parameters": {
"text": "=You are a LinkedIn networking expert. Analyze the following user profile and potential connections to provide intelligent networking recommendations.\n\nUser Profile:\n- Name: {{ $json.userProfile.name }}\n- Position: {{ $json.userProfile.current_position }}\n- Industry: {{ $json.userProfile.industry }}\n- Location: {{ $json.userProfile.location }}\n- Skills: {{ $json.userProfile.skills }}\n- Interests: {{ $json.userProfile.interests }}\n- Target Roles: {{ $json.userProfile.target_roles }}\n- Preferred Companies: {{ $json.userProfile.company_types }}\n\nPotential Connections Found:\n{{ $json.foundProfiles.map(p => `- ${p.name}: ${p.headline}`).join('\\n') }}\n\nPlease provide a JSON response with the following structure:\n{\n \"scored_profiles\": [\n {\n \"name\": \"Profile Name\",\n \"score\": 8.5,\n \"reasons\": [\"Similar role\", \"Same industry\", \"Skill overlap\"]\n }\n ],\n \"top_connections\": [\n // Top 10 recommended profiles with full details\n ],\n \"connection_strategies\": [\n \"Personalized connection message suggestion for each top profile\"\n ],\n \"networking_insights\": \"Key insights about networking opportunities and industry trends\"\n}\n\nScore profiles from 1-10 based on:\n- Role alignment with user's target positions\n- Industry relevance\n- Skill complementarity\n- Networking value\n- Career growth potential\n\nFocus on quality connections that could provide mutual value.",
"batching": {},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "d8205e9b-e176-477c-a8e7-2f1eb94bc3cb",
"name": "Ollama モデル1",
"type": "@n8n/n8n-nodes-langchain.lmOllama",
"position": [
-72,
224.7629310344828
],
"parameters": {
"model": "llama3.2-16000:latest",
"options": {
"topP": 0.9,
"temperature": 0.7
}
},
"credentials": {
"ollamaApi": {
"id": "7td3WzXCW2wNhraP",
"name": "Ollama - test"
}
},
"typeVersion": 1
},
{
"id": "482f65e9-4075-4d60-8bc8-3c078f8c7acc",
"name": "メールを送信",
"type": "n8n-nodes-base.emailSend",
"position": [
656,
4.76293103448279
],
"webhookId": "46290c2a-08bd-43d7-bb85-112fceaed4b8",
"parameters": {
"text": "={{ $json.body }}",
"options": {},
"subject": "={{ $json.subject }}",
"toEmail": "{{ $json.from }}",
"fromEmail": "abc@gmail.com",
"emailFormat": "text"
},
"credentials": {
"smtp": {
"id": "G1kyF8cSWTZ4vouN",
"name": "SMTP -test"
}
},
"typeVersion": 2.1
},
{
"id": "c759dfb7-9935-41e0-9d38-e41ff48c8b0b",
"name": "メール作成",
"type": "n8n-nodes-base.code",
"position": [
436,
4.76293103448279
],
"parameters": {
"jsCode": "// Get the input data (your JSON)\nconst data = items[0].json;\n\n// Build the email text\nlet emailText = `📊 Networking Report for ${data.user_profile.name}\\n`;\nemailText += `\\nInterests: ${data.user_profile.interests}`;\nemailText += `\\nTarget Industry: ${data.user_profile.target_industry}\\n`;\n\nemailText += `\\nSummary:\\n`;\nemailText += `- Total Profiles Found: ${data.summary.total_profiles_found}\\n`;\nemailText += `- Analyzed Connections: ${data.summary.analyzed_connections}\\n`;\nemailText += `- High Priority: ${data.summary.high_priority}\\n`;\nemailText += `- Medium Priority: ${data.summary.medium_priority}\\n`;\nemailText += `- Average Score: ${data.summary.average_score}\\n`;\n\nemailText += `\\nTop Connection Recommendations:\\n`;\ndata.connection_recommendations.forEach((rec, index) => {\n emailText += `\\n${index + 1}. ${rec.name} (${rec.priority} Priority, Score: ${rec.aiScore})`;\n emailText += `\\n ${rec.description}`;\n emailText += `\\n Mutual Connections: ${rec.mutual_connections}`;\n emailText += `\\n Reason: ${rec.connectionReason}`;\n emailText += `\\n Suggested Message: \"${rec.suggestedMessage}\"\\n`;\n});\n\nemailText += `\\nNext Steps:\\n`;\ndata.next_steps.forEach((step, i) => {\n emailText += `- ${step}\\n`;\n});\n\nemailText += `\\nAI Insights:\\n${data.ai_insights}\\n`;\n\nemailText += `\\nBest Networking Times:\\nDays: ${data.networking_strategy.best_days.join(\", \")}\\nTimes: ${data.networking_strategy.best_times.join(\", \")}\\n`;\n\nreturn [{\n json: {\n subject: `Networking Report - ${data.user_profile.name}`,\n body: emailText\n }\n}];\n"
},
"typeVersion": 2
},
{
"id": "7e27272d-1c4e-4e15-b7be-f0ef85937c13",
"name": "あなたのプロフィール情報",
"type": "n8n-nodes-base.set",
"position": [
-820,
4.76293103448279
],
"parameters": {
"fields": {
"values": [
{
"name": "Name"
},
{
"name": "Position"
},
{
"name": "Industry"
},
{
"name": "Location"
},
{
"name": "Skills"
},
{
"name": "Interests"
},
{
"name": "Target Roles"
},
{
"name": "Company Types"
}
]
},
"options": {}
},
"typeVersion": 3
},
{
"id": "a9d1762a-aaf2-45a5-a5fc-381ec2d174c5",
"name": "LinkedIn の検索結果を処理",
"type": "n8n-nodes-base.code",
"position": [
-380,
4.76293103448279
],
"parameters": {
"jsCode": "// Process search results and extract LinkedIn profiles\nconst results = $json.organic_results || [];\n\n// Get user profile from the previous node\nconst userProfile = $input.first().json || {};\n\n// Filter and process LinkedIn profiles\nconst linkedinProfiles = results\n .filter(result => {\n const link = result.link || '';\n return link.includes('linkedin.com/in/') && \n !link.includes('/posts/') && \n !link.includes('/activity/');\n })\n .map(result => {\n let name = result.title || 'Unknown';\n // Clean up the title to extract just the name\n name = name.replace(/\\s*[-|]\\s*LinkedIn.*$/i, '').trim();\n \n return {\n name: name,\n headline: result.snippet || result.title || '',\n link: result.link,\n description: result.snippet || '',\n source: 'Google Search via SerpAPI'\n };\n })\n .slice(0, 15); // Limit to top 15 results\n\n// Safely extract skills - handle undefined/null values\nconst getFirstSkill = (skills) => {\n if (!skills || typeof skills !== 'string') {\n return '';\n }\n const skillsArray = skills.split(',');\n return skillsArray.length > 0 ? skillsArray[0].trim() : '';\n};\n\n// Build search query with safe property access\nconst buildSearchQuery = () => {\n const position = userProfile.Position || '';\n const location = userProfile.Location || '';\n const firstSkill = getFirstSkill(userProfile.Skills);\n \n return `site:linkedin.com/in \"${position}\" \"${location}\" ${firstSkill}`.trim();\n};\n\n// Return structured data for AI analysis\nreturn {\n json: {\n userProfile: {\n name: $('Your Profile Information').first().json.Name || '',\n current_position: $('Your Profile Information').first().json.Position || '',\n industry: $('Your Profile Information').first().json.Industry || '',\n location: $('Your Profile Information').first().json.Location|| '',\n skills: $('Your Profile Information').first().json.Skills|| '',\n interests: $('Your Profile Information').first().json.Interests || '',\n target_roles: $('Your Profile Information').first().json['Target Roles']|| '',\n company_types: $('Your Profile Information').first().json['Company Types'] || ''\n },\n foundProfiles: linkedinProfiles,\n totalFound: linkedinProfiles.length,\n searchQuery: buildSearchQuery()\n }\n};"
},
"typeVersion": 2,
"alwaysOutputData": true
},
{
"id": "808cb1fa-9970-4d0e-8d34-37eea340fdb4",
"name": "最終推薦を作成",
"type": "n8n-nodes-base.code",
"position": [
216,
4.76293103448279
],
"parameters": {
"jsCode": "// Process AI recommendations and create final output\nconst inputData = $input.first();\nconst inputText = inputData.json?.text || inputData.json || inputData;\n\nlet aiRecommendations = {};\ntry {\n // Extract JSON from the text content\n const content = typeof inputText === 'string' ? inputText : JSON.stringify(inputText);\n \n // Try to parse JSON from the AI response\n const jsonMatch = content.match(/```json\\n([\\s\\S]*?)\\n```/) || content.match(/\\{[\\s\\S]*\\}/);\n if (jsonMatch) {\n const jsonString = jsonMatch[1] || jsonMatch[0];\n aiRecommendations = JSON.parse(jsonString);\n } else {\n throw new Error('No JSON found in response');\n }\n} catch (error) {\n console.log('Could not parse AI response:', error.message);\n console.log('Input data:', inputData);\n \n // Create fallback recommendations if parsing fails\n aiRecommendations = {\n scored_profiles: [],\n top_connections: [],\n connection_strategies: [],\n networking_insights: 'Focus on building meaningful professional relationships in your industry.'\n };\n}\n\n// Helper function to safely split and get first element\nfunction safeGetFirst(str, delimiter = ',') {\n if (!str || typeof str !== 'string') return '';\n const parts = str.split(delimiter);\n return parts.length > 0 ? parts[0].trim() : '';\n}\n\n// Helper function to safely split string\nfunction safeSplit(str, delimiter = ',') {\n if (!str || typeof str !== 'string') return [];\n return str.split(delimiter).map(item => item.trim()).filter(item => item);\n}\n\n// Helper function to generate connection message\nfunction generateConnectionMessage(profile, index) {\n if (!profile || !profile.name) return 'Hi! I\\'d love to connect and share professional insights.';\n \n const firstName = safeGetFirst(profile.name, ' ');\n const description = profile.description || '';\n \n // Create personalized messages based on profile\n if (description.toLowerCase().includes('devops')) {\n return `Hi ${firstName}, I'm interested in DevOps and cloud technologies. I'd love to connect and learn from your experience!`;\n } else if (description.toLowerCase().includes('aws') || description.toLowerCase().includes('cloud')) {\n return `Hi ${firstName}, I noticed your expertise in cloud computing. Would love to connect and share insights about the industry!`;\n } else {\n return `Hi ${firstName}, I'd love to connect with a fellow professional and learn from your experience in the industry.`;\n }\n}\n\n// Helper function to extract tags from description\nfunction extractTags(description) {\n if (!description) return ['Professional Contact'];\n \n const tags = [];\n const descText = description.toLowerCase();\n \n // Add technology tags\n const techs = ['aws', 'azure', 'gcp', 'devops', 'terraform', 'ansible', 'jenkins', 'kubernetes', 'docker'];\n techs.forEach(tech => {\n if (descText.includes(tech)) {\n tags.push(tech.toUpperCase());\n }\n });\n \n // Add role tags\n if (descText.includes('senior') || descText.includes('lead')) {\n tags.push('Senior Level');\n }\n \n if (descText.includes('mentor') || descText.includes('enthusiast')) {\n tags.push('Mentor');\n }\n \n return tags.length > 0 ? tags : ['Professional Contact'];\n}\n\n// Process the connections from AI recommendations\nconst connections = aiRecommendations.top_connections || [];\nconst scoredProfiles = aiRecommendations.scored_profiles || [];\n\nconst enhancedConnections = connections.map((profile, index) => {\n // Find matching score data\n const scoreData = scoredProfiles.find(p => \n p.name && profile.name && \n p.name.toLowerCase().trim() === profile.name.toLowerCase().trim()\n );\n \n const score = scoreData?.score || (9.5 - index * 0.3); // Fallback scoring\n \n return {\n name: profile.name || 'Unknown',\n description: profile.description || '',\n connections: profile.connections || 0,\n mutual_connections: profile.mutual_connections || 0,\n priority: score >= 8.5 ? 'High' : score >= 7.5 ? 'Medium' : 'Low',\n aiScore: score,\n connectionReason: scoreData?.reasons?.join(', ') || 'Professional networking opportunity',\n suggestedMessage: generateConnectionMessage(profile, index),\n tags: extractTags(profile.description),\n estimatedResponseRate: score >= 8.5 ? 'High (70-90%)' : score >= 7.5 ? 'Medium (40-70%)' : 'Low (20-40%)',\n link: profile.link || '#'\n };\n}).sort((a, b) => b.aiScore - a.aiScore); // Sort by AI score\n\n// Create individual connection strategies\nconst connectionStrategies = enhancedConnections.map(conn => {\n const firstName = safeGetFirst(conn.name, ' ');\n return `${firstName}: ${conn.suggestedMessage.replace(`Hi ${firstName}, `, '')}`;\n});\n\nreturn {\n json: {\n summary: {\n total_profiles_found: scoredProfiles.length,\n analyzed_connections: enhancedConnections.length,\n high_priority: enhancedConnections.filter(c => c.priority === 'High').length,\n medium_priority: enhancedConnections.filter(c => c.priority === 'Medium').length,\n low_priority: enhancedConnections.filter(c => c.priority === 'Low').length,\n average_score: enhancedConnections.length > 0 ? \n (enhancedConnections.reduce((sum, c) => sum + c.aiScore, 0) / enhancedConnections.length).toFixed(1) : 0\n },\n user_profile: {\n name: \"Vrushti Sukhadiya\", // Extracted from the analysis text\n interests: \"DevOps, Cloud Computing, Automation\",\n target_industry: \"IT, Tech Startups, Cloud Companies\"\n },\n connection_recommendations: enhancedConnections,\n connection_strategies: connectionStrategies,\n ai_insights: aiRecommendations.networking_insights || 'Focus on building meaningful professional relationships in your industry.',\n networking_strategy: {\n weekly_goal: '5-10 new connections',\n best_days: ['Tuesday', 'Wednesday', 'Thursday'],\n best_times: ['9-11 AM', '2-4 PM'],\n follow_up_schedule: 'Within 48 hours of connection acceptance',\n focus_areas: ['DevOps professionals', 'Cloud Computing experts', 'AI/ML enthusiasts']\n },\n next_steps: [\n 'Start with highest-scored profiles (Mihir Suthar - 9.5, Muneeswaran M - 9.2)',\n 'Check for mutual connections before reaching out',\n 'Engage with their recent posts about DevOps/Cloud topics',\n 'Send personalized connection requests highlighting common interests',\n 'Follow up with thoughtful messages about industry trends',\n 'Consider attending DevOps/Cloud computing events where they might be present'\n ],\n top_recommendations: enhancedConnections.slice(0, 3).map(conn => ({\n name: conn.name,\n why_connect: conn.connectionReason,\n action_item: `Connect with ${safeGetFirst(conn.name, ' ')} focusing on ${conn.tags.slice(0, 2).join(' and ')} expertise`\n }))\n }\n};"
},
"typeVersion": 2
},
{
"id": "e1b30786-455f-414f-9577-36634a0c1cd9",
"name": "メールからユーザーデータを取得",
"type": "n8n-nodes-base.emailReadImap",
"position": [
-1040,
4.76293103448279
],
"parameters": {
"options": {}
},
"credentials": {
"imap": {
"id": "zTEGYssr7MSVeCs3",
"name": "IMAP-test"
}
},
"typeVersion": 2
},
{
"id": "02259afc-6178-49f4-b08c-82dc7667bd06",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
-940,
-420
],
"parameters": {
"width": 680,
"height": 340,
"content": "## System Architecture\n- **Profile Analysis Pipeline**:\n - **Get User Data from Email**: Initiates with manual user input.\n - **Your Profile Information**: Provides initial data.\n - **Search LinkedIn Profiles**: Fetches profile data via API.\n - **Process LinkedIn Search Results**: Extracts relevant information.\n- **AI Recommendation Flow**:\n - **AI Profile Analysis**: Analyzes data with AI.\n - **Create Recommendations**: Generates initial connection list.\n - **Create Final Recommendations**: Refines the list.\n- **Delivery Flow**:\n - **Create Email**: Prepares the email content.\n - **Send Email**: Sends the curated list to the user."
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "9073190a-946e-4f57-998d-365de4ec3ae8",
"connections": {
"c759dfb7-9935-41e0-9d38-e41ff48c8b0b": {
"main": [
[
{
"node": "482f65e9-4075-4d60-8bc8-3c078f8c7acc",
"type": "main",
"index": 0
}
]
]
},
"d8205e9b-e176-477c-a8e7-2f1eb94bc3cb": {
"ai_languageModel": [
[
{
"node": "34999f59-ae4b-4ef6-9603-bc5f6b2798d0",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"34999f59-ae4b-4ef6-9603-bc5f6b2798d0": {
"main": [
[
{
"node": "808cb1fa-9970-4d0e-8d34-37eea340fdb4",
"type": "main",
"index": 0
}
]
]
},
"ef9e2f3b-c06a-484a-8903-2f37b35728f3": {
"main": [
[
{
"node": "a9d1762a-aaf2-45a5-a5fc-381ec2d174c5",
"type": "main",
"index": 0
}
]
]
},
"7e27272d-1c4e-4e15-b7be-f0ef85937c13": {
"main": [
[
{
"node": "ef9e2f3b-c06a-484a-8903-2f37b35728f3",
"type": "main",
"index": 0
}
]
]
},
"e1b30786-455f-414f-9577-36634a0c1cd9": {
"main": [
[
{
"node": "7e27272d-1c4e-4e15-b7be-f0ef85937c13",
"type": "main",
"index": 0
}
]
]
},
"808cb1fa-9970-4d0e-8d34-37eea340fdb4": {
"main": [
[
{
"node": "c759dfb7-9935-41e0-9d38-e41ff48c8b0b",
"type": "main",
"index": 0
}
]
]
},
"a9d1762a-aaf2-45a5-a5fc-381ec2d174c5": {
"main": [
[
{
"node": "34999f59-ae4b-4ef6-9603-bc5f6b2798d0",
"type": "main",
"index": 0
}
]
]
}
}
}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
中級 - リード獲得, マルチモーダルAI
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
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ワークフロー情報
難易度
中級
ノード数10
カテゴリー2
ノードタイプ8
作成者
Oneclick AI Squad
@oneclick-aiThe AI Squad Initiative is a pioneering effort to build, automate and scale AI-powered workflows using n8n.io. Our mission is to help individuals and businesses integrate AI agents seamlessly into their daily operations from automating tasks and enhancing productivity to creating innovative, intelligent solutions. We design modular, reusable AI workflow templates that empower creators, developers and teams to supercharge their automation with minimal effort and maximum impact.
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