Enrichir et qualifier des leads avec l'IA

• •Compte Google et informations d'identification Gmail API
• •Token Bot Slack ou URL Webhook
• •Clé API HubSpot
• •Point de terminaison HTTP Webhook (généré automatiquement par n8n)
• •Peut nécessiter les informations d'identification d'authentification de l'API cible
• •Clé API Anthropic

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  "name": "Enrich and score leads with AI",
  "tags": [],
  "nodes": [
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      "name": "Enrichissement PDL",
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      "parameters": {
        "url": "https://api.peopledatalabs.com/v5/person/enrich",
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        "sendQuery": true,
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
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      "parameters": {
        "options": {},
        "messages": {
          "message": [
            {
              "content": "=Research {{ $json.data.full_name }} at {{ $json.data.job_company_name }} for B2B sales context.\n\nFocus on:\n1. Recent career moves or promotions (last 6 months)\n2. Professional achievements and thought leadership\n3. Speaking engagements or publications\n4. Relevant timing signals for outreach\n\nProvide ONLY actionable insights for sales in under 150 words.\n\nFormat:\nRECENT ACTIVITY: [Key recent developments]\nEXPERTISE: [Professional focus areas]\nOUTREACH ANGLE: [Best conversation starter]\nTIMING: [High/Medium/Low urgency]"
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      "parameters": {
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          "message": [
            {
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      "id": "13eb8525-4863-4b36-8291-1dc811314255",
      "name": "Fusionner les données d'enrichissement",
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      "position": [
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        "jsCode": "const inputs = $input.all();\n\nconst enrichedData = {\n  contact: {\n    email: null,\n    name: null\n  },\n  enrichment: {\n    pdl: {},\n    individual: {},\n    company: {},\n    linkedin: {}\n  },\n  metadata: {\n    enrichmentTimestamp: new Date().toISOString(),\n    sourcesSuccessful: [],\n    sourcesFailed: []\n  }\n};\n\ninputs.forEach((input, index) => {\n  const data = input.json;\n  \n  if (index === 0 && data.choices && data.choices[0] && data.choices[0].message && data.choices[0].message.content) {\n    const content = data.choices[0].message.content;\n    enrichedData.enrichment.individual = {\n      rawResearch: content,\n      recentActivity: extractSection(content, 'RECENT ACTIVITY'),\n      expertise: extractSection(content, 'EXPERTISE'),\n      outreachAngle: extractSection(content, 'OUTREACH ANGLE'),\n      timing: extractSection(content, 'TIMING')\n    };\n    enrichedData.metadata.sourcesSuccessful.push('Individual Research');\n  }\n  \n  else if (index === 1 && data && !data.error) {\n    const pdl = data.data || data;\n    enrichedData.enrichment.pdl = {\n      fullName: pdl.full_name,\n      jobTitle: pdl.job_title,\n      companyName: pdl.job_company_name,\n      companySize: pdl.job_company_size,\n      industry: pdl.job_company_industry,\n      seniorityLevel: pdl.job_title_levels,\n      linkedinUrl: pdl.linkedin_url,\n      location: pdl.location_name,\n      skills: pdl.skills\n    };\n    enrichedData.contact.name = pdl.full_name;\n    enrichedData.metadata.sourcesSuccessful.push('PDL');\n  }\n  \n  else if (index === 2 && data.choices && data.choices[0] && data.choices[0].message && data.choices[0].message.content) {\n    const content = data.choices[0].message.content;\n    enrichedData.enrichment.company = {\n      rawResearch: content,\n      developments: extractSection(content, 'RECENT DEVELOPMENTS'),\n      buyingSignals: extractSection(content, 'BUYING SIGNALS'),\n      companyHealth: extractSection(content, 'COMPANY HEALTH'),\n      priority: extractSection(content, 'PRIORITY')\n    };\n    enrichedData.metadata.sourcesSuccessful.push('Company Research');\n  }\n  \n  else if (index === 3 && data && Array.isArray(data) && data.length > 0) {\n    const profile = data[0];\n    enrichedData.enrichment.linkedin = {\n      headline: profile.headline,\n      summary: profile.summary,\n      recentPosts: profile.posts ? profile.posts.slice(0, 5) : [],\n      connectionsCount: profile.connectionsCount,\n      postsAnalyzed: true\n    };\n    enrichedData.metadata.sourcesSuccessful.push('LinkedIn');\n  }\n  \n  else if (index === 4 && data.validationPassed) {\n    enrichedData.contact.email = data.email;\n    enrichedData.contact.domain = data.domain;\n    enrichedData.contact.isFreeEmail = data.isFreeEmail;\n  }\n});\n\nconst qualityScore = calculateQuality(enrichedData);\nenrichedData.metadata.dataQualityScore = qualityScore;\n\nfunction extractSection(text, header) {\n  const pattern = header + ': ';\n  const startIdx = text.indexOf(pattern);\n  if (startIdx === -1) return 'N/A';\n  const afterHeader = text.substring(startIdx + pattern.length);\n  const endIdx = afterHeader.search(/\\n[A-Z]/);\n  return endIdx === -1 ? afterHeader.trim() : afterHeader.substring(0, endIdx).trim();\n}\n\nfunction calculateQuality(data) {\n  let score = 0;\n  if (data.enrichment.pdl.fullName) score += 25;\n  if (data.enrichment.individual.recentActivity !== 'N/A') score += 25;\n  if (data.enrichment.company.developments !== 'N/A') score += 25;\n  if (data.enrichment.linkedin.postsAnalyzed) score += 25;\n  return score;\n}\n\nreturn [{ json: enrichedData }];"
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        "jsCode": "const raw = $input.first().json.output;\n\nlet scoring;\ntry {\n  let cleaned = raw.replace(/```json\\n?|```\\n?/g, '').trim();\n  cleaned = cleaned.replace(/,(\\s*[}\\]])/g, '$1');\n  scoring = JSON.parse(cleaned);\n  \n} catch (err) {\n  const extract = (field) => {\n    const regex = new RegExp('\"' + field + '\":\\\\s*\"([^\"]*(?:\\\\\\\\.[^\"]*)*)\"', 's');\n    const match = raw.match(regex);\n    return match ? match[1].replace(/\\\\n/g, '\\n').replace(/\\\\\"/g, '\"') : null;\n  };\n  \n  const extractArray = (field) => {\n    const regex = new RegExp('\"' + field + '\":\\\\s*\\\\[([^\\\\]]+)\\\\]', 's');\n    const match = raw.match(regex);\n    if (!match) return [];\n    return match[1].split(',').map(s => s.trim().replace(/^\"|\"$/g, ''));\n  };\n  \n  const extractNumber = (field) => {\n    const regex = new RegExp('\"' + field + '\":\\\\s*(\\\\d+)');\n    const match = raw.match(regex);\n    return match ? parseInt(match[1]) : 0;\n  };\n  \n  const extractObject = (field) => {\n    const regex = new RegExp('\"' + field + '\":\\\\s*({[^}]+})');\n    const match = raw.match(regex);\n    if (!match) return {};\n    try {\n      return JSON.parse(match[1]);\n    } catch {\n      return {};\n    }\n  };\n  \n  scoring = {\n    email: extract('email'),\n    name: extract('name'),\n    title: extract('title'),\n    companyName: extract('companyName'),\n    companySize: extract('companySize'),\n    industry: extract('industry'),\n    seniorityLevel: extractArray('seniorityLevel'),\n    linkedinUrl: extract('linkedinUrl'),\n    individualResearch: extract('individualResearch'),\n    companyResearch: extract('companyResearch'),\n    dataQualityScore: extractNumber('dataQualityScore'),\n    leadScore: extractNumber('leadScore'),\n    scoreBreakdown: extractObject('scoreBreakdown'),\n    icpMatch: extractObject('icpMatch'),\n    keyInsights: extractArray('keyInsights'),\n    outreachRecommendation: extract('outreachRecommendation'),\n    conversationStarters: extractArray('conversationStarters'),\n    timingOpportunities: extractArray('timingOpportunities'),\n    redFlags: extractArray('redFlags'),\n    nextAction: extract('nextAction'),\n    confidenceLevel: extract('confidenceLevel'),\n    routingCategory: extract('routingCategory')\n  };\n}\n\nconst finalLead = {\n  email: scoring.email,\n  name: scoring.name,\n  title: scoring.title,\n  companyName: scoring.companyName,\n  companySize: scoring.companySize,\n  industry: scoring.industry,\n  seniorityLevel: scoring.seniorityLevel,\n  linkedinUrl: scoring.linkedinUrl,\n  individualResearch: scoring.individualResearch,\n  companyResearch: scoring.companyResearch,\n  dataQualityScore: scoring.dataQualityScore,\n  leadScore: scoring.leadScore,\n  scoreBreakdown: scoring.scoreBreakdown,\n  scoreReasoning: scoring.leadScore + '/10 - ' + Object.entries(scoring.scoreBreakdown || {}).map(function(pair) { return pair[0] + ': ' + pair[1]; }).join(', '),\n  icpMatch: scoring.icpMatch,\n  companySizeMatch: scoring.icpMatch ? scoring.icpMatch.companySizeMatch : null,\n  industryMatch: scoring.icpMatch ? scoring.icpMatch.industryMatch : null,\n  titleMatch: scoring.icpMatch ? scoring.icpMatch.titleMatch : null,\n  keyInsights: scoring.keyInsights || [],\n  outreachRecommendation: scoring.outreachRecommendation,\n  conversationStarters: scoring.conversationStarters || [],\n  timingOpportunities: scoring.timingOpportunities || [],\n  redFlags: scoring.redFlags || [],\n  nextAction: scoring.nextAction,\n  confidenceLevel: scoring.confidenceLevel,\n  routingCategory: scoring.routingCategory,\n  processedAt: new Date().toISOString()\n};\n\nreturn [{ json: finalLead }];"
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      "name": "Router par score",
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      "parameters": {
        "rules": {
          "values": [
            {
              "outputKey": "Hot Lead",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
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                    "id": "99013e96-7d32-48fc-907d-d524c3cfb81d",
                    "operator": {
                      "type": "number",
                      "operation": "gte"
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                    "rightValue": 8
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "Warm Lead",
              "conditions": {
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                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
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                    "operator": {
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                      "operation": "gte"
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                    "leftValue": "={{ $json.leadScore }}",
                    "rightValue": 5
                  },
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                    "operator": {
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                      "operation": "lt"
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                    "leftValue": "={{ $json.leadScore }}",
                    "rightValue": 8
                  }
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              },
              "renameOutput": true
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            {
              "outputKey": "Cold Lead",
              "conditions": {
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                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
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          "cachedResultName": "all-connors-personal-slack"
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      },
      "typeVersion": 2
    },
    {
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      "type": "n8n-nodes-base.gmail",
      "position": [
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      "webhookId": "e733042b-2ce4-45c1-805d-e956a4593d07",
      "parameters": {
        "sendTo": "={{ $json.to }}",
        "message": "={{ $json.body }}",
        "options": {
          "appendAttribution": false
        },
        "subject": "={{ $json.subject }}"
      },
      "credentials": {
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      },
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    },
    {
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      "name": "Envoyer prospect tiède vers digest",
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      ],
      "webhookId": "68ba787c-94c7-4833-ba59-3d03ac6510bc",
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          "mode": "list",
          "value": "C096FHNCPUM",
          "cachedResultName": "all-connors-personal-slack"
        },
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        "authentication": "oAuth2"
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      "credentials": {
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          "name": "Slack account"
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      },
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    },
    {
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      "name": "Formatter pour CRM",
      "type": "n8n-nodes-base.code",
      "position": [
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        672
      ],
      "parameters": {
        "jsCode": "const lead = $json;\n\nreturn [{\n  json: {\n    email: lead.email,\n    firstname: lead.name ? lead.name.split(' ')[0] : null,\n    lastname: lead.name ? lead.name.split(' ').slice(1).join(' ') : null,\n    jobtitle: lead.title,\n    company: lead.companyName,\n    linkedin_url: lead.linkedinUrl,\n    lead_score: lead.leadScore,\n    lead_score_reasoning: lead.scoreReasoning,\n    routing_category: lead.routingCategory,\n    icp_company_size_match: lead.companySizeMatch,\n    icp_industry_match: lead.industryMatch,\n    icp_title_match: lead.titleMatch,\n    key_insights: lead.keyInsights ? lead.keyInsights.join(' | ') : null,\n    conversation_starters: lead.conversationStarters ? lead.conversationStarters.join(' | ') : null,\n    timing_opportunities: lead.timingOpportunities ? lead.timingOpportunities.join(' | ') : null,\n    outreach_recommendation: lead.outreachRecommendation,\n    red_flags: lead.redFlags ? lead.redFlags.join(' | ') : null,\n    individual_research_summary: lead.individualResearch,\n    company_research_summary: lead.companyResearch,\n    data_quality_score: lead.dataQualityScore,\n    enrichment_sources: lead.sourcesUsed ? lead.sourcesUsed.join(', ') : null,\n    last_enrichment_date: lead.processedAt,\n    lifecyclestage: lead.routingCategory === 'hot' ? 'salesqualifiedlead' : 'lead',\n    hs_lead_status: lead.routingCategory === 'hot' ? 'OPEN' : 'NEW'\n  }\n}];"
      },
      "typeVersion": 2
    },
    {
      "id": "aca601b2-b493-4682-919a-88e0bd4f404f",
      "name": "Upsert vers CRM HubSpot",
      "type": "n8n-nodes-base.hubspot",
      "notes": "Enable after configuring HubSpot credentials",
      "position": [
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        672
      ],
      "parameters": {
        "email": "={{ $json.email }}",
        "options": {},
        "additionalFields": {
          "customPropertiesUi": {
            "customPropertiesValues": [
              {
                "value": "={{ $json.firstname }}",
                "property": "firstname"
              },
              {
                "value": "={{ $json.lastname }}",
                "property": "lastname"
              },
              {
                "value": "={{ $json.jobtitle }}",
                "property": "jobtitle"
              },
              {
                "value": "={{ $json.company }}",
                "property": "company"
              },
              {
                "value": "={{ $json.lead_score }}",
                "property": "lead_score"
              },
              {
                "value": "={{ $json.lifecyclestage }}",
                "property": "lifecyclestage"
              }
            ]
          }
        }
      },
      "typeVersion": 2
    },
    {
      "id": "c87419fe-28ab-45cf-89c3-b9f9d9de3efd",
      "name": "Agent IA",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        384,
        416
      ],
      "parameters": {
        "text": "=You are a B2B lead scoring AI with access to ICP rules stored in a Google Doc.\n\nCRITICAL FIRST STEP: Use the available Google Docs tool to fetch the ICP scoring rules document before analyzing the lead.\n\nLead Data:\n{{ JSON.stringify($json, null, 2) }}\n\nSCORING PROCESS:\n1. Fetch ICP rules from the doc\n2. Score each component (0-3 for company, 0-3 for title, 0-2 for signals, 0-2 for timing) based on the rules\n3. CRITICAL: Calculate leadScore by ADDING the four breakdown scores together\n   leadScore equals companyFit plus titleFit plus buyingSignals plus timing\n4. Determine routing category based on total score:\n   - 8-10 equals hot\n   - 5-7 equals warm  \n   - 0-4 equals cold\n\nSCORING RULES:\n- Company Fit (0-3): Compare company size, industry, and geography against ICP criteria in doc\n- Title Fit (0-3): Match persona title against ICP persona tiers in doc\n- Buying Signals (0-2): Count strong/medium signals from research data\n- Timing (0-2): Assess urgency based on recent changes and signals\n\nReturn ONLY valid JSON (no markdown, no code blocks) with these fields: email, name, title, companyName, companySize, industry, seniorityLevel, linkedinUrl, individualResearch, companyResearch, dataQualityScore, leadScore (sum of breakdown scores), scoreBreakdown object with companyFit/titleFit/buyingSignals/timing, icpMatch object with companySizeMatch/industryMatch/titleMatch booleans, keyInsights array, outreachRecommendation string, conversationStarters array, timingOpportunities array, redFlags array, nextAction string, confidenceLevel string, routingCategory string based on score thresholds above.",
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        "promptType": "define"
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      "typeVersion": 2.2
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    {
      "id": "cbf742e7-a18e-47e8-85e2-6537abe0b4f9",
      "name": "Modèle de chat Anthropic",
      "type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
      "position": [
        384,
        608
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "claude-sonnet-4-20250514",
          "cachedResultName": "Claude 4 Sonnet"
        },
        "options": {}
      },
      "credentials": {
        "anthropicApi": {
          "id": "JEgF1ooDsuHYBKx5",
          "name": "Anthropic account"
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      },
      "typeVersion": 1.3
    },
    {
      "id": "9c9f0f0f-b6a3-4f72-88e5-760ab64305d3",
      "name": "Formatter Slack prospect chaud",
      "type": "@n8n/n8n-nodes-langchain.googleGemini",
      "position": [
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        144
      ],
      "parameters": {
        "modelId": {
          "__rl": true,
          "mode": "list",
          "value": "models/gemini-2.5-flash",
          "cachedResultName": "models/gemini-2.5-flash"
        },
        "options": {},
        "messages": {
          "values": [
            {
              "content": "=Create a concise Slack alert for a HOT LEAD that requires immediate sales attention.\n\nLead Data:\n{{ JSON.stringify($json, null, 2) }}\n\nUsing the data above, create a Slack message in mrkdwn format with this structure:\n\nHOT LEAD ALERT\n\n[name] | [title] at [companyName]\nScore: [leadScore]/10 | [confidenceLevel] confidence\n[email]\n\nKey Insights:\n- [First 3-4 items from keyInsights array as bullets]\n\nWhy This Matters:\n[Pull from timingOpportunities - 1-2 sentences on urgency]\n\nRecommended Approach:\n[outreachRecommendation - keep concise]\n\nConversation Starters:\n- [First 2 from conversationStarters array]\n\nNote: [First redFlag if exists]\n\nNext Action: [nextAction]\n\nKeep it under 300 words and extremely scannable. Use actual values from the JSON data."
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          ]
        }
      },
      "credentials": {
        "googlePalmApi": {
          "id": "d8ipU9ibs2OJxC51",
          "name": "Google Gemini(PaLM) Api account"
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      },
      "typeVersion": 1
    },
    {
      "id": "4de89a82-f720-4ee6-88f5-fa35006e4f29",
      "name": "Formatter email prospect chaud",
      "type": "@n8n/n8n-nodes-langchain.googleGemini",
      "position": [
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          "mode": "list",
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          "cachedResultName": "models/gemini-2.5-flash"
        },
        "options": {},
        "messages": {
          "values": [
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              "content": "=Create a personalized welcome email for a HOT LEAD.\n\nLead Data:\n{{ JSON.stringify($json, null, 2) }}\n\nRequirements:\n- Warm, professional tone\n- Reference 1-2 relevant insights naturally\n- Clear value proposition for their role/company\n- Soft CTA (calendar link or reply)\n- 100-150 words max\n- Feel human-written, not templated\n\nReturn JSON (include the email from the input) with fields: email (extract from input data), subject (engaging subject line), body (email body with paragraph tags, not HTML angle brackets)."
            }
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        }
      },
      "credentials": {
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          "name": "Google Gemini(PaLM) Api account"
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    {
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      "name": "Formatter Slack prospect tiède",
      "type": "@n8n/n8n-nodes-langchain.googleGemini",
      "position": [
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          "cachedResultName": "models/gemini-2.5-flash"
        },
        "options": {},
        "messages": {
          "values": [
            {
              "content": "=Create a Slack digest entry for a WARM LEAD.\n\nLead Data:\n{{ JSON.stringify($json, null, 2) }}\n\nUsing the data above, create a message:\n\n[name] | [title] at [companyName]\nScore: [leadScore]/10\n\nQuick Context:\n- [2-3 items from keyInsights]\n\nNext Steps: [nextAction]\n\nKeep it under 150 words. Use actual values from the JSON."
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      "name": "Webhook",
      "type": "n8n-nodes-base.webhook",
      "position": [
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      "webhookId": "1d670952-c57f-4985-980a-b740fc9a5f6c",
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        "path": "lead-intake",
        "options": {},
        "httpMethod": "POST"
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      "typeVersion": 2.1
    },
    {
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      "name": "Profile Scraper LinkedIn",
      "type": "@apify/n8n-nodes-apify.apify",
      "position": [
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        560
      ],
      "parameters": {
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        "actorId": {
          "__rl": true,
          "mode": "url",
          "value": "https://console.apify.com/actors/LQQIXN9Othf8f7R5n/input"
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        "timeout": {},
        "operation": "Run actor",
        "customBody": "={ \"username\": \"{{ $json.data.profiles[0].url }}\" }",
        "actorSource": "store",
        "waitForFinish": 60,
        "authentication": "apifyOAuth2Api"
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      "credentials": {
        "apifyOAuth2Api": {
          "id": "k2EtiqJb7kjmtjRn",
          "name": "Apify account"
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      "typeVersion": 1,
      "continueOnFail": true
    },
    {
      "id": "cca5c728-3ee5-4192-91e3-33ba69630dc9",
      "name": "ICP et cas d'usage",
      "type": "n8n-nodes-base.googleDocsTool",
      "position": [
        528,
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      ],
      "parameters": {
        "operation": "get",
        "documentURL": "https://docs.google.com/document/d/YOUR_DOCUMENT_ID/edit"
      },
      "credentials": {
        "googleDocsOAuth2Api": {
          "id": "UxwVvTjaY2WY3bMb",
          "name": "Google Docs account"
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      },
      "typeVersion": 2
    },
    {
      "id": "6d3fcf37-6aa7-45c5-ae0f-49666579be13",
      "name": "Note adhésive1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        176,
        -144
      ],
      "parameters": {
        "color": 4,
        "width": 704,
        "height": 528,
        "content": "## Enrich and score leads with AI\n\nThis workflow automates lead qualification by enriching email addresses with firmographic data from People Data Labs, researching individuals and companies using Perplexity AI, scoring leads against your ICP criteria with Claude, and routing them to appropriate channels.\n\n### What it does:\n- Hot leads (8-10 score) get instant Slack alerts with personalized email drafts\n- Warm leads (5-7) go to a digest channel\n- Cold leads (0-4) log to your CRM only\n- Processing takes 30-60 seconds per lead versus 20 minutes manual research\n- Cost per lead: $0.08-0.15\n\n### Setup required:\n1. Configure webhook path (default: lead-intake)\n2. Add credentials for: PDL, Perplexity, Claude, Slack, Gmail, Google Docs\n3. Create ICP rules Google Doc and update URL in ICP & Use Case node\n4. Optional: Add Apify and HubSpot credentials\n\n### How to use:\nSend POST to webhook with: {\"email\": \"lead@company.com\", \"name\": \"Optional Name\"}"
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    },
    {
      "id": "f951f6b2-cae8-4287-bccc-3bcb8090287e",
      "name": "Note adhésive2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -656,
        256
      ],
      "parameters": {
        "width": 176,
        "height": 112,
        "content": "**Setup Required:**\nCreate Header Auth credential with:\n- Name: X-Api-Key\n- Value: Your PDL API key\n\nAlternative: Use Apollo or Clearbit"
      },
      "typeVersion": 1
    },
    {
      "id": "d3d0ab31-2b0c-40aa-8ecf-c1c3207482c8",
      "name": "Note adhésive3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      "parameters": {
        "content": "**Optional:**\nGet API key from:\nhttps://apify.com/curious_coder/linkedin-profile-scraper\n\nAdd OAuth2 credentials"
      },
      "typeVersion": 1
    },
    {
      "id": "45baaf4f-6afa-4e21-b04e-b05d091f6e7d",
      "name": "Note adhésive4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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        768
      ],
      "parameters": {
        "width": 150,
        "height": 144,
        "content": "**Setup Required:**\nReplace documentURL with your ICP rules Google Doc URL\n\nAdd OAuth2 credentials"
      },
      "typeVersion": 1
    },
    {
      "id": "684eb148-af5f-404c-9307-d8bfe705afa6",
      "name": "Note adhésive5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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        656
      ],
      "parameters": {
        "width": 150,
        "height": 196,
        "content": "**Optional:**\nEnable node and add credentials for:\n- HubSpot\n- Salesforce\n- Pipedrive\n- Or custom CRM"
      },
      "typeVersion": 1
    },
    {
      "id": "21a65fe2-b9ad-4b52-ac4d-590edabd0a3f",
      "name": "Raisonnement IA",
      "type": "@n8n/n8n-nodes-langchain.toolThink",
      "position": [
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      "typeVersion": 1.1
    }
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