// n8n Function Node - Lead Scoring Engine
const leadData = $input.first().json;
 
// Scoring configuration
const scoringModel = {
  demographic: {
    weight: 0.30,
    factors: {
      company_size: {
        'enterprise': 100,
        'mid_market': 80,
        'small_business': 60,
        'startup': 40,
        'unknown': 20
      },
      industry: {
        'technology': 100,
        'finance': 95,
        'healthcare': 90,
        'manufacturing': 85,
        'retail': 75,
        'other': 50
      },
      job_title: {
        patterns: [
          { regex: /^(c-level|ceo|cto|cfo|coo|cmo)/i, score: 100 },
          { regex: /^(vp|vice president|director)/i, score: 90 },
          { regex: /^(head|senior manager|manager)/i, score: 75 },
          { regex: /^(senior|lead|principal)/i, score: 60 },
          { regex: /.+/, score: 40 }
        ]
      },
      location: {
        'tier1_markets': 100,
        'tier2_markets': 80,
        'tier3_markets': 60,
        'other': 40
      }
    }
  },
  behavioral: {
    weight: 0.40,
    factors: {
      page_views: {
        '20+': 100,
        '10-19': 80,
        '5-9': 60,
        '1-4': 40,
        '0': 0
      },
      pricing_page_visits: {
        '3+': 100,
        '2': 80,
        '1': 50,
        '0': 0
      },
      content_downloads: {
        '5+': 100,
        '3-4': 80,
        '1-2': 50,
        '0': 0
      },
      demo_requests: {
        'yes': 100,
        'no': 0
      },
      email_engagement: {
        'high': 100,
        'medium': 60,
        'low': 30,
        'none': 0
      }
    }
  },
  engagement: {
    weight: 0.20,
    factors: {
      email_opens: {
        '10+': 100,
        '5-9': 80,
        '1-4': 50,
        '0': 0
      },
      email_clicks: {
        '5+': 100,
        '2-4': 70,
        '1': 40,
        '0': 0
      },
      webinar_attendance: {
        'attended_live': 100,
        'watched_recording': 70,
        'registered_no_show': 30,
        'none': 0
      },
      social_engagement: {
        'high': 100,
        'medium': 60,
        'low': 30,
        'none': 0
      }
    }
  },
  intent: {
    weight: 0.10,
    factors: {
      recency: {
        '24_hours': 100,
        '7_days': 80,
        '30_days': 50,
        '90_days': 20,
        'older': 0
      },
      frequency: {
        'daily': 100,
        'weekly': 70,
        'monthly': 40,
        'rarely': 10
      }
    }
  }
};
 
// Calculate demographic score
function calculateDemographicScore(lead) {
  let score = 0;
  const factors = scoringModel.demographic.factors;
 
  // Company size
  const sizeScore = factors.company_size[lead.company_size] || factors.company_size['unknown'];
  score += sizeScore * 0.25;
 
  // Industry
  const industryScore = factors.industry[lead.industry] || factors.industry['other'];
  score += industryScore * 0.25;
 
  // Job title
  const titlePatterns = factors.job_title.patterns;
  let titleScore = 40; // default
  for (const pattern of titlePatterns) {
    if (pattern.regex.test(lead.job_title || '')) {
      titleScore = pattern.score;
      break;
    }
  }
  score += titleScore * 0.30;
 
  // Location
  const locationTier = determineLocationTier(lead.country, lead.state);
  const locationScore = factors.location[locationTier] || factors.location['other'];
  score += locationScore * 0.20;
 
  return score;
}
 
// Calculate behavioral score
function calculateBehavioralScore(lead) {
  let score = 0;
  const factors = scoringModel.behavioral.factors;
  const behavior = lead.behavior || {};
 
  // Page views
  const pageViews = behavior.page_views || 0;
  const pvScore = pageViews >= 20 ? 100 : pageViews >= 10 ? 80 : pageViews >= 5 ? 60 : pageViews >= 1 ? 40 : 0;
  score += pvScore * 0.20;
 
  // Pricing page visits
  const pricingVisits = behavior.pricing_page_visits || 0;
  const ppScore = pricingVisits >= 3 ? 100 : pricingVisits === 2 ? 80 : pricingVisits === 1 ? 50 : 0;
  score += ppScore * 0.25;
 
  // Content downloads
  const downloads = behavior.content_downloads || 0;
  const dlScore = downloads >= 5 ? 100 : downloads >= 3 ? 80 : downloads >= 1 ? 50 : 0;
  score += dlScore * 0.20;
 
  // Demo request
  const demoScore = behavior.demo_requested ? 100 : 0;
  score += demoScore * 0.25;
 
  // Email engagement
  const emailEngagement = behavior.email_engagement || 'none';
  const emailScore = factors.email_engagement[emailEngagement] || 0;
  score += emailScore * 0.10;
 
  return score;
}
 
// Calculate engagement score
function calculateEngagementScore(lead) {
  let score = 0;
  const engagement = lead.engagement || {};
 
  // Email opens
  const opens = engagement.email_opens || 0;
  const openScore = opens >= 10 ? 100 : opens >= 5 ? 80 : opens >= 1 ? 50 : 0;
  score += openScore * 0.25;
 
  // Email clicks
  const clicks = engagement.email_clicks || 0;
  const clickScore = clicks >= 5 ? 100 : clicks >= 2 ? 70 : clicks >= 1 ? 40 : 0;
  score += clickScore * 0.30;
 
  // Webinar attendance
  const webinarStatus = engagement.webinar_status || 'none';
  const webinarScore = scoringModel.engagement.factors.webinar_attendance[webinarStatus] || 0;
  score += webinarScore * 0.25;
 
  // Social engagement
  const socialEngagement = engagement.social_engagement || 'none';
  const socialScore = scoringModel.engagement.factors.social_engagement[socialEngagement] || 0;
  score += socialScore * 0.20;
 
  return score;
}
 
// Calculate intent score
function calculateIntentScore(lead) {
  let score = 0;
  const intent = lead.intent || {};
 
  // Recency
  const lastActivityDate = new Date(intent.last_activity || 0);
  const daysSinceActivity = Math.floor((Date.now() - lastActivityDate) / (1000 * 60 * 60 * 24));
 
  let recencyScore = 0;
  if (daysSinceActivity <= 1) recencyScore = 100;
  else if (daysSinceActivity <= 7) recencyScore = 80;
  else if (daysSinceActivity <= 30) recencyScore = 50;
  else if (daysSinceActivity <= 90) recencyScore = 20;
  score += recencyScore * 0.50;
 
  // Frequency
  const visitFrequency = intent.visit_frequency || 'rarely';
  const freqScore = scoringModel.intent.factors.frequency[visitFrequency] || 10;
  score += freqScore * 0.50;
 
  return score;
}
 
function determineLocationTier(country, state) {
  const tier1 = ['US', 'GB', 'CA', 'AU', 'DE'];
  const tier2 = ['FR', 'NL', 'SE', 'NO', 'DK', 'CH', 'JP'];
 
  if (tier1.includes(country)) return 'tier1_markets';
  if (tier2.includes(country)) return 'tier2_markets';
  return 'tier3_markets';
}
 
// Calculate all scores
const demographicScore = calculateDemographicScore(leadData);
const behavioralScore = calculateBehavioralScore(leadData);
const engagementScore = calculateEngagementScore(leadData);
const intentScore = calculateIntentScore(leadData);
 
// Calculate weighted total
const totalScore = Math.round(
  demographicScore * scoringModel.demographic.weight +
  behavioralScore * scoringModel.behavioral.weight +
  engagementScore * scoringModel.engagement.weight +
  intentScore * scoringModel.intent.weight
);
 
// Determine lead grade
function determineGrade(score) {
  if (score >= 80) return 'A';
  if (score >= 60) return 'B';
  if (score >= 40) return 'C';
  if (score >= 20) return 'D';
  return 'F';
}
 
// Determine MQL/SQL status
function determineQualificationStatus(score, grade, lead) {
  // SQL criteria
  if (score >= 75 && lead.behavior?.demo_requested) {
    return 'SQL';
  }
  if (score >= 80) {
    return 'SQL';
  }
 
  // MQL criteria
  if (score >= 50 && grade <= 'B') {
    return 'MQL';
  }
  if (score >= 40 && lead.behavior?.pricing_page_visits >= 2) {
    return 'MQL';
  }
 
  return 'Lead';
}
 
const grade = determineGrade(totalScore);
const qualification = determineQualificationStatus(totalScore, grade, leadData);
 
// Build scoring result
const scoringResult = {
  lead_id: leadData.id,
  email: leadData.email,
  scores: {
    demographic: Math.round(demographicScore),
    behavioral: Math.round(behavioralScore),
    engagement: Math.round(engagementScore),
    intent: Math.round(intentScore),
    total: totalScore
  },
  grade: grade,
  qualification_status: qualification,
  score_breakdown: {
    demographic_factors: {
      company_size: leadData.company_size,
      industry: leadData.industry,
      job_title: leadData.job_title,
      location: leadData.country
    },
    behavioral_factors: {
      page_views: leadData.behavior?.page_views || 0,
      pricing_visits: leadData.behavior?.pricing_page_visits || 0,
      downloads: leadData.behavior?.content_downloads || 0,
      demo_requested: leadData.behavior?.demo_requested || false
    }
  },
  scored_at: new Date().toISOString(),
  previous_score: leadData.previous_score || null,
  score_change: leadData.previous_score ? totalScore - leadData.previous_score : null
};
 
return { json: scoringResult };

// n8n Function Node - Real-Time Score Updater
const event = $input.first().json;
const currentScores = $('Get Lead Scores').first()?.json || {};
 
// Event scoring adjustments
const eventScoreAdjustments = {
  // Website events
  'page_view': 1,
  'pricing_page_view': 5,
  'product_page_view': 3,
  'case_study_view': 4,
  'blog_post_view': 1,
 
  // Content events
  'ebook_download': 10,
  'whitepaper_download': 12,
  'checklist_download': 8,
  'webinar_registration': 15,
  'webinar_attendance': 20,
 
  // Form submissions
  'demo_request': 30,
  'contact_form': 25,
  'pricing_request': 28,
  'trial_signup': 35,
 
  // Email events
  'email_open': 2,
  'email_click': 5,
  'email_reply': 15,
  'unsubscribe': -20,
 
  // Negative events
  'bounce': -10,
  'spam_complaint': -50,
  'inactive_30_days': -15,
  'inactive_60_days': -25,
  'inactive_90_days': -40
};
 
// Calculate score adjustment
const eventType = event.event_type;
const adjustment = eventScoreAdjustments[eventType] || 0;
 
// Apply decay for old scores
function applyScoreDecay(currentScore, lastActivityDate) {
  const daysSinceActivity = Math.floor(
    (Date.now() - new Date(lastActivityDate).getTime()) / (1000 * 60 * 60 * 24)
  );
 
  // Apply 2% decay per inactive week
  const weeksInactive = Math.floor(daysSinceActivity / 7);
  const decayMultiplier = Math.pow(0.98, weeksInactive);
 
  return Math.round(currentScore * decayMultiplier);
}
 
// Calculate new score
let newBehavioralScore = currentScores.behavioral || 0;
 
// Apply event adjustment
newBehavioralScore += adjustment;
 
// Apply decay if needed
if (event.event_type.includes('inactive')) {
  newBehavioralScore = applyScoreDecay(
    newBehavioralScore,
    currentScores.last_activity_date
  );
}
 
// Ensure score stays within bounds
newBehavioralScore = Math.max(0, Math.min(100, newBehavioralScore));
 
// Check for threshold crossings
const thresholds = {
  mql: 50,
  sql: 75,
  hot_lead: 85
};
 
const previousTotal = currentScores.total || 0;
const newTotal = Math.round(
  currentScores.demographic * 0.30 +
  newBehavioralScore * 0.40 +
  currentScores.engagement * 0.20 +
  currentScores.intent * 0.10
);
 
const thresholdsCrossed = [];
for (const [name, threshold] of Object.entries(thresholds)) {
  if (previousTotal < threshold && newTotal >= threshold) {
    thresholdsCrossed.push({ threshold: name, direction: 'up' });
  } else if (previousTotal >= threshold && newTotal < threshold) {
    thresholdsCrossed.push({ threshold: name, direction: 'down' });
  }
}
 
// Determine actions based on score change
const actions = [];
 
if (thresholdsCrossed.some(t => t.threshold === 'sql' && t.direction === 'up')) {
  actions.push({
    type: 'notify_sales',
    priority: 'high',
    message: `Lead ${event.lead_id} is now SQL (score: ${newTotal})`
  });
  actions.push({
    type: 'create_task',
    assignee: 'sales_round_robin',
    task: `Follow up with SQL: ${event.lead_email}`
  });
}
 
if (thresholdsCrossed.some(t => t.threshold === 'mql' && t.direction === 'up')) {
  actions.push({
    type: 'add_to_nurture',
    campaign: 'mql_nurture',
    message: 'Added to MQL nurture sequence'
  });
}
 
if (thresholdsCrossed.some(t => t.threshold === 'hot_lead' && t.direction === 'up')) {
  actions.push({
    type: 'notify_sales',
    priority: 'urgent',
    message: `Hot lead alert! ${event.lead_id} score: ${newTotal}`
  });
}
 
return {
  json: {
    lead_id: event.lead_id,
    event: eventType,
    score_adjustment: adjustment,
    scores: {
      previous: {
        behavioral: currentScores.behavioral,
        total: previousTotal
      },
      current: {
        behavioral: newBehavioralScore,
        total: newTotal
      }
    },
    thresholds_crossed: thresholdsCrossed,
    actions: actions,
    updated_at: new Date().toISOString()
  }
};

// n8n Function Node - Lead Router
const scoredLead = $input.first().json;
const salesTeam = $('Get Sales Team').all().map(i => i.json);
 
// Routing rules configuration
const routingRules = {
  enterprise: {
    condition: (lead) => lead.company_size === 'enterprise' || lead.scores.total >= 85,
    team: 'enterprise_sales',
    sla_minutes: 15
  },
  mid_market: {
    condition: (lead) => lead.company_size === 'mid_market' || lead.scores.total >= 70,
    team: 'mid_market_sales',
    sla_minutes: 30
  },
  smb: {
    condition: (lead) => true, // Default
    team: 'smb_sales',
    sla_minutes: 60
  }
};
 
// Industry-specific routing
const industryRouting = {
  'healthcare': 'healthcare_specialist',
  'finance': 'financial_services_specialist',
  'technology': 'tech_specialist'
};
 
// Geographic routing
const geoRouting = {
  'US': { 'CA': 'west_coast_team', 'NY': 'east_coast_team' },
  'GB': 'emea_team',
  'DE': 'emea_team',
  'JP': 'apac_team',
  'AU': 'apac_team'
};
 
function determineRoute(lead) {
  // Determine segment
  let segment = 'smb';
  for (const [seg, rule] of Object.entries(routingRules)) {
    if (rule.condition(lead)) {
      segment = seg;
      break;
    }
  }
 
  // Check for specialist routing
  let specialist = null;
  if (industryRouting[lead.industry]) {
    specialist = industryRouting[lead.industry];
  }
 
  // Check geographic routing
  let geoTeam = null;
  if (geoRouting[lead.country]) {
    if (typeof geoRouting[lead.country] === 'object') {
      geoTeam = geoRouting[lead.country][lead.state] || null;
    } else {
      geoTeam = geoRouting[lead.country];
    }
  }
 
  return {
    segment,
    team: routingRules[segment].team,
    specialist,
    geo_team: geoTeam,
    sla_minutes: routingRules[segment].sla_minutes
  };
}
 
function selectSalesRep(team, availableReps) {
  // Filter by team and availability
  const teamReps = availableReps.filter(rep =>
    rep.team === team && rep.is_available && rep.current_leads < rep.max_leads
  );
 
  if (teamReps.length === 0) {
    // Fall back to any available rep
    const anyAvailable = availableReps.filter(rep =>
      rep.is_available && rep.current_leads < rep.max_leads
    );
    if (anyAvailable.length === 0) return null;
    return anyAvailable.sort((a, b) => a.current_leads - b.current_leads)[0];
  }
 
  // Round-robin with load balancing
  return teamReps.sort((a, b) => {
    // Prioritize by current load
    const loadDiff = a.current_leads - b.current_leads;
    if (loadDiff !== 0) return loadDiff;
 
    // Then by last assignment time
    return new Date(a.last_assigned) - new Date(b.last_assigned);
  })[0];
}
 
const route = determineRoute(scoredLead);
const assignedRep = selectSalesRep(route.team, salesTeam);
 
const routingResult = {
  lead_id: scoredLead.lead_id,
  routing: {
    segment: route.segment,
    team: route.team,
    specialist_required: route.specialist,
    geographic_team: route.geo_team,
    sla_minutes: route.sla_minutes,
    sla_deadline: new Date(Date.now() + route.sla_minutes * 60 * 1000).toISOString()
  },
  assignment: assignedRep ? {
    rep_id: assignedRep.id,
    rep_name: assignedRep.name,
    rep_email: assignedRep.email,
    assigned_at: new Date().toISOString()
  } : null,
  fallback_required: !assignedRep,
  lead_score: scoredLead.scores.total,
  lead_grade: scoredLead.grade,
  qualification: scoredLead.qualification_status
};
 
return { json: routingResult };

// n8n Function Node - CRM Sync
const routingResult = $input.first().json;
const scoredLead = $('Lead Scoring').first().json;
 
// Build CRM update payload
function buildCRMPayload(lead, routing) {
  return {
    // Contact fields
    contact: {
      id: lead.lead_id,
      email: lead.email,
      custom_fields: {
        lead_score: lead.scores.total,
        lead_grade: lead.grade,
        demographic_score: lead.scores.demographic,
        behavioral_score: lead.scores.behavioral,
        engagement_score: lead.scores.engagement,
        intent_score: lead.scores.intent,
        last_scored_at: new Date().toISOString()
      }
    },
 
    // Lead stage update
    lifecycle: {
      stage: mapQualificationToStage(lead.qualification_status),
      status: 'active',
      score: lead.scores.total
    },
 
    // Owner assignment
    assignment: routing.assignment ? {
      owner_id: routing.assignment.rep_id,
      assigned_at: routing.assignment.assigned_at,
      assignment_reason: `Auto-routed: ${routing.routing.segment} segment`
    } : null,
 
    // Task creation
    task: routing.assignment ? {
      title: `Follow up with ${lead.qualification_status}: ${lead.email}`,
      description: buildTaskDescription(lead, routing),
      due_date: routing.routing.sla_deadline,
      priority: lead.scores.total >= 80 ? 'high' : 'normal',
      assignee_id: routing.assignment.rep_id,
      type: 'follow_up'
    } : null,
 
    // Activity log
    activity: {
      type: 'score_update',
      timestamp: new Date().toISOString(),
      details: {
        previous_score: lead.previous_score,
        new_score: lead.scores.total,
        score_change: lead.score_change,
        triggered_by: 'automated_scoring'
      }
    }
  };
}
 
function mapQualificationToStage(qualification) {
  const mapping = {
    'Lead': 'new_lead',
    'MQL': 'marketing_qualified',
    'SQL': 'sales_qualified',
    'Opportunity': 'opportunity'
  };
  return mapping[qualification] || 'new_lead';
}
 
function buildTaskDescription(lead, routing) {
  return `
## Lead Overview
- **Score**: ${lead.scores.total} (Grade: ${lead.grade})
- **Status**: ${lead.qualification_status}
- **Segment**: ${routing.routing.segment}
 
## Score Breakdown
- Demographic: ${lead.scores.demographic}/100
- Behavioral: ${lead.scores.behavioral}/100
- Engagement: ${lead.scores.engagement}/100
- Intent: ${lead.scores.intent}/100
 
## Key Signals
${lead.score_breakdown.behavioral_factors.demo_requested ? '- ✅ Requested demo\n' : ''}
${lead.score_breakdown.behavioral_factors.pricing_visits > 0 ? `- 👀 Visited pricing page ${lead.score_breakdown.behavioral_factors.pricing_visits} times\n` : ''}
${lead.score_breakdown.behavioral_factors.downloads > 0 ? `- 📥 Downloaded ${lead.score_breakdown.behavioral_factors.downloads} resources\n` : ''}
 
## SLA
- **Deadline**: ${routing.routing.sla_deadline}
- **Time allowed**: ${routing.routing.sla_minutes} minutes
  `.trim();
}
 
const crmPayload = buildCRMPayload(scoredLead, routingResult);
 
// Build notification for sales rep
const notification = routingResult.assignment ? {
  type: 'new_lead_assignment',
  recipient: routingResult.assignment.rep_email,
  subject: `New ${scoredLead.qualification_status} Assigned: ${scoredLead.email}`,
  body: {
    lead_email: scoredLead.email,
    score: scoredLead.scores.total,
    grade: scoredLead.grade,
    sla_deadline: routingResult.routing.sla_deadline,
    quick_view_url: `${process.env.CRM_URL}/leads/${scoredLead.lead_id}`
  },
  channel: scoredLead.scores.total >= 80 ? 'slack_dm' : 'email'
} : null;
 
return {
  json: {
    crm_payload: crmPayload,
    notification: notification,
    metadata: {
      lead_id: scoredLead.lead_id,
      processed_at: new Date().toISOString()
    }
  }
};

// n8n Function Node - Scoring Analytics
const allLeads = $input.all().map(i => i.json);
 
// Calculate scoring metrics
const metrics = {
  total_leads: allLeads.length,
  by_grade: { A: 0, B: 0, C: 0, D: 0, F: 0 },
  by_qualification: { Lead: 0, MQL: 0, SQL: 0 },
  score_distribution: [],
  conversion_rates: {},
  average_scores: {
    demographic: 0,
    behavioral: 0,
    engagement: 0,
    intent: 0,
    total: 0
  }
};
 
// Aggregate metrics
for (const lead of allLeads) {
  metrics.by_grade[lead.grade] = (metrics.by_grade[lead.grade] || 0) + 1;
  metrics.by_qualification[lead.qualification_status] = (metrics.by_qualification[lead.qualification_status] || 0) + 1;
 
  metrics.average_scores.demographic += lead.scores.demographic;
  metrics.average_scores.behavioral += lead.scores.behavioral;
  metrics.average_scores.engagement += lead.scores.engagement;
  metrics.average_scores.intent += lead.scores.intent;
  metrics.average_scores.total += lead.scores.total;
}
 
// Calculate averages
const count = allLeads.length || 1;
for (const key in metrics.average_scores) {
  metrics.average_scores[key] = Math.round(metrics.average_scores[key] / count);
}
 
// Score distribution buckets
const buckets = [
  { min: 0, max: 20, label: '0-20' },
  { min: 21, max: 40, label: '21-40' },
  { min: 41, max: 60, label: '41-60' },
  { min: 61, max: 80, label: '61-80' },
  { min: 81, max: 100, label: '81-100' }
];
 
for (const bucket of buckets) {
  const count = allLeads.filter(l =>
    l.scores.total >= bucket.min && l.scores.total <= bucket.max
  ).length;
  metrics.score_distribution.push({
    range: bucket.label,
    count,
    percentage: Math.round((count / allLeads.length) * 100)
  });
}
 
// Calculate conversion rates (would need historical data)
metrics.conversion_rates = {
  mql_to_sql: 0.35, // Placeholder
  sql_to_opportunity: 0.45,
  opportunity_to_won: 0.25
};
 
// Build report
const report = {
  generated_at: new Date().toISOString(),
  period: 'last_30_days',
  metrics,
  insights: generateInsights(metrics),
  recommendations: generateRecommendations(metrics)
};
 
function generateInsights(metrics) {
  const insights = [];
 
  const aGradePercent = (metrics.by_grade.A / metrics.total_leads) * 100;
  if (aGradePercent < 10) {
    insights.push({
      type: 'warning',
      message: `Only ${aGradePercent.toFixed(1)}% of leads are A-grade. Consider reviewing acquisition channels.`
    });
  }
 
  const avgScore = metrics.average_scores.total;
  if (avgScore < 40) {
    insights.push({
      type: 'info',
      message: `Average lead score is ${avgScore}. Focus on lead quality improvement.`
    });
  }
 
  return insights;
}
 
function generateRecommendations(metrics) {
  const recommendations = [];
 
  if (metrics.average_scores.behavioral < 40) {
    recommendations.push({
      area: 'engagement',
      recommendation: 'Implement more interactive content to boost behavioral scores'
    });
  }
 
  if (metrics.by_qualification.MQL > metrics.by_qualification.SQL * 3) {
    recommendations.push({
      area: 'conversion',
      recommendation: 'Review MQL to SQL conversion - consider adjusting thresholds or nurture campaigns'
    });
  }
 
  return recommendations;
}
 
return { json: report };