Monitoring Performance

Monitoring Performance

Set up comprehensive monitoring to track flow health, identify issues early, and optimize performance. Learn metrics, alerting, dashboards, and continuous improvement strategies.

📍 You Are Here

Your flows are running, but you need visibility into their performance. This guide shows you how to monitor effectively, set up alerts, and continuously optimize your lead operations.

🎯 What You'll Learn

• Key performance indicators
• Real-time monitoring setup
• Alert configuration
• Dashboard creation
• Performance optimization
• Trend analysis

📊 Key Performance Indicators

Volume Metrics

Track lead flow:

• Leads per hour/day/month
• Source distribution
• Peak vs off-peak patterns
• Growth trends

// Calculate hourly rate
hourly_rate = leads_last_hour.count
daily_projection = hourly_rate * 24

// Check if normal
if (hourly_rate < historical_average * 0.5) {
  alert("Volume significantly below normal")
}

Quality Metrics

Monitor lead quality:

• Acceptance rate (% passing criteria)
• Validation pass rate (email, phone)
• Duplicate rate
• Enhancement success rate

// Quality score calculation
quality_score = (
  (valid_emails / total) * 0.3 +
  (valid_phones / total) * 0.3 +
  (non_duplicates / total) * 0.2 +
  (enhanced_data / total) * 0.2
) * 100

Performance Metrics

System performance:

• Average processing time
• Step duration breakdown
• API response times
• Queue depth

Business Metrics

Bottom line impact:

• Cost per lead
• Revenue per lead
• ROI by source
• Conversion rates (with feedback)

🚨 Setting Up Alerts

Critical Alerts

Immediate attention needed:

Flow Stopped:

Alert: Flow Processing Stopped
Condition: leads_last_15_min = 0 AND expected > 0
Action: Email + SMS to on-call
Priority: Critical

High Failure Rate:

Alert: High Rejection Rate
Condition: failure_rate > 50% for 10 minutes
Action: Email team, pause source
Priority: High

API Errors:

Alert: Integration Failing
Condition: API_errors > 10 in 5 minutes
Action: Email, create ticket
Priority: High

Warning Alerts

Attention needed soon:

Volume Changes:

Alert: Volume Drop
Condition: current_volume < average * 0.7
Duration: 30 minutes
Action: Email notification
Priority: Medium

Quality Degradation:

Alert: Quality Declining
Condition: quality_score < 80%
Duration: 1 hour
Action: Email report
Priority: Medium

Informational Alerts

Good to know:

Daily Summary:

Alert: Daily Performance Report
Schedule: Daily at 9 AM
Content: Volume, quality, cost metrics
Action: Email to team
Priority: Low

📈 Real-Time Dashboards

Executive Dashboard

High-level business view:

┌─────────────────────────────────────────┐
│         EXECUTIVE DASHBOARD             │
├─────────────────┬───────────────────────┤
│ Today's Leads   │ 12,456 ↑ 15%        │
│ Acceptance Rate │ 89.3% ↓ 2.1%        │
│ Total Cost      │ $18,684              │
│ Projected Rev   │ $124,560             │
│ ROI             │ 567% ↑ 12%          │
└─────────────────┴───────────────────────┘

Top Sources          Quality    Volume
1. Google Ads         95.2%     4,521
2. Facebook           91.8%     3,892
3. Partner Network    87.4%     2,156

Operations Dashboard

Detailed operational view:

┌─────────────────────────────────────────┐
│       OPERATIONS DASHBOARD              │
├─────────────────────────────────────────┤
│ Processing Time:  324ms avg            │
│ Queue Depth:      12 leads             │
│ Active Flows:     8/10                 │
│                                        │
│ Errors (Last Hour):                    │
│ - Email validation: 3                  │
│ - CRM timeout: 1                       │
│ - Phone service: 0                     │
│                                        │
│ [Processing Graph - Real-time]         │
└─────────────────────────────────────────┘

Source Performance Dashboard

Vendor management view:

Source: ABC Marketing
├─ Volume: 1,234 leads today
├─ Quality Score: 91.2%
├─ Duplicate Rate: 3.4%
├─ Cost per Lead: $12.50
├─ Rejection Reasons:
│  - Invalid phone: 45 (3.6%)
│  - Duplicate: 42 (3.4%)
│  - Bad email: 23 (1.9%)
└─ Trend: ↑ Improving

🔍 Deep Dive Analysis

Hourly Patterns

Identify optimal times:

// Analyze by hour
hourly_analysis = leads
  .groupBy(lead => new Date(lead.created).getHours())
  .map(hour => ({
    hour: hour.key,
    volume: hour.length,
    quality: hour.filter(l => l.valid).length / hour.length,
    conversion: hour.filter(l => l.converted).length / hour.length
  }))

// Find best hours
best_hours = hourly_analysis
  .sort((a, b) => b.conversion - a.conversion)
  .slice(0, 3)

Source Comparison

Compare vendor performance:

source_metrics = sources.map(source => ({
  name: source.name,
  volume: getVolume(source),
  quality: getQualityScore(source),
  cost: getTotalCost(source),
  revenue: getProjectedRevenue(source),
  roi: (revenue - cost) / cost * 100
}))

// Rank by ROI
ranked_sources = source_metrics
  .sort((a, b) => b.roi - a.roi)

Error Analysis

Understand failure patterns:

error_analysis = failed_leads
  .groupBy(lead => lead.failure_reason)
  .map(reason => ({
    reason: reason.key,
    count: reason.length,
    percentage: reason.length / total_leads * 100,
    sources: [...new Set(reason.map(l => l.source))],
    trend: calculateTrend(reason.key, last_period)
  }))
  .sort((a, b) => b.count - a.count)

🎯 Performance Optimization

Identify Bottlenecks

Find slow steps:

// Average time per step
step_performance = events
  .flatMap(e => e.steps)
  .groupBy(s => s.name)
  .map(step => ({
    name: step.key,
    avg_time: average(step.map(s => s.duration)),
    max_time: Math.max(...step.map(s => s.duration)),
    count: step.length
  }))
  .sort((a, b) => b.avg_time - a.avg_time)

// Steps taking > 1 second
slow_steps = step_performance
  .filter(s => s.avg_time > 1000)

Optimize Slow Steps

Common optimizations:

Reorder Steps:

// Before: Slow enhancement first
1. Data Enhancement (2s)
2. Email Check (0.1s)
3. Delivery (0.5s)
Total: 2.6s

// After: Fast filter first
1. Email Check (0.1s)
2. Data Enhancement (2s) - only if email valid
3. Delivery (0.5s)
Total: 0.6s for invalid, 2.6s for valid

Add Caching:

// Cache enhancement results
if (cache.has(phone)) {
  result = cache.get(phone)
} else {
  result = await enhance(phone)
  cache.set(phone, result, ttl: 3600)
}

📊 Trend Analysis

Daily Trends

Track patterns over time:

// 30-day rolling average
daily_trends = past_30_days.map(day => ({
  date: day,
  volume: getVolume(day),
  quality: getQuality(day),
  moving_avg: getMovingAverage(day, 7)
}))

// Detect anomalies
anomalies = daily_trends.filter(day => 
  Math.abs(day.volume - day.moving_avg) > day.moving_avg * 0.3
)

Seasonal Patterns

Understand cycles:

// Day of week analysis
dow_pattern = leads
  .groupBy(l => new Date(l.created).getDay())
  .map(day => ({
    day: ['Sun','Mon','Tue','Wed','Thu','Fri','Sat'][day.key],
    avg_volume: average(day.volumes),
    avg_quality: average(day.qualities)
  }))

// Monthly patterns
monthly_pattern = leads
  .groupBy(l => new Date(l.created).getMonth())
  .map(month => ({
    month: month.key,
    characteristics: analyzeMonth(month)
  }))

🔧 Monitoring Tools

Built-in Tools

LeadConduit provides:

• Real-time flow statistics
• Event browser
• Basic reports
• Email alerts

External Integration

Connect to monitoring platforms:

Datadog:

// Send metrics
datadog.gauge('leadconduit.acceptance_rate', acceptance_rate, tags)
datadog.increment('leadconduit.leads_processed', 1, tags)

New Relic:

// Track transactions
newrelic.startSegment('lead_processing', true, () => {
  // Process lead
  newrelic.addCustomAttribute('source', lead.source)
  newrelic.addCustomAttribute('outcome', outcome)
})

Custom Webhooks:

// Send to monitoring endpoint
webhook.send({
  metric: 'lead_processed',
  dimensions: {
    flow: flow_id,
    source: source_name,
    outcome: result
  },
  value: 1,
  timestamp: Date.now()
})

💡 Best Practices

Monitor Proactively

Don't Wait for Problems:

• Set up alerts before issues
• Review dashboards daily
• Track trends weekly
• Deep dive monthly

Focus on Business Impact

Prioritize Metrics:

1. Revenue-impacting metrics
2. Cost-related metrics
3. Quality indicators
4. Technical performance

Automate Response

When Possible:

// Auto-pause bad sources
if (source.quality_score < 70) {
  source.pause()
  notify_team("Source auto-paused: " + source.name)
}

// Auto-scale volume caps
if (conversion_rate > target) {
  increase_volume_cap(source, 20)
}

Document and Share

Keep Team Informed:

• Document what metrics mean
• Share dashboard access
• Train on alert response
• Regular performance reviews

🎯 Monitoring Checklist

Initial Setup:

• Define KPIs
• Set up dashboards
• Configure critical alerts
• Test alert delivery

Daily Monitoring:

• Check dashboard
• Review any alerts
• Note anomalies
• Quick fixes applied

Weekly Review:

• Analyze trends
• Compare sources
• Review costs
• Plan optimizations

Monthly Deep Dive:

• Full performance analysis
• ROI calculations
• Process improvements
• Strategy adjustments

📈 Continuous Improvement

Regular Optimization Cycle

1. Measure: Collect performance data
2. Analyze: Identify improvement areas
3. Optimize: Implement changes
4. Verify: Confirm improvements
5. Repeat: Continue cycle

A/B Testing

Test improvements:

// Test new validation
if (Math.random() < 0.1) {  // 10% test
  use_new_validation = true
} else {
  use_old_validation = true
}

// Track results
track_metric('validation_success', {
  version: use_new_validation ? 'new' : 'old',
  result: validation_result
})

📚 Related Documentation

• Custom Reports - Build specific reports
• Understanding Events - Event analysis
• Flow Optimization - Performance tips

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📊 Monitor to Master: Effective monitoring transforms reactive firefighting into proactive optimization. Set up comprehensive monitoring and watch your performance improve continuously!