You're at the mercy of Google Bot's crawling decisions, with limited control over what gets crawled, when, and how. This lack of control prevents advanced SEO testing, personalized bot experiences, and precise crawl budget allocation. Cloudflare Workers provide unprecedented control over bot traffic, but most SEOs don't leverage this power. The solution is implementing sophisticated bot management strategies that transform Google Bot from an unknown variable into a controlled optimization tool.

Bot Control Architecture with Workers

Traditional bot management is reactive—you set rules in robots.txt and hope Google Bot follows them. Cloudflare Workers enable proactive bot management where you can intercept, analyze, and manipulate bot traffic in real-time. This creates a new architecture: Bot Control Layer at the Edge.

The architecture consists of three components: Bot Detection (identifying and classifying bots), Bot Decision Engine (applying rules based on bot type and behavior), and Bot Response Manipulation (serving optimized content, controlling crawl rates, or blocking unwanted behavior). This layer sits between Google Bot and your Jekyll site, giving you complete control without modifying your static site structure.

Bot Control Components Architecture

Advanced Bot Detection and Classification

Go beyond simple user agent matching:

// Advanced bot detection with behavioral analysis
class BotDetector {
  constructor() {
    this.botPatterns = this.loadBotPatterns()
    this.botBehaviorProfiles = this.loadBehaviorProfiles()
  }
  
  async detectBot(request, response) {
    const detection = {
      isBot: false,
      botType: null,
      confidence: 0,
      behaviorProfile: null
    }
    
    // Method 1: User Agent Analysis
    const uaDetection = this.analyzeUserAgent(request.headers.get('User-Agent'))
    detection.confidence += uaDetection.confidence * 0.4
    
    // Method 2: IP Analysis
    const ipDetection = await this.analyzeIP(request.headers.get('CF-Connecting-IP'))
    detection.confidence += ipDetection.confidence * 0.3
    
    // Method 3: Behavioral Analysis
    const behaviorDetection = await this.analyzeBehavior(request, response)
    detection.confidence += behaviorDetection.confidence * 0.3
    
    // Method 4: Header Analysis
    const headerDetection = this.analyzeHeaders(request.headers)
    detection.confidence += headerDetection.confidence * 0.2
    
    // Combine detections
    if (detection.confidence >= 0.7) {
      detection.isBot = true
      detection.botType = this.determineBotType(uaDetection, behaviorDetection)
      detection.behaviorProfile = this.getBehaviorProfile(detection.botType)
    }
    
    return detection
  }
  
  analyzeUserAgent(userAgent) {
    const patterns = {
      googlebot: /Googlebot/i,
      googlebotSmartphone: /Googlebot.*Smartphone|iPhone.*Googlebot/i,
      googlebotImage: /Googlebot-Image/i,
      googlebotVideo: /Googlebot-Video/i,
      bingbot: /Bingbot/i,
      yahoo: /Slurp/i,
      baidu: /Baiduspider/i,
      yandex: /YandexBot/i,
      facebook: /facebookexternalhit/i,
      twitter: /Twitterbot/i,
      linkedin: /LinkedInBot/i
    }
    
    for (const [type, pattern] of Object.entries(patterns)) {
      if (pattern.test(userAgent)) {
        return {
          botType: type,
          confidence: 0.9,
          rawMatch: userAgent.match(pattern)[0]
        }
      }
    }
    
    // Check for generic bot patterns
    const genericBotPatterns = [
      /bot/i, /crawler/i, /spider/i, /scraper/i,
      /curl/i, /wget/i, /python/i, /java/i
    ]
    
    if (genericBotPatterns.some(p => p.test(userAgent))) {
      return {
        botType: 'generic_bot',
        confidence: 0.6,
        warning: 'Generic bot detected'
      }
    }
    
    return { botType: null, confidence: 0 }
  }
  
  async analyzeIP(ip) {
    // Check if IP is from known search engine ranges
    const knownRanges = await this.fetchKnownBotIPRanges()
    
    for (const range of knownRanges) {
      if (this.isIPInRange(ip, range)) {
        return {
          confidence: 0.95,
          range: range.name,
          provider: range.provider
        }
      }
    }
    
    // Check IP reputation
    const reputation = await this.checkIPReputation(ip)
    
    return {
      confidence: reputation.score > 80 ? 0.8 : 0.3,
      reputation: reputation
    }
  }
  
  analyzeBehavior(request, response) {
    const behavior = {
      requestRate: this.calculateRequestRate(request),
      crawlPattern: this.analyzeCrawlPattern(request),
      resourceConsumption: this.analyzeResourceConsumption(response),
      timingPatterns: this.analyzeTimingPatterns(request)
    }
    
    let confidence = 0
    
    // Bot-like behaviors
    if (behavior.requestRate > 10) confidence += 0.3 // High request rate
    if (behavior.crawlPattern === 'systematic') confidence += 0.3
    if (behavior.resourceConsumption.low) confidence += 0.2 // Bots don't execute JS
    if (behavior.timingPatterns.consistent) confidence += 0.2
    
    return {
      confidence: Math.min(confidence, 1),
      behavior: behavior
    }
  }
  
  analyzeHeaders(headers) {
    const botHeaders = {
      'Accept': /text\/html.*application\/xhtml\+xml.*application\/xml/i,
      'Accept-Language': /en-US,en/i,
      'Accept-Encoding': /gzip, deflate/i,
      'Connection': /keep-alive/i
    }
    
    let matches = 0
    let total = Object.keys(botHeaders).length
    
    for (const [header, pattern] of Object.entries(botHeaders)) {
      const value = headers.get(header)
      if (value && pattern.test(value)) {
        matches++
      }
    }
    
    return {
      confidence: matches / total,
      matches: matches,
      total: total
    }
  }
}

Precise Crawl Control Strategies

Implement granular crawl control:

1. Dynamic Crawl Budget Allocation

// Dynamic crawl budget manager
class CrawlBudgetManager {
  constructor() {
    this.budgets = new Map()
    this.crawlLog = []
  }
  
  async manageCrawl(request, detection) {
    const url = new URL(request.url)
    const botType = detection.botType
    
    // Get or create budget for this bot type
    let budget = this.budgets.get(botType)
    if (!budget) {
      budget = this.createBudgetForBot(botType)
      this.budgets.set(botType, budget)
    }
    
    // Check if crawl is allowed
    const crawlDecision = this.evaluateCrawl(url, budget, detection)
    
    if (!crawlDecision.allow) {
      return {
        action: 'block',
        reason: crawlDecision.reason,
        retryAfter: crawlDecision.retryAfter
      }
    }
    
    // Update budget
    budget.used += 1
    this.logCrawl(url, botType, detection)
    
    // Apply crawl delay if needed
    const delay = this.calculateOptimalDelay(url, budget, detection)
    
    return {
      action: 'allow',
      delay: delay,
      budgetRemaining: budget.total - budget.used
    }
  }
  
  createBudgetForBot(botType) {
    const baseBudgets = {
      googlebot: { total: 1000, period: 'daily', priority: 'high' },
      googlebotSmartphone: { total: 1500, period: 'daily', priority: 'critical' },
      googlebotImage: { total: 500, period: 'daily', priority: 'medium' },
      bingbot: { total: 300, period: 'daily', priority: 'medium' },
      generic_bot: { total: 100, period: 'daily', priority: 'low' }
    }
    
    const config = baseBudgets[botType] || { total: 50, period: 'daily', priority: 'low' }
    
    return {
      ...config,
      used: 0,
      resetAt: this.calculateResetTime(config.period),
      history: []
    }
  }
  
  evaluateCrawl(url, budget, detection) {
    // Rule 1: Budget exhaustion
    if (budget.used >= budget.total) {
      return {
        allow: false,
        reason: 'Daily crawl budget exhausted',
        retryAfter: this.secondsUntilReset(budget.resetAt)
      }
    }
    
    // Rule 2: Low priority URLs for high-value bots
    if (budget.priority === 'high' && this.isLowPriorityURL(url)) {
      return {
        allow: false,
        reason: 'Low priority URL for high-value bot',
        retryAfter: 3600 // 1 hour
      }
    }
    
    // Rule 3: Recent crawl (avoid duplicate crawls)
    const lastCrawl = this.getLastCrawlTime(url, detection.botType)
    if (lastCrawl && Date.now() - lastCrawl < this.getMinCrawlInterval(url)) {
      return {
        allow: false,
        reason: 'Crawled too recently',
        retryAfter: this.getMinCrawlInterval(url) / 1000
      }
    }
    
    return { allow: true }
  }
  
  calculateOptimalDelay(url, budget, detection) {
    let baseDelay = 1000 // 1 second default
    
    // Adjust based on bot type
    switch(detection.botType) {
      case 'googlebotSmartphone':
        baseDelay = 500 // Faster for mobile bot
        break
      case 'googlebot':
        baseDelay = 1000
        break
      case 'generic_bot':
        baseDelay = 3000 // Slower for generic bots
        break
    }
    
    // Adjust based on URL importance
    if (this.isHighPriorityURL(url)) {
      baseDelay *= 0.5 // Faster for important pages
    } else if (this.isLowPriorityURL(url)) {
      baseDelay *= 2 // Slower for low priority pages
    }
    
    // Adjust based on budget usage
    const usageRatio = budget.used / budget.total
    if (usageRatio > 0.8) {
      baseDelay *= 1.5 // Slow down near budget limit
    }
    
    return Math.round(baseDelay)
  }
}

2. Intelligent URL Prioritization

// URL priority classifier for crawl control
class URLPriorityClassifier {
  constructor(analyticsData) {
    this.analytics = analyticsData
    this.priorityCache = new Map()
  }
  
  classifyURL(url) {
    if (this.priorityCache.has(url)) {
      return this.priorityCache.get(url)
    }
    
    let score = 0
    const factors = []
    
    // Factor 1: Page authority (traffic)
    const traffic = this.analytics.trafficByURL[url] || 0
    if (traffic > 1000) score += 30
    else if (traffic > 100) score += 20
    else if (traffic > 10) score += 10
    factors.push(`traffic:${traffic}`)
    
    // Factor 2: Content freshness
    const freshness = this.getContentFreshness(url)
    if (freshness === 'fresh') score += 25
    else if (freshness === 'updated') score += 15
    else if (freshness === 'stale') score += 5
    factors.push(`freshness:${freshness}`)
    
    // Factor 3: Conversion value
    const conversionRate = this.getConversionRate(url)
    score += conversionRate * 20
    factors.push(`conversion:${conversionRate}`)
    
    // Factor 4: Structural importance
    if (url === '/') score += 25
    else if (url.includes('/blog/')) score += 15
    else if (url.includes('/product/')) score += 20
    else if (url.includes('/category/')) score += 5
    factors.push(`structure:${url.split('/')[1]}`)
    
    // Factor 5: External signals
    const backlinks = this.getBacklinkCount(url)
    score += Math.min(backlinks / 10, 10) // Max 10 points
    factors.push(`backlinks:${backlinks}`)
    
    // Normalize score and assign priority
    const normalizedScore = Math.min(score, 100)
    let priority
    
    if (normalizedScore >= 70) priority = 'critical'
    else if (normalizedScore >= 50) priority = 'high'
    else if (normalizedScore >= 30) priority = 'medium'
    else if (normalizedScore >= 10) priority = 'low'
    else priority = 'very_low'
    
    const classification = {
      score: normalizedScore,
      priority: priority,
      factors: factors,
      crawlFrequency: this.recommendCrawlFrequency(priority)
    }
    
    this.priorityCache.set(url, classification)
    return classification
  }
  
  recommendCrawlFrequency(priority) {
    const frequencies = {
      critical: 'hourly',
      high: 'daily',
      medium: 'weekly',
      low: 'monthly',
      very_low: 'quarterly'
    }
    
    return frequencies[priority]
  }
  
  generateCrawlSchedule() {
    const urls = Object.keys(this.analytics.trafficByURL)
    const classified = urls.map(url => this.classifyURL(url))
    
    const schedule = {
      hourly: classified.filter(c => c.priority === 'critical').map(c => c.url),
      daily: classified.filter(c => c.priority === 'high').map(c => c.url),
      weekly: classified.filter(c => c.priority === 'medium').map(c => c.url),
      monthly: classified.filter(c => c.priority === 'low').map(c => c.url),
      quarterly: classified.filter(c => c.priority === 'very_low').map(c => c.url)
    }
    
    return schedule
  }
}

Dynamic Rendering for SEO Testing

Serve different content to Google Bot for testing:

// Dynamic rendering engine for SEO experiments
class DynamicRenderer {
  constructor() {
    this.experiments = new Map()
    this.renderCache = new Map()
  }
  
  async renderForBot(request, originalResponse, detection) {
    const url = new URL(request.url)
    const cacheKey = `${url.pathname}-${detection.botType}`
    
    // Check cache
    if (this.renderCache.has(cacheKey)) {
      const cached = this.renderCache.get(cacheKey)
      if (Date.now() - cached.timestamp < 300000) { // 5 minute cache
        return cached.response
      }
    }
    
    // Check for active experiments
    const experiment = this.getActiveExperiment(url, detection.botType)
    
    let renderedHTML
    if (experiment) {
      // Apply experiment variant
      renderedHTML = await this.applyExperimentVariant(
        originalResponse,
        experiment
      )
    } else {
      // Apply standard bot optimizations
      renderedHTML = await this.applyStandardOptimizations(
        originalResponse,
        detection
      )
    }
    
    // Apply bot-specific enhancements
    renderedHTML = this.enhanceForBot(renderedHTML, detection)
    
    // Create response
    const response = new Response(renderedHTML, originalResponse)
    
    // Add bot rendering headers
    response.headers.set('X-Bot-Rendered', 'true')
    response.headers.set('X-Bot-Type', detection.botType)
    if (experiment) {
      response.headers.set('X-Experiment-ID', experiment.id)
      response.headers.set('X-Experiment-Variant', experiment.variant)
    }
    
    // Cache the response
    this.renderCache.set(cacheKey, {
      response: response,
      timestamp: Date.now()
    })
    
    return response
  }
  
  async applyStandardOptimizations(response, detection) {
    let html = await response.text()
    
    // Different optimizations for different bot types
    switch(detection.botType) {
      case 'googlebotSmartphone':
        html = this.optimizeForMobileBot(html)
        break
      case 'googlebotImage':
        html = this.optimizeForImageBot(html)
        break
      case 'googlebot':
        html = this.optimizeForDesktopBot(html)
        break
    }
    
    // Common optimizations for all bots
    html = this.injectStructuredData(html)
    html = this.optimizeInternalLinking(html)
    html = this.addBotHelpfulMeta(html)
    
    return html
  }
  
  async applyExperimentVariant(response, experiment) {
    let html = await response.text()
    
    switch(experiment.type) {
      case 'title_optimization':
        html = this.experimentWithTitles(html, experiment.variant)
        break
      case 'meta_description':
        html = this.experimentWithDescriptions(html, experiment.variant)
        break
      case 'internal_linking':
        html = this.experimentWithInternalLinks(html, experiment.variant)
        break
      case 'content_length':
        html = this.experimentWithContentLength(html, experiment.variant)
        break
      case 'schema_markup':
        html = this.experimentWithSchema(html, experiment.variant)
        break
    }
    
    // Track experiment impression
    this.trackExperimentImpression(experiment.id, experiment.variant)
    
    return html
  }
  
  experimentWithTitles(html, variant) {
    const titleMatch = html.match(/title(.*?)\/title/i)
    if (!titleMatch) return html
    
    const originalTitle = titleMatch[1]
    let newTitle
    
    switch(variant) {
      case 'add_keyword_front':
        newTitle = `Best Guide: ${originalTitle}`
        break
      case 'add_year':
        newTitle = `${originalTitle} (2024 Edition)`
        break
      case 'add_brackets':
        newTitle = `${originalTitle} [Complete Guide]`
        break
      default:
        newTitle = originalTitle
    }
    
    return html.replace(/title(.*?)\/title/i, `<title>${newTitle}</title>`)
  }
  
  enhanceForBot(html, detection) {
    // Add bot-specific enhancements
    
    // 1. Inject crawl hints
    const crawlHints = this.generateCrawlHints(detection.botType)
    html = html.replace('</head>', `${crawlHints}</head>`)
    
    // 2. Add bot-readable metadata
    const botMeta = this.generateBotMeta(detection)
    html = html.replace('</head>', `${botMeta}</head>`)
    
    // 3. Optimize for bot rendering
    if (detection.botType === 'googlebotSmartphone') {
      html = this.addMobileBotEnhancements(html)
    }
    
    return html
  }
  
  generateCrawlHints(botType) {
    const hints = []
    
    // Add resource hints for faster crawling
    hints.push('<link rel="preconnect" href="https://fonts.googleapis.com">')
    hints.push('<link rel="dns-prefetch" href="//cdn.yoursite.com">')
    
    // Bot-specific hints
    if (botType === 'googlebotSmartphone') {
      hints.push('<meta name="googlebot" content="max-image-preview:large">')
    }
    
    return hints.join('\n')
  }
}

Bot Traffic Shaping and Prioritization

Shape bot traffic flow intelligently:

// Bot traffic shaper and prioritization engine
class BotTrafficShaper {
  constructor() {
    this.queues = new Map()
    this.priorityRules = this.loadPriorityRules()
    this.trafficHistory = []
  }
  
  async shapeTraffic(request, detection) {
    const url = new URL(request.url)
    
    // Determine priority
    const priority = this.calculatePriority(url, detection)
    
    // Check rate limits
    if (!this.checkRateLimits(detection.botType, priority)) {
      return this.handleRateLimitExceeded(detection)
    }
    
    // Queue management for high traffic periods
    if (this.isPeakTrafficPeriod()) {
      return this.handleWithQueue(request, detection, priority)
    }
    
    // Apply priority-based delays
    const delay = this.calculatePriorityDelay(priority)
    
    if (delay > 0) {
      await this.delay(delay)
    }
    
    // Process request
    return this.processRequest(request, detection)
  }
  
  calculatePriority(url, detection) {
    let score = 0
    
    // Bot type priority
    const botPriority = {
      googlebotSmartphone: 100,
      googlebot: 90,
      googlebotImage: 80,
      bingbot: 70,
      googlebotVideo: 60,
      generic_bot: 10
    }
    
    score += botPriority[detection.botType] || 0
    
    // URL priority
    if (url.pathname === '/') score += 50
    else if (url.pathname.includes('/blog/')) score += 40
    else if (url.pathname.includes('/product/')) score += 45
    else if (url.pathname.includes('/category/')) score += 20
    
    // Content freshness priority
    const freshness = this.getContentFreshness(url)
    if (freshness === 'fresh') score += 30
    else if (freshness === 'updated') score += 20
    
    // Convert score to priority level
    if (score >= 120) return 'critical'
    else if (score >= 90) return 'high'
    else if (score >= 60) return 'medium'
    else if (score >= 30) return 'low'
    else return 'very_low'
  }
  
  checkRateLimits(botType, priority) {
    const limits = {
      critical: { requests: 100, period: 60 }, // per minute
      high: { requests: 50, period: 60 },
      medium: { requests: 20, period: 60 },
      low: { requests: 10, period: 60 },
      very_low: { requests: 5, period: 60 }
    }
    
    const limit = limits[priority]
    const key = `${botType}:${priority}`
    
    // Get recent requests
    const now = Date.now()
    const recent = this.trafficHistory.filter(
      entry => entry.key === key && now - entry.timestamp < limit.period * 1000
    )
    
    return recent.length < limit.requests
  }
  
  handleWithQueue(request, detection, priority) {
    const queue = this.getQueue(priority)
    const queueItem = {
      request: request,
      detection: detection,
      timestamp: Date.now(),
      priority: priority
    }
    
    // Add to queue
    queue.push(queueItem)
    
    // Process queue in priority order
    return this.processQueue()
  }
  
  async processQueue() {
    // Process queues in priority order
    const priorities = ['critical', 'high', 'medium', 'low', 'very_low']
    
    for (const priority of priorities) {
      const queue = this.getQueue(priority)
      if (queue.length > 0) {
        const item = queue.shift() // FIFO within priority
        
        // Check if still valid (not too old)
        if (Date.now() - item.timestamp < 30000) { // 30 second timeout
          return this.processRequest(item.request, item.detection)
        }
      }
    }
    
    // If all queues empty, fall through
    return new Response('Queue processed', { status: 200 })
  }
  
  calculatePriorityDelay(priority) {
    const delays = {
      critical: 0,    // No delay for critical
      high: 100,      // 100ms for high
      medium: 500,    // 500ms for medium
      low: 1000,      // 1 second for low
      very_low: 3000  // 3 seconds for very low
    }
    
    return delays[priority] || 1000
  }
  
  async processRequest(request, detection) {
    // Add bot processing headers
    const response = await fetch(request)
    const newResponse = new Response(response.body, response)
    
    newResponse.headers.set('X-Bot-Processed', 'true')
    newResponse.headers.set('X-Bot-Priority', detection.priority || 'medium')
    newResponse.headers.set('X-Crawl-Delay', this.calculatePriorityDelay(detection.priority))
    
    // Log the processing
    this.logBotProcessing(request.url, detection)
    
    return newResponse
  }
}

SEO Experimentation with Controlled Bots

Run controlled SEO experiments on Google Bot:

// SEO experiment framework for bot testing
class SEOExperimentFramework {
  constructor() {
    this.experiments = new Map()
    this.results = new Map()
    this.activeVariants = new Map()
  }
  
  createExperiment(config) {
    const experiment = {
      id: this.generateExperimentId(),
      name: config.name,
      type: config.type,
      hypothesis: config.hypothesis,
      variants: config.variants,
      trafficAllocation: config.trafficAllocation || { control: 50, variant: 50 },
      targetBots: config.targetBots || ['googlebot', 'googlebotSmartphone'],
      startDate: new Date(),
      endDate: config.duration ? new Date(Date.now() + config.duration * 86400000) : null,
      status: 'active',
      metrics: {}
    }
    
    this.experiments.set(experiment.id, experiment)
    return experiment
  }
  
  assignVariant(experimentId, requestUrl, botType) {
    const experiment = this.experiments.get(experimentId)
    if (!experiment || experiment.status !== 'active') return null
    
    // Check if bot is targeted
    if (!experiment.targetBots.includes(botType)) return null
    
    // Check if URL matches experiment criteria
    if (!this.urlMatchesCriteria(requestUrl, experiment.criteria)) return null
    
    // Assign variant based on traffic allocation
    const variantKey = `${experimentId}:${requestUrl}`
    
    if (this.activeVariants.has(variantKey)) {
      return this.activeVariants.get(variantKey)
    }
    
    // Random assignment based on traffic allocation
    const random = Math.random() * 100
    let assignedVariant
    
    if (random < experiment.trafficAllocation.control) {
      assignedVariant = 'control'
    } else if (random < experiment.trafficAllocation.control + experiment.trafficAllocation.variant) {
      assignedVariant = 'variant_a'
    } else if (experiment.variants.variant_b && 
               random < experiment.trafficAllocation.control + 
                        experiment.trafficAllocation.variant + 
                        experiment.trafficAllocation.variant_b) {
      assignedVariant = 'variant_b'
    } else {
      assignedVariant = 'control' // Fallback
    }
    
    this.activeVariants.set(variantKey, assignedVariant)
    return assignedVariant
  }
  
  async trackResult(experimentId, variant, metric, value) {
    const experiment = this.experiments.get(experimentId)
    if (!experiment) return
    
    // Initialize metric tracking
    if (!experiment.metrics[metric]) {
      experiment.metrics[metric] = {
        control: { sum: 0, count: 0, values: [] },
        variant_a: { sum: 0, count: 0, values: [] },
        variant_b: { sum: 0, count: 0, values: [] }
      }
    }
    
    // Update metric
    const metricData = experiment.metrics[metric][variant]
    metricData.sum += value
    metricData.count += 1
    metricData.values.push(value)
    
    // Check for statistical significance
    if (metricData.count >= experiment.minSampleSize) {
      const significance = this.calculateStatisticalSignificance(experiment, metric)
      
      if (significance.pValue < 0.05) { // 95% confidence
        experiment.status = 'concluded'
        experiment.conclusion = {
          winner: significance.winner,
          confidence: 1 - significance.pValue,
          improvement: significance.improvement,
          metric: metric
        }
        
        this.notifyExperimentConclusion(experiment)
      }
    }
  }
  
  calculateStatisticalSignificance(experiment, metric) {
    const control = experiment.metrics[metric].control
    const variant = experiment.metrics[metric].variant_a
    
    // Simple t-test calculation
    const controlMean = control.sum / control.count
    const variantMean = variant.sum / variant.count
    
    const controlVariance = this.calculateVariance(control.values, controlMean)
    const variantVariance = this.calculateVariance(variant.values, variantMean)
    
    const pooledVariance = (
      (control.count - 1) * controlVariance + 
      (variant.count - 1) * variantVariance
    ) / (control.count + variant.count - 2)
    
    const tStatistic = (variantMean - controlMean) / 
                      Math.sqrt(pooledVariance * (1/control.count + 1/variant.count))
    
    // Degrees of freedom
    const df = control.count + variant.count - 2
    
    // Calculate p-value (simplified)
    const pValue = this.calculatePValue(tStatistic, df)
    
    return {
      pValue: pValue,
      winner: variantMean > controlMean ? 'variant' : 'control',
      improvement: ((variantMean - controlMean) / controlMean) * 100
    }
  }
  
  // Example experiment configurations
  static getPredefinedExperiments() {
    return {
      title_optimization: {
        name: 'Title Tag Optimization',
        type: 'title_optimization',
        hypothesis: 'Adding [2024] to title increases CTR',
        variants: {
          control: 'Original title',
          variant_a: 'Title with [2024]',
          variant_b: 'Title with (Updated 2024)'
        },
        targetBots: ['googlebot', 'googlebotSmartphone'],
        duration: 30, // 30 days
        minSampleSize: 1000,
        metrics: ['impressions', 'clicks', 'ctr']
      },
      
      meta_description: {
        name: 'Meta Description Length',
        type: 'meta_description',
        hypothesis: 'Longer meta descriptions (160 chars) increase CTR',
        variants: {
          control: 'Short description (120 chars)',
          variant_a: 'Medium description (140 chars)',
          variant_b: 'Long description (160 chars)'
        },
        duration: 45,
        minSampleSize: 1500
      },
      
      internal_linking: {
        name: 'Internal Link Placement',
        type: 'internal_linking',
        hypothesis: 'Internal links in first paragraph increase crawl depth',
        variants: {
          control: 'Links in middle of content',
          variant_a: 'Links in first paragraph',
          variant_b: 'Links in conclusion'
        },
        metrics: ['pages_crawled', 'crawl_depth', 'indexation_rate']
      }
    }
  }
}

// Worker integration for experiments
addEventListener('fetch', event => {
  event.respondWith(handleExperimentRequest(event.request))
})

async function handleExperimentRequest(request) {
  const detector = new BotDetector()
  const detection = await detector.detectBot(request)
  
  if (!detection.isBot) {
    return fetch(request)
  }
  
  const experimentFramework = new SEOExperimentFramework()
  const experiments = experimentFramework.getActiveExperiments()
  
  let response = await fetch(request)
  let html = await response.text()
  
  // Apply experiments
  for (const experiment of experiments) {
    const variant = experimentFramework.assignVariant(
      experiment.id, 
      request.url, 
      detection.botType
    )
    
    if (variant) {
      const renderer = new DynamicRenderer()
      html = await renderer.applyExperimentVariant(
        new Response(html, response),
        { id: experiment.id, variant: variant, type: experiment.type }
      )
      
      // Track experiment assignment
      experimentFramework.trackAssignment(experiment.id, variant, request.url)
    }
  }
  
  return new Response(html, response)
}

Start implementing advanced bot management today. Begin with basic bot detection and priority-based crawling. Then implement dynamic rendering for critical pages. Gradually add more sophisticated features like traffic shaping and SEO experimentation. Monitor results in both Cloudflare Analytics and Google Search Console. Advanced bot management transforms Google Bot from an uncontrollable variable into a precision SEO tool.