Activity: App Store Optimization

class CompetitorAnalyzer {
  constructor() {
    this.competitors = new Map();
    this.metrics = ['ranking', 'ratings', 'reviews', 'keywords', 'pricing'];
  }

  async analyzeCompetitor(appId, competitorData) {
    const analysis = {
      appId,
      name: competitorData.name,
      category: competitorData.category,
      ranking: competitorData.ranking,
      ratings: {
        average: competitorData.ratingAverage,
        count: competitorData.ratingCount,
        trend: this.calculateRatingTrend(competitorData.ratingHistory)
      },
      keywords: this.extractCompetitorKeywords(competitorData),
      screenshots: this.analyzeCompetitorScreenshots(competitorData.screenshots),
      pricing: competitorData.pricing,
      features: this.extractFeatureList(competitorData.description),
      strengths: [],
      weaknesses: [],
      opportunities: []
    };

    // Identify competitive advantages
    analysis.strengths = this.identifyStrengths(analysis);
    analysis.weaknesses = this.identifyWeaknesses(analysis);
    analysis.opportunities = this.identifyOpportunities(analysis);

    this.competitors.set(appId, analysis);
    return analysis;
  }

  generateCompetitiveReport(myAppData) {
    const report = {
      myApp: myAppData,
      competitors: Array.from(this.competitors.values()),
      comparison: {},
      recommendations: []
    };

    // Compare key metrics
    report.comparison = {
      ranking: this.compareRankings(myAppData, this.competitors),
      ratings: this.compareRatings(myAppData, this.competitors),
      keywords: this.compareKeywords(myAppData, this.competitors),
      features: this.compareFeatures(myAppData, this.competitors)
    };

    // Generate actionable recommendations
    report.recommendations = this.generateCompetitiveRecommendations(report.comparison);

    return report;
  }

  identifyMarketGaps() {
    const gaps = {
      underservedKeywords: [],
      missingFeatures: [],
      pricingOpportunities: [],
      designTrends: []
    };

    // Analyze keyword gaps
    const allCompetitorKeywords = new Set();
    for (const competitor of this.competitors.values()) {
      competitor.keywords.forEach(keyword => allCompetitorKeywords.add(keyword));
    }

    // Find underserved keywords (high volume, low competition)
    gaps.underservedKeywords = this.findUnderservedKeywords(allCompetitorKeywords);

    // Identify missing features
    gaps.missingFeatures = this.identifyMissingFeatures();

    return gaps;
  }
}

const competitorAnalyzer = new CompetitorAnalyzer();

// Example competitor analysis
const myAppData = {
  name: 'FitTracker Pro',
  category: 'fitness',
  ranking: { fitness: 45, overall: 1250 },
  ratings: { average: 4.2, count: 1500 }
};

// This would typically come from app store APIs or scraping tools
const competitorData = {
  name: 'Fitness Competitor',
  category: 'fitness',
  ranking: { fitness: 12, overall: 340 },
  ratingAverage: 4.6,
  ratingCount: 25000,
  description: 'Ultimate fitness tracking app...',
  screenshots: ['screenshot1.jpg', 'screenshot2.jpg'],
  pricing: 'freemium'
};

competitorAnalyzer.analyzeCompetitor('competitor1', competitorData);
const competitiveReport = competitorAnalyzer.generateCompetitiveReport(myAppData);

import React, { useState, useEffect, useRef } from 'react';
import { View, Text, ScrollView, TouchableOpacity, TextInput, Alert } from 'react-native';

// Advanced ASO Testing and Analytics System
class ASOTestingPlatform {
  constructor() {
    this.activeTests = new Map();
    this.testResults = new Map();
    this.conversionFunnels = new Map();
    this.performanceMetrics = {
      impressions: new Map(),
      conversions: new Map(),
      keywords: new Map(),
      screenshots: new Map()
    };
  }

  // A/B testing for app store elements
  async createABTest(testConfig) {
    const test = {
      id: Date.now().toString(),
      name: testConfig.name,
      type: testConfig.type, // 'title', 'description', 'screenshots', 'icon'
      variants: testConfig.variants,
      startDate: new Date(),
      endDate: new Date(Date.now() + testConfig.duration),
      targetMetric: testConfig.targetMetric, // 'conversion_rate', 'ctr', 'retention'
      status: 'active',
      trafficSplit: testConfig.trafficSplit || [50, 50],
      results: {
        variant_a: { impressions: 0, conversions: 0, rate: 0 },
        variant_b: { impressions: 0, conversions: 0, rate: 0 }
      },
      statisticalSignificance: {
        achieved: false,
        confidenceLevel: 0,
        requiredSampleSize: this.calculateSampleSize(testConfig)
      }
    };

    this.activeTests.set(test.id, test);
    await this.deployTestVariants(test);
    
    return test;
  }

  calculateSampleSize(testConfig) {
    // Statistical calculation for required sample size
    const baselineRate = testConfig.baselineConversionRate || 0.05; // 5% default
    const minimumDetectableEffect = testConfig.minimumDetectableEffect || 0.2; // 20% improvement
    const alpha = testConfig.alpha || 0.05; // 95% confidence
    const beta = testConfig.beta || 0.2; // 80% power

    // Simplified sample size calculation
    const effectSize = minimumDetectableEffect * baselineRate;
    const pooledRate = baselineRate + effectSize / 2;
    
    const sampleSize = Math.ceil(
      2 * pooledRate * (1 - pooledRate) * 
      Math.pow((1.96 + 0.84), 2) / Math.pow(effectSize, 2)
    );

    return sampleSize;
  }

  async deployTestVariants(test) {
    // This would integrate with app store APIs or management platforms
    console.log(`Deploying A/B test: ${test.name}`);
    
    switch (test.type) {
      case 'title':
        await this.deployTitleTest(test);
        break;
      case 'screenshots':
        await this.deployScreenshotTest(test);
        break;
      case 'description':
        await this.deployDescriptionTest(test);
        break;
      case 'icon':
        await this.deployIconTest(test);
        break;
    }

    // Set up analytics tracking
    await this.setupTestTracking(test);
  }

  async deployTitleTest(test) {
    // Deploy title variants across app stores
    const variants = test.variants;
    
    // iOS App Store Connect API integration
    await this.updateAppStoreMetadata('ios', {
      title: variants.variant_a.title,
      testId: test.id,
      variant: 'a'
    });

    // Google Play Console API integration
    await this.updatePlayStoreMetadata('android', {
      title: variants.variant_b.title,
      testId: test.id,
      variant: 'b'
    });

    console.log(`Title test deployed: "${variants.variant_a.title}" vs "${variants.variant_b.title}"`);
  }

  async deployScreenshotTest(test) {
    const variants = test.variants;
    
    // Upload and deploy screenshot variants
    for (const [variantKey, variantData] of Object.entries(variants)) {
      await this.uploadScreenshotSet(variantData.screenshots, test.id, variantKey);
    }
  }

  // Track test performance
  async recordTestMetric(testId, variant, metricType, value) {
    const test = this.activeTests.get(testId);
    if (!test) return;

    test.results[variant][metricType] += value;
    
    // Recalculate conversion rate
    if (test.results[variant].impressions > 0) {
      test.results[variant].rate = 
        test.results[variant].conversions / test.results[variant].impressions;
    }

    // Check statistical significance
    await this.checkStatisticalSignificance(testId);
    
    // Auto-end test if significant results achieved
    if (test.statisticalSignificance.achieved && 
        test.results.variant_a.impressions + test.results.variant_b.impressions >= 
        test.statisticalSignificance.requiredSampleSize) {
      await this.endABTest(testId);
    }
  }

  async checkStatisticalSignificance(testId) {
    const test = this.activeTests.get(testId);
    if (!test) return;

    const { variant_a, variant_b } = test.results;
    
    if (variant_a.impressions < 100 || variant_b.impressions < 100) {
      return; // Need minimum sample size
    }

    // Two-proportion z-test
    const p1 = variant_a.rate;
    const p2 = variant_b.rate;
    const n1 = variant_a.impressions;
    const n2 = variant_b.impressions;
    
    const pooledP = (variant_a.conversions + variant_b.conversions) / (n1 + n2);
    const standardError = Math.sqrt(pooledP * (1 - pooledP) * (1/n1 + 1/n2));
    const zScore = Math.abs(p1 - p2) / standardError;
    
    // 95% confidence level (z = 1.96)
    const isSignificant = zScore > 1.96;
    const confidenceLevel = this.calculateConfidenceLevel(zScore);

    test.statisticalSignificance = {
      achieved: isSignificant,
      confidenceLevel: confidenceLevel,
      zScore: zScore,
      effect: Math.abs((p2 - p1) / p1 * 100), // Percentage improvement
      requiredSampleSize: test.statisticalSignificance.requiredSampleSize
    };

    console.log(`Test ${testId} significance: ${isSignificant}, confidence: ${confidenceLevel}%`);
  }

  calculateConfidenceLevel(zScore) {
    // Convert z-score to confidence level
    if (zScore >= 2.58) return 99;
    if (zScore >= 1.96) return 95;
    if (zScore >= 1.64) return 90;
    if (zScore >= 1.28) return 80;
    return Math.round((1 - 2 * (1 - this.normalCDF(Math.abs(zScore)))) * 100);
  }

  normalCDF(x) {
    // Approximation of standard normal cumulative distribution function
    return 0.5 * (1 + this.erf(x / Math.sqrt(2)));
  }

  erf(x) {
    // Error function approximation
    const a1 =  0.254829592;
    const a2 = -0.284496736;
    const a3 =  1.421413741;
    const a4 = -1.453152027;
    const a5 =  1.061405429;
    const p  =  0.3275911;

    const sign = x < 0 ? -1 : 1;
    x = Math.abs(x);

    const t = 1.0 / (1.0 + p * x);
    const y = 1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * Math.exp(-x * x);

    return sign * y;
  }

  async endABTest(testId) {
    const test = this.activeTests.get(testId);
    if (!test) return;

    test.status = 'completed';
    test.endDate = new Date();

    // Determine winner
    const winnerVariant = test.results.variant_b.rate > test.results.variant_a.rate ? 'b' : 'a';
    const improvement = Math.abs((test.results.variant_b.rate - test.results.variant_a.rate) / test.results.variant_a.rate * 100);

    const result = {
      testId,
      winner: winnerVariant,
      improvement: improvement,
      significance: test.statisticalSignificance,
      recommendation: improvement > 5 && test.statisticalSignificance.achieved ? 
        'implement_winner' : 'continue_testing'
    };

    this.testResults.set(testId, result);

    // Auto-implement winner if significant improvement
    if (result.recommendation === 'implement_winner') {
      await this.implementWinningVariant(testId, winnerVariant);
    }

    return result;
  }

  // Conversion funnel tracking
  trackConversionFunnel(userId, step, metadata = {}) {
    const funnelId = 'app_store_conversion';
    
    if (!this.conversionFunnels.has(funnelId)) {
      this.conversionFunnels.set(funnelId, {
        users: new Map(),
        steps: ['impression', 'view', 'install', 'open', 'onboard', 'convert'],
        dropoffRates: new Map()
      });
    }

    const funnel = this.conversionFunnels.get(funnelId);
    
    if (!funnel.users.has(userId)) {
      funnel.users.set(userId, {
        steps: [],
        timestamps: [],
        metadata: []
      });
    }

    const userJourney = funnel.users.get(userId);
    userJourney.steps.push(step);
    userJourney.timestamps.push(Date.now());
    userJourney.metadata.push(metadata);

    // Calculate real-time funnel metrics
    this.updateFunnelMetrics(funnelId);
  }

  updateFunnelMetrics(funnelId) {
    const funnel = this.conversionFunnels.get(funnelId);
    const stepCounts = new Map();
    
    // Count users at each step
    for (const userData of funnel.users.values()) {
      const uniqueSteps = [...new Set(userData.steps)];
      for (const step of uniqueSteps) {
        stepCounts.set(step, (stepCounts.get(step) || 0) + 1);
      }
    }

    // Calculate drop-off rates
    const orderedSteps = funnel.steps;
    for (let i = 1; i < orderedSteps.length; i++) {
      const currentStep = orderedSteps[i];
      const previousStep = orderedSteps[i - 1];
      
      const currentCount = stepCounts.get(currentStep) || 0;
      const previousCount = stepCounts.get(previousStep) || 0;
      
      if (previousCount > 0) {
        const dropoffRate = ((previousCount - currentCount) / previousCount) * 100;
        funnel.dropoffRates.set(currentStep, dropoffRate);
      }
    }
  }

  generateFunnelReport(funnelId) {
    const funnel = this.conversionFunnels.get(funnelId);
    if (!funnel) return null;

    const report = {
      totalUsers: funnel.users.size,
      stepConversions: new Map(),
      dropoffRates: funnel.dropoffRates,
      averageTimeToConvert: 0,
      recommendations: []
    };

    // Calculate step conversion rates
    const stepCounts = new Map();
    for (const userData of funnel.users.values()) {
      const uniqueSteps = [...new Set(userData.steps)];
      for (const step of uniqueSteps) {
        stepCounts.set(step, (stepCounts.get(step) || 0) + 1);
      }
    }

    const impressionCount = stepCounts.get('impression') || 1;
    for (const [step, count] of stepCounts.entries()) {
      report.stepConversions.set(step, (count / impressionCount) * 100);
    }

    // Generate recommendations based on drop-off rates
    for (const [step, dropoffRate] of funnel.dropoffRates.entries()) {
      if (dropoffRate > 70) {
        report.recommendations.push({
          step,
          issue: `High drop-off rate at ${step} (${dropoffRate.toFixed(1)}%)`,
          suggestions: this.getDropoffSuggestions(step)
        });
      }
    }

    return report;
  }

  getDropoffSuggestions(step) {
    const suggestions = {
      'view': [
        'Optimize app store listing visibility',
        'Improve keyword targeting',
        'Enhance app icon design',
        'Review app store category selection'
      ],
      'install': [
        'Optimize app screenshots and preview',
        'Improve app description and value proposition',
        'Address negative reviews',
        'Consider app size optimization'
      ],
      'open': [
        'Optimize app startup time',
        'Review app permissions requests',
        'Check for crashes on app launch',
        'Improve app icon and branding'
      ],
      'onboard': [
        'Simplify onboarding process',
        'Reduce required user inputs',
        'Add progress indicators',
        'Implement skip options for non-critical steps'
      ]
    };

    return suggestions[step] || ['Analyze user behavior for this step'];
  }
}

// ASO Dashboard Component
const ASODashboard = () => {
  const [asoTester] = useState(() => new ASOTestingPlatform());
  const [activeTests, setActiveTests] = useState([]);
  const [testResults, setTestResults] = useState([]);
  const [conversionFunnel, setConversionFunnel] = useState(null);
  const [newTestConfig, setNewTestConfig] = useState({
    name: '',
    type: 'title',
    variants: { variant_a: '', variant_b: '' },
    duration: 14 * 24 * 60 * 60 * 1000 // 14 days
  });

  useEffect(() => {
    loadASOData();
    
    // Simulate real-time data updates
    const interval = setInterval(() => {
      updateTestMetrics();
    }, 30000);

    return () => clearInterval(interval);
  }, []);

  const loadASOData = async () => {
    // Load active tests
    const tests = Array.from(asoTester.activeTests.values());
    setActiveTests(tests);

    // Load test results
    const results = Array.from(asoTester.testResults.values());
    setTestResults(results);

    // Load conversion funnel
    const funnel = asoTester.generateFunnelReport('app_store_conversion');
    setConversionFunnel(funnel);
  };

  const updateTestMetrics = () => {
    // Simulate incoming metrics data
    activeTests.forEach(test => {
      if (test.status === 'active') {
        // Simulate random metrics updates
        const impressionsA = Math.floor(Math.random() * 50) + 10;
        const impressionsB = Math.floor(Math.random() * 50) + 10;
        const conversionsA = Math.floor(impressionsA * (0.03 + Math.random() * 0.05));
        const conversionsB = Math.floor(impressionsB * (0.03 + Math.random() * 0.05));

        asoTester.recordTestMetric(test.id, 'variant_a', 'impressions', impressionsA);
        asoTester.recordTestMetric(test.id, 'variant_a', 'conversions', conversionsA);
        asoTester.recordTestMetric(test.id, 'variant_b', 'impressions', impressionsB);
        asoTester.recordTestMetric(test.id, 'variant_b', 'conversions', conversionsB);
      }
    });

    loadASOData();
  };

  const createNewTest = async () => {
    if (!newTestConfig.name || !newTestConfig.variants.variant_a || !newTestConfig.variants.variant_b) {
      Alert.alert('Error', 'Please fill in all test configuration fields');
      return;
    }

    try {
      const test = await asoTester.createABTest({
        ...newTestConfig,
        baselineConversionRate: 0.05,
        minimumDetectableEffect: 0.2
      });

      Alert.alert('Success', `A/B test "${test.name}" created successfully`);
      setNewTestConfig({ name: '', type: 'title', variants: { variant_a: '', variant_b: '' } });
      loadASOData();
    } catch (error) {
      Alert.alert('Error', `Failed to create test: ${error.message}`);
    }
  };

  const TestResultCard = ({ test }) => (
    <View style={styles.testCard}>
      <Text style={styles.testName}>{test.name}</Text>
      <Text style={styles.testType}>{test.type.toUpperCase()} TEST</Text>
      
      <View style={styles.testResults}>
        <View style={styles.variantResult}>
          <Text style={styles.variantLabel}>Variant A</Text>
          <Text style={styles.conversionRate}>
            {(test.results.variant_a.rate * 100).toFixed(2)}%
          </Text>
          <Text style={styles.sampleSize}>
            ({test.results.variant_a.conversions}/{test.results.variant_a.impressions})
          </Text>
        </View>
        
        <Text style={styles.vsText}>VS</Text>
        
        <View style={styles.variantResult}>
          <Text style={styles.variantLabel}>Variant B</Text>
          <Text style={styles.conversionRate}>
            {(test.results.variant_b.rate * 100).toFixed(2)}%
          </Text>
          <Text style={styles.sampleSize}>
            ({test.results.variant_b.conversions}/{test.results.variant_b.impressions})
          </Text>
        </View>
      </View>
      
      <View style={styles.testStatus}>
        <Text style={[styles.statusText, { 
          color: test.status === 'active' ? '#f39c12' : '#2ecc71' 
        }]}>
          {test.status.toUpperCase()}
        </Text>
        
        {test.statisticalSignificance.achieved && (
          <Text style={styles.significanceText}>
            ✅ {test.statisticalSignificance.confidenceLevel}% Confidence
          </Text>
        )}
      </View>
    </View>
  );

  return (
    <ScrollView style={styles.dashboard}>
      <Text style={styles.dashboardTitle}>App Store Optimization Dashboard</Text>
      
      {/* Create New Test */}
      <View style={styles.createTestSection}>
        <Text style={styles.sectionTitle}>Create A/B Test</Text>
        
        <TextInput
          style={styles.input}
          placeholder="Test Name"
          value={newTestConfig.name}
          onChangeText={(text) => setNewTestConfig(prev => ({ ...prev, name: text }))}
        />
        
        <TextInput
          style={styles.input}
          placeholder="Variant A"
          value={newTestConfig.variants.variant_a}
          onChangeText={(text) => setNewTestConfig(prev => ({ 
            ...prev, 
            variants: { ...prev.variants, variant_a: text }
          }))}
        />
        
        <TextInput
          style={styles.input}
          placeholder="Variant B"
          value={newTestConfig.variants.variant_b}
          onChangeText={(text) => setNewTestConfig(prev => ({ 
            ...prev, 
            variants: { ...prev.variants, variant_b: text }
          }))}
        />
        
        <TouchableOpacity style={styles.createButton} onPress={createNewTest}>
          <Text style={styles.createButtonText}>Create Test</Text>
        </TouchableOpacity>
      </View>

      {/* Active Tests */}
      <View style={styles.testsSection}>
        <Text style={styles.sectionTitle}>Active Tests</Text>
        
        {activeTests.map(test => (
          <TestResultCard key={test.id} test={test} />
        ))}
      </View>

      {/* Conversion Funnel */}
      {conversionFunnel && (
        <View style={styles.funnelSection}>
          <Text style={styles.sectionTitle}>App Store Conversion Funnel</Text>
          
          <View style={styles.funnelStats}>
            <Text>Total Users: {conversionFunnel.totalUsers}</Text>
            
            {Array.from(conversionFunnel.stepConversions.entries()).map(([step, rate]) => (
              <View key={step} style={styles.funnelStep}>
                <Text style={styles.funnelStepName}>{step}</Text>
                <Text style={styles.funnelStepRate}>{rate.toFixed(1)}%</Text>
              </View>
            ))}
          </View>
          
          {conversionFunnel.recommendations.map((rec, index) => (
            <View key={index} style={styles.recommendationCard}>
              <Text style={styles.recommendationTitle}>{rec.issue}</Text>
              {rec.suggestions.map((suggestion, sIndex) => (
                <Text key={sIndex} style={styles.suggestionText}>• {suggestion}</Text>
              ))}
            </View>
          ))}
        </View>
      )}
    </ScrollView>
  );
};

// Advanced ASO features
class AdvancedASOPlatform extends ASOTestingPlatform {
  constructor() {
    super();
    this.seasonalTrends = new Map();
    this.localizedOptimization = new Map();
    this.reviewAnalytics = new Map();
    this.rankingTracker = new Map();
  }

  // Seasonal optimization
  analyzeSeasonalTrends(category, timeframe = '2years') {
    const trends = {
      monthly: new Map(),
      holidays: new Map(),
      events: new Map(),
      predictions: new Map()
    };

    // Analyze monthly patterns
    const monthlyData = this.getMonthlyDownloadData(category, timeframe);
    for (const [month, data] of monthlyData.entries()) {
      trends.monthly.set(month, {
        averageDownloads: data.downloads / data.years,
        growthRate: data.yearOverYearGrowth,
        competitionLevel: data.competitorCount
      });
    }

    // Identify holiday impacts
    const holidays = ['new_year', 'valentine', 'summer', 'black_friday', 'christmas'];
    holidays.forEach(holiday => {
      const impact = this.calculateHolidayImpact(category, holiday);
      trends.holidays.set(holiday, impact);
    });

    // Generate seasonal optimization strategies
    const strategies = this.generateSeasonalStrategies(trends);
    
    return { trends, strategies };
  }

  generateSeasonalStrategies(trends) {
    const strategies = [];

    // Peak season strategies
    const peakMonths = Array.from(trends.monthly.entries())
      .sort(([,a], [,b]) => b.averageDownloads - a.averageDownloads)
      .slice(0, 3);

    peakMonths.forEach(([month, data]) => {
      strategies.push({
        type: 'peak_season',
        month: month,
        strategy: 'maximize_visibility',
        actions: [
          'Increase ad spend by 30-50%',
          'Launch seasonal A/B tests',
          'Update screenshots with seasonal themes',
          'Optimize for seasonal keywords'
        ],
        expectedLift: `${(data.growthRate * 100).toFixed(1)}%`
      });
    });

    // Off-season strategies
    const lowMonths = Array.from(trends.monthly.entries())
      .sort(([,a], [,b]) => a.averageDownloads - b.averageDownloads)
      .slice(0, 2);

    lowMonths.forEach(([month, data]) => {
      strategies.push({
        type: 'off_season',
        month: month,
        strategy: 'optimize_retention',
        actions: [
          'Focus on user retention campaigns',
          'Test new feature messaging',
          'Optimize for long-tail keywords',
          'Improve app quality and ratings'
        ],
        expectedLift: 'Maintain market position'
      });
    });

    return strategies;
  }

  // Localized ASO optimization
  async optimizeForLocalization(targetCountries) {
    const localizationPlan = {
      countries: new Map(),
      keywords: new Map(),
      culturalAdaptations: new Map(),
      priorityMarkets: []
    };

    for (const country of targetCountries) {
      const marketAnalysis = await this.analyzeLocalMarket(country);
      
      localizationPlan.countries.set(country, {
        marketSize: marketAnalysis.totalUsers,
        competitionLevel: marketAnalysis.competitorCount,
        averageCPI: marketAnalysis.costPerInstall,
        topCategories: marketAnalysis.popularCategories,
        culturalNotes: marketAnalysis.culturalConsiderations
      });

      // Localized keyword research
      const localKeywords = await this.researchLocalKeywords(country);
      localizationPlan.keywords.set(country, localKeywords);

      // Cultural adaptations needed
      const adaptations = this.identifyCulturalAdaptations(country, marketAnalysis);
      localizationPlan.culturalAdaptations.set(country, adaptations);
    }

    // Prioritize markets by opportunity score
    localizationPlan.priorityMarkets = this.prioritizeMarkets(localizationPlan.countries);

    return localizationPlan;
  }

  async researchLocalKeywords(country) {
    const localKeywords = {
      primary: [],
      translated: [],
      cultural: [],
      trending: []
    };

    // Get local language equivalents
    const translatedKeywords = await this.translateKeywords(this.baseKeywords, country);
    localKeywords.translated = translatedKeywords;

    // Research local trending terms
    const trendingTerms = await this.getLocalTrendingTerms(country);
    localKeywords.trending = trendingTerms;

    // Identify cultural keywords specific to region
    const culturalTerms = this.getCulturalKeywords(country);
    localKeywords.cultural = culturalTerms;

    // Combine and score keywords
    localKeywords.primary = this.combineAndScoreKeywords(
      localKeywords.translated,
      localKeywords.trending,
      localKeywords.cultural
    );

    return localKeywords;
  }

  // Advanced review analytics
  analyzeReviewSentiment(reviews) {
    const analysis = {
      overall: {
        sentiment: 0, // -1 to 1
        confidence: 0,
        totalReviews: reviews.length
      },
      topics: new Map(),
      trends: {
        positive: [],
        negative: [],
        neutral: []
      },
      actionableInsights: []
    };

    // Sentiment analysis for each review
    reviews.forEach(review => {
      const sentiment = this.calculateSentiment(review.text);
      const topics = this.extractTopics(review.text);
      
      // Add to overall sentiment
      analysis.overall.sentiment += sentiment.score;
      
      // Track topics and their sentiment
      topics.forEach(topic => {
        if (!analysis.topics.has(topic)) {
          analysis.topics.set(topic, {
            mentions: 0,
            averageSentiment: 0,
            examples: []
          });
        }
        
        const topicData = analysis.topics.get(topic);
        topicData.mentions++;
        topicData.averageSentiment = 
          (topicData.averageSentiment + sentiment.score) / topicData.mentions;
        topicData.examples.push(review.text.substring(0, 100) + '...');
      });
    });

    // Calculate overall sentiment
    analysis.overall.sentiment /= reviews.length;
    analysis.overall.confidence = this.calculateSentimentConfidence(reviews);

    // Generate actionable insights
    analysis.actionableInsights = this.generateReviewInsights(analysis.topics);

    return analysis;
  }

  generateReviewInsights(topics) {
    const insights = [];

    // Find most negative topics
    const negativeTopics = Array.from(topics.entries())
      .filter(([, data]) => data.averageSentiment < -0.3 && data.mentions > 5)
      .sort(([,a], [,b]) => a.averageSentiment - b.averageSentiment);

    negativeTopics.forEach(([topic, data]) => {
      insights.push({
        type: 'negative_feedback',
        priority: 'high',
        topic: topic,
        issue: `Negative sentiment around "${topic}" (${data.mentions} mentions)`,
        recommendation: this.getTopicRecommendation(topic, 'negative'),
        examples: data.examples.slice(0, 3)
      });
    });

    // Find most positive topics
    const positiveTopics = Array.from(topics.entries())
      .filter(([, data]) => data.averageSentiment > 0.5 && data.mentions > 3)
      .sort(([,a], [,b]) => b.averageSentiment - a.averageSentiment);

    positiveTopics.slice(0, 3).forEach(([topic, data]) => {
      insights.push({
        type: 'positive_feedback',
        priority: 'medium',
        topic: topic,
        issue: `Strong positive sentiment for "${topic}"`,
        recommendation: `Highlight "${topic}" in app store listing and marketing`,
        examples: data.examples.slice(0, 2)
      });
    });

    return insights;
  }

  // Ranking tracking and optimization
  trackAppRankings(keywords, categories) {
    const rankingData = {
      timestamp: Date.now(),
      keywords: new Map(),
      categories: new Map(),
      changes: new Map(),
      trends: new Map()
    };

    // Track keyword rankings
    keywords.forEach(keyword => {
      const currentRank = this.getCurrentKeywordRank(keyword);
      const previousRank = this.getPreviousKeywordRank(keyword);
      const change = previousRank ? previousRank - currentRank : 0;

      rankingData.keywords.set(keyword, {
        current: currentRank,
        previous: previousRank,
        change: change,
        trend: this.calculateRankingTrend(keyword, 30) // 30-day trend
      });

      rankingData.changes.set(keyword, change);
    });

    // Track category rankings
    categories.forEach(category => {
      const currentRank = this.getCurrentCategoryRank(category);
      const previousRank = this.getPreviousCategoryRank(category);
      const change = previousRank ? previousRank - currentRank : 0;

      rankingData.categories.set(category, {
        current: currentRank,
        previous: previousRank,
        change: change
      });
    });

    // Store ranking data
    this.rankingTracker.set(Date.now(), rankingData);

    // Generate ranking alerts
    this.checkRankingAlerts(rankingData);

    return rankingData;
  }

  checkRankingAlerts(rankingData) {
    const alerts = [];

    // Check for significant drops
    rankingData.changes.forEach((change, keyword) => {
      if (change < -10) { // Dropped more than 10 positions
        alerts.push({
          type: 'ranking_drop',
          severity: change < -25 ? 'critical' : 'warning',
          keyword: keyword,
          change: change,
          recommendation: 'Review recent ASO changes and competitor activity'
        });
      } else if (change > 10) { // Improved more than 10 positions
        alerts.push({
          type: 'ranking_improvement',
          severity: 'info',
          keyword: keyword,
          change: change,
          recommendation: 'Analyze what caused this improvement and apply to other keywords'
        });
      }
    });

    // Send alerts to monitoring system
    alerts.forEach(alert => this.sendRankingAlert(alert));

    return alerts;
  }

  // Automated ASO recommendations
  generateASORecommendations(appData, competitorData, performanceData) {
    const recommendations = {
      immediate: [], // Can implement right away
      testing: [],   // Should A/B test
      longTerm: []   // Requires significant changes
    };

    // Title optimization
    if (appData.title.length > 30) {
      recommendations.immediate.push({
        category: 'title',
        priority: 'high',
        issue: 'Title too long for iOS',
        action: 'Shorten title to under 30 characters',
        impact: 'Better visibility on iOS App Store'
      });
    }

    // Keyword optimization
    const keywordGaps = this.findKeywordGaps(appData.keywords, competitorData);
    if (keywordGaps.length > 0) {
      recommendations.testing.push({
        category: 'keywords',
        priority: 'high',
        issue: `Missing ${keywordGaps.length} high-opportunity keywords`,
        action: `A/B test including keywords: ${keywordGaps.slice(0, 3).join(', ')}`,
        impact: 'Potential 15-30% increase in organic discovery'
      });
    }

    // Screenshot optimization
    if (!appData.screenshots || appData.screenshots.length < 5) {
      recommendations.immediate.push({
        category: 'screenshots',
        priority: 'medium',
        issue: 'Insufficient screenshots',
        action: 'Add more screenshots showcasing key features',
        impact: 'Improved conversion rate from store listing views'
      });
    }

    // Conversion rate optimization
    if (performanceData.conversionRate < 0.3) {
      recommendations.testing.push({
        category: 'conversion',
        priority: 'critical',
        issue: `Low conversion rate (${(performanceData.conversionRate * 100).toFixed(1)}%)`,
        action: 'A/B test app icon, first screenshot, and value proposition',
        impact: 'Could double or triple install rate'
      });
    }

    // Rating and review optimization
    if (performanceData.averageRating < 4.0) {
      recommendations.longTerm.push({
        category: 'quality',
        priority: 'critical',
        issue: `Low average rating (${performanceData.averageRating})`,
        action: 'Address top user complaints and implement feedback',
        impact: 'Improved ratings lead to better rankings and conversion'
      });
    }

    return recommendations;
  }
}

// Usage example
const advancedASO = new AdvancedASOPlatform();

// Seasonal optimization
const seasonalAnalysis = advancedASO.analyzeSeasonalTrends('fitness');
console.log('Seasonal Strategies:', seasonalAnalysis.strategies);

// Localization planning
const localizationPlan = advancedASO.optimizeForLocalization(['DE', 'FR', 'ES', 'JP']);
console.log('Priority Markets:', localizationPlan.priorityMarkets);

// ASO Performance Dashboard
const ASOPerformanceDashboard = () => {
  const [performanceData, setPerformanceData] = useState({});
  const [rankings, setRankings] = useState(new Map());
  const [recommendations, setRecommendations] = useState([]);
  const [competitorData, setCompetitorData] = useState([]);

  useEffect(() => {
    loadPerformanceData();
    
    const interval = setInterval(() => {
      updateRankings();
    }, 3600000); // Update hourly

    return () => clearInterval(interval);
  }, []);

  const loadPerformanceData = async () => {
    // Simulate loading ASO performance data
    const data = {
      visibility: {
        totalImpressions: 125000,
        uniqueUsers: 95000,
        impressionTrend: [120000, 118000, 125000, 130000, 127000],
        topKeywords: [
          { keyword: 'fitness tracker', rank: 12, impressions: 25000 },
          { keyword: 'workout app', rank: 8, impressions: 18000 },
          { keyword: 'exercise planner', rank: 22, impressions: 12000 }
        ]
      },
      conversion: {
        overallRate: 0.078, // 7.8%
        rateBySource: new Map([
          ['organic', 0.085],
          ['search_ads', 0.065],
          ['featured', 0.120]
        ]),
        conversionFunnel: [
          { step: 'Impression', users: 125000, rate: 100 },
          { step: 'Store Visit', users: 45000, rate: 36 },
          { step: 'Screenshot View', users: 28000, rate: 62 },
          { step: 'Description Read', users: 15000, rate: 54 },
          { step: 'Install', users: 9750, rate: 65 }
        ]
      },
      ratings: {
        average: 4.3,
        totalCount: 2847,
        distribution: { 5: 1520, 4: 892, 3: 285, 2: 98, 1: 52 },
        recentTrend: [4.1, 4.2, 4.25, 4.3, 4.32]
      }
    };

    setPerformanceData(data);

    // Generate recommendations
    const recs = generatePerformanceRecommendations(data);
    setRecommendations(recs);
  };

  const generatePerformanceRecommendations = (data) => {
    const recs = [];

    // Conversion rate analysis
    if (data.conversion.overallRate < 0.05) {
      recs.push({
        category: 'Conversion',
        priority: 'Critical',
        issue: 'Very low conversion rate',
        recommendation: 'Optimize app icon, first screenshot, and title',
        expectedImpact: '+50-100% conversion rate'
      });
    }

    // Funnel analysis
    const funnelDropOffs = data.conversion.conversionFunnel.map((step, index) => {
      if (index === 0) return { step: step.step, dropOff: 0 };
      const prevStep = data.conversion.conversionFunnel[index - 1];
      return {
        step: step.step,
        dropOff: ((prevStep.users - step.users) / prevStep.users) * 100
      };
    });

    const highestDropOff = funnelDropOffs.reduce((max, current) => 
      current.dropOff > max.dropOff ? current : max
    );

    if (highestDropOff.dropOff > 60) {
      recs.push({
        category: 'Funnel Optimization',
        priority: 'High',
        issue: `High drop-off at ${highestDropOff.step} (${highestDropOff.dropOff.toFixed(1)}%)`,
        recommendation: getFunnelOptimizationAdvice(highestDropOff.step),
        expectedImpact: `+${Math.round(highestDropOff.dropOff * 0.3)}% overall conversion`
      });
    }

    // Rating optimization
    if (data.ratings.average < 4.0) {
      recs.push({
        category: 'Quality',
        priority: 'High',
        issue: `Low rating (${data.ratings.average})`,
        recommendation: 'Address top user complaints and improve app quality',
        expectedImpact: 'Better rankings and conversion rates'
      });
    }

    return recs;
  };

  const getFunnelOptimizationAdvice = (step) => {
    const advice = {
      'Store Visit': 'Improve keyword targeting and app store presence',
      'Screenshot View': 'Optimize app icon and title to increase interest',
      'Description Read': 'Make screenshots more compelling and informative',
      'Install': 'Improve app description, address concerns in reviews'
    };

    return advice[step] || 'Analyze user behavior at this step';
  };

  const RankingChart = ({ rankings }) => (
    <View style={styles.chartContainer}>
      <Text style={styles.chartTitle}>Keyword Rankings</Text>
      {Array.from(rankings.entries()).map(([keyword, data]) => (
        <View key={keyword} style={styles.rankingItem}>
          <Text style={styles.keywordText}>{keyword}</Text>
          <View style={styles.rankingInfo}>
            <Text style={[styles.rankText, { 
              color: data.change > 0 ? '#2ecc71' : data.change < 0 ? '#e74c3c' : '#95a5a6' 
            }]}>
              #{data.current}
            </Text>
            {data.change !== 0 && (
              <Text style={[styles.changeText, { 
                color: data.change > 0 ? '#2ecc71' : '#e74c3c' 
              }]}>
                {data.change > 0 ? '+' : ''}{data.change}
              </Text>
            )}
          </View>
        </View>
      ))}
    </View>
  );

  const ConversionFunnel = ({ funnel }) => (
    <View style={styles.funnelContainer}>
      <Text style={styles.funnelTitle}>Conversion Funnel</Text>
      {funnel.map((step, index) => {
        const barWidth = (step.rate / 100) * 300;
        return (
          <View key={step.step} style={styles.funnelStep}>
            <View style={styles.funnelStepInfo}>
              <Text style={styles.funnelStepName}>{step.step}</Text>
              <Text style={styles.funnelStepStats}>
                {step.users.toLocaleString()} users ({step.rate}%)
              </Text>
            </View>
            <View style={styles.funnelBar}>
              <View style={[styles.funnelBarFill, { width: barWidth }]} />
            </View>
          </View>
        );
      })}
    </View>
  );

  const RecommendationCard = ({ rec }) => (
    <View style={[styles.recCard, styles[`priority${rec.priority}`]]}>
      <View style={styles.recHeader}>
        <Text style={styles.recCategory}>{rec.category}</Text>
        <Text style={styles.recPriority}>{rec.priority}</Text>
      </View>
      <Text style={styles.recIssue}>{rec.issue}</Text>
      <Text style={styles.recAction}>{rec.recommendation}</Text>
      <Text style={styles.recImpact}>Expected Impact: {rec.expectedImpact}</Text>
    </View>
  );

  if (!performanceData.visibility) {
    return (
      <View style={styles.loadingContainer}>
        <Text>Loading ASO performance data...</Text>
      </View>
    );
  }

  return (
    <ScrollView style={styles.dashboard}>
      <Text style={styles.dashboardTitle}>ASO Performance Dashboard</Text>
      
      {/* Key Metrics Overview */}
      <View style={styles.metricsOverview}>
        <View style={styles.metricCard}>
          <Text style={styles.metricTitle}>Visibility</Text>
          <Text style={styles.metricValue}>
            {performanceData.visibility.totalImpressions.toLocaleString()}
          </Text>
          <Text style={styles.metricLabel}>Total Impressions</Text>
        </View>
        
        <View style={styles.metricCard}>
          <Text style={styles.metricTitle}>Conversion</Text>
          <Text style={styles.metricValue}>
            {(performanceData.conversion.overallRate * 100).toFixed(1)}%
          </Text>
          <Text style={styles.metricLabel}>Install Rate</Text>
        </View>
        
        <View style={styles.metricCard}>
          <Text style={styles.metricTitle}>Quality</Text>
          <Text style={styles.metricValue}>{performanceData.ratings.average}</Text>
          <Text style={styles.metricLabel}>Avg Rating</Text>
        </View>
      </View>

      {/* Keyword Rankings */}
      <RankingChart rankings={rankings} />

      {/* Conversion Funnel */}
      <ConversionFunnel funnel={performanceData.conversion.conversionFunnel} />

      {/* Recommendations */}
      <View style={styles.recommendationsSection}>
        <Text style={styles.sectionTitle}>Optimization Recommendations</Text>
        {recommendations.map((rec, index) => (
          <RecommendationCard key={index} rec={rec} />
        ))}
      </View>

      {/* Export Controls */}
      <View style={styles.exportSection}>
        <TouchableOpacity style={styles.exportButton}>
          <Text style={styles.exportButtonText}>📊 Export Report</Text>
        </TouchableOpacity>
        
        <TouchableOpacity style={styles.exportButton}>
          <Text style={styles.exportButtonText}>📧 Schedule Report</Text>
        </TouchableOpacity>
      </View>
    </ScrollView>
  );
};