Best Five9 Phone Validation API & Contact Center Integration 2025

// Advanced Five9 contact center optimization
class Five9ContactCenterOptimizer {
  constructor(five9Client, oneLookupClient) {
    this.five9 = five9Client;
    this.lookup = oneLookupClient;
  }

  async optimizeContactCenter(optimization) {
    console.log('Starting Five9 contact center optimization');

    // Analyze current performance
    const currentPerformance = await this.analyzeCurrentPerformance();
    
    // Optimize campaigns
    const campaignOptimizations = await this.optimizeCampaigns(currentPerformance);
    
    // Optimize workforce allocation
    const workforceOptimizations = await this.optimizeWorkforce(currentPerformance);
    
    // Implement optimizations
    await this.implementOptimizations(campaignOptimizations, workforceOptimizations);

    return {
      currentPerformance: currentPerformance,
      campaignOptimizations: campaignOptimizations,
      workforceOptimizations: workforceOptimizations,
      projectedImprovement: this.calculateProjectedImprovement(currentPerformance)
    };
  }

  async analyzeCurrentPerformance() {
    const campaigns = await this.five9.configuration.getCampaigns();
    const agents = await this.five9.configuration.getAgents();
    const callStats = await this.five9.statistics.getCallStatistics();

    const analysis = {
      totalCampaigns: campaigns.length,
      activeCampaigns: campaigns.filter(c => c.state === 'RUNNING').length,
      totalAgents: agents.length,
      availableAgents: agents.filter(a => a.state === 'READY').length,
      callMetrics: {
        totalCalls: callStats.totalCalls,
        connectedCalls: callStats.connectedCalls,
        connectionRate: (callStats.connectedCalls / callStats.totalCalls * 100).toFixed(2),
        avgHandleTime: callStats.avgHandleTime,
        abandonmentRate: (callStats.abandonedCalls / callStats.totalCalls * 100).toFixed(2)
      },
      contactQuality: await this.assessContactQuality(campaigns)
    };

    return analysis;
  }

  async optimizeCampaigns(performance) {
    const optimizations = [];

    for (const campaign of performance.campaigns) {
      if (campaign.connectionRate < 30) {
        // Low connection rate - optimize contact list
        const contactOptimization = await this.optimizeCampaignContacts(campaign.id);
        optimizations.push({
          campaignId: campaign.id,
          type: 'contact_optimization',
          action: 'validate_and_score_contacts',
          expectedImprovement: contactOptimization.projectedImprovement
        });
      }

      if (campaign.abandonmentRate > 5) {
        // High abandonment - optimize agent availability
        optimizations.push({
          campaignId: campaign.id,
          type: 'agent_optimization',
          action: 'increase_agent_staffing',
          recommendedStaffing: this.calculateOptimalStaffing(campaign)
        });
      }
    }

    return optimizations;
  }

  async optimizeCampaignContacts(campaignId) {
    const contacts = await this.five9.configuration.getCampaignContacts(campaignId);
    const validatedContacts = [];

    for (const contact of contacts) {
      const validation = await this.lookup.phone.validate({
        phone: contact.number1,
        includeCarrierInfo: true,
        includeConnectionProbability: true,
        includeLeadScoring: true
      });

      if (validation.isValid && validation.connectionProbability > 0.3) {
        const leadScore = await this.calculateContactCenterLeadScore(validation, contact);
        
        validatedContacts.push({
          ...contact,
          leadScore: leadScore,
          connectionProbability: validation.connectionProbability,
          optimalCallTime: validation.optimalTiming,
          validation: validation
        });
      }
    }

    // Sort by lead score and connection probability
    validatedContacts.sort((a, b) => {
      const scoreA = (a.leadScore * 0.7) + (a.connectionProbability * 30);
      const scoreB = (b.leadScore * 0.7) + (b.connectionProbability * 30);
      return scoreB - scoreA;
    });

    // Update Five9 with optimized contact order
    await this.updateCampaignContactOrder(campaignId, validatedContacts);

    const projectedImprovement = this.calculateContactListImprovement(
      contacts.length,
      validatedContacts.length,
      validatedContacts
    );

    return {
      originalContacts: contacts.length,
      optimizedContacts: validatedContacts.length,
      projectedImprovement: projectedImprovement
    };
  }

  async calculateContactCenterLeadScore(validation, contact) {
    let score = 50;

    // Phone validation quality
    if (validation.isValid) score += 20;
    if (validation.confidence > 90) score += 10;

    // Connection probability
    score += (validation.connectionProbability * 25);

    // Carrier quality for contact centers
    if (validation.carrierInfo && validation.carrierInfo.contactCenterFriendly) {
      score += 15;
    }

    // Contact history
    if (contact.call_history && contact.call_history.length > 0) {
      const recentSuccessRate = this.calculateRecentSuccessRate(contact.call_history);
      score += (recentSuccessRate * 20);
    }

    // Geographic factors
    if (validation.locationInfo && validation.locationInfo.businessHours) {
      score += 10;
    }

    return Math.max(0, Math.min(100, Math.round(score)));
  }

  calculateContactListImprovement(originalCount, optimizedCount, optimizedContacts) {
    const avgLeadScore = optimizedContacts.reduce((sum, c) => sum + c.leadScore, 0) / optimizedContacts.length;
    const avgConnectionProb = optimizedContacts.reduce((sum, c) => sum + c.connectionProbability, 0) / optimizedContacts.length;

    // Estimate improvement based on data quality
    const qualityImprovement = (avgLeadScore - 50) / 50; // 50 is baseline
    const connectionImprovement = (avgConnectionProb - 0.25) / 0.25; // 25% baseline

    const overallImprovement = (qualityImprovement + connectionImprovement) / 2;

    return {
      qualityScore: avgLeadScore.toFixed(1),
      connectionProbability: (avgConnectionProb * 100).toFixed(1) + '%',
      estimatedImprovementPercent: (overallImprovement * 100).toFixed(1) + '%',
      contactRetentionRate: ((optimizedCount / originalCount) * 100).toFixed(1) + '%'
    };
  }
}