Best ConnectLeader Phone Validation API & Predictive Dialer Integration 2025

// Advanced predictive campaign management
class ConnectLeaderCampaignManager {
  constructor(connectLeaderAPI, oneLookupClient) {
    this.cl = connectLeaderAPI;
    this.lookup = oneLookupClient;
    this.mlModel = new PredictiveDialingModel();
  }

  async optimizePredictiveCampaign(campaignId, goals) {
    console.log(`Starting predictive optimization for campaign ${campaignId}`);
    
    const campaign = await this.cl.getCampaign(campaignId);
    const contacts = await this.cl.getCampaignContacts(campaignId);
    const agents = await this.cl.getAvailableAgents();

    // Analyze all contacts for predictive dialing
    const analysis = await this.analyzeContactsForPredictive(contacts, goals);
    
    // Optimize dialing algorithm parameters
    const dialingParams = await this.optimizeDialingParameters(analysis, agents);
    
    // Create predictive dialing strategy
    const strategy = await this.createPredictiveStrategy(analysis, dialingParams, goals);
    
    // Apply optimizations
    await this.applyOptimizations(campaignId, strategy);

    return {
      campaignName: campaign.name,
      optimization: strategy,
      expectedResults: this.projectResults(analysis, strategy),
      recommendations: this.generateRecommendations(analysis, strategy)
    };
  }

  async analyzeContactsForPredictive(contacts, goals) {
    const analysis = {
      total: contacts.length,
      qualified: 0,
      highPriority: 0,
      mediumPriority: 0,
      lowPriority: 0,
      nonCompliant: 0,
      insights: []
    };

    const batchSize = 100;
    const processedContacts = [];

    for (let i = 0; i < contacts.length; i += batchSize) {
      const batch = contacts.slice(i, i + batchSize);
      
      const batchResults = await Promise.allSettled(
        batch.map(contact => this.analyzeContactForPredictive(contact, goals))
      );

      for (let j = 0; j < batchResults.length; j++) {
        const result = batchResults[j];
        const contact = batch[j];

        if (result.status === 'fulfilled' && result.value) {
          const contactAnalysis = result.value;
          processedContacts.push({
            ...contact,
            ...contactAnalysis
          });

          // Update analysis counters
          if (contactAnalysis.qualified) {
            analysis.qualified++;
            
            switch (contactAnalysis.priority) {
              case 'high':
                analysis.highPriority++;
                break;
              case 'medium':
                analysis.mediumPriority++;
                break;
              default:
                analysis.lowPriority++;
            }
          }

          if (!contactAnalysis.compliant) {
            analysis.nonCompliant++;
          }

        } else {
          console.error(`Failed to analyze contact ${contact.id}:`, result.reason);
        }
      }

      // Rate limiting
      await new Promise(resolve => setTimeout(resolve, 100));
    }

    analysis.contacts = processedContacts;
    analysis.insights = this.generateAnalysisInsights(processedContacts);
    
    return analysis;
  }

  async analyzeContactForPredictive(contact, goals) {
    try {
      const validation = await this.lookup.phone.validateForPredictive({
        phone: contact.phoneNumber,
        includeCarrierInfo: true,
        includeConnectionProbability: true,
        includePredictiveInsights: true,
        includeComplianceCheck: true,
        context: {
          goals: goals,
          contactData: contact
        }
      });

      if (!validation.isValid) {
        return {
          qualified: false,
          reason: 'Invalid phone number',
          validation: validation
        };
      }

      // Predictive scoring
      const predictiveScore = await this.calculatePredictiveScore(validation, contact, goals);
      
      // Connection probability analysis
      const connectionAnalysis = await this.analyzeConnectionProbability(validation, contact);
      
      // Optimal timing calculation
      const timingAnalysis = await this.calculateOptimalTiming(validation, contact);

      return {
        qualified: predictiveScore.score > 60,
        predictiveScore: predictiveScore.score,
        priority: this.determinePriority(predictiveScore.score),
        connectionProbability: connectionAnalysis.probability,
        expectedCallDuration: connectionAnalysis.estimatedDuration,
        optimalCallTime: timingAnalysis.optimalTime,
        dialingRecommendations: timingAnalysis.recommendations,
        compliant: validation.compliance.isCompliant,
        validation: validation
      };

    } catch (error) {
      console.error(`Contact analysis failed for ${contact.id}:`, error);
      return {
        qualified: false,
        reason: 'Analysis failed',
        error: error.message
      };
    }
  }

  async calculatePredictiveScore(validation, contact, goals) {
    let score = 50; // Base score

    // Phone validation quality (25 points)
    if (validation.isValid) score += 20;
    if (validation.confidence > 90) score += 5;

    // Connection probability (30 points)
    score += (validation.connectionProbability * 30);

    // Carrier compatibility for predictive dialing (15 points)
    if (validation.carrierInfo) {
      if (validation.carrierInfo.predictiveDialingOptimal) score += 15;
      else if (validation.carrierInfo.predictiveDialingCompatible) score += 10;
    }

    // Contact quality indicators (20 points)
    if (contact.previousConnections > 0) {
      const connectionRate = contact.successfulConnections / contact.previousConnections;
      score += (connectionRate * 20);
    }

    // Goals alignment (10 points)
    if (goals.targetDemographic && validation.demographics) {
      const alignment = this.calculateDemographicAlignment(
        validation.demographics, 
        goals.targetDemographic
      );
      score += (alignment * 10);
    }

    return {
      score: Math.max(0, Math.min(100, Math.round(score))),
      factors: {
        validation: validation.isValid ? 20 : 0,
        connection: Math.round(validation.connectionProbability * 30),
        carrier: validation.carrierInfo?.predictiveDialingOptimal ? 15 : 0,
        history: contact.previousConnections > 0 ? Math.round((contact.successfulConnections / contact.previousConnections) * 20) : 0
      }
    };
  }

  async optimizeDialingParameters(analysis, agents) {
    const totalQualified = analysis.qualified;
    const avgConnectionProb = analysis.contacts
      .filter(c => c.qualified)
      .reduce((sum, c) => sum + c.connectionProbability, 0) / totalQualified;

    const avgCallDuration = analysis.contacts
      .filter(c => c.qualified && c.expectedCallDuration)
      .reduce((sum, c) => sum + c.expectedCallDuration, 0) / totalQualified;

    // Calculate optimal dialing ratio
    const dialingRatio = this.calculateOptimalDialingRatio(
      avgConnectionProb,
      avgCallDuration,
      agents.length
    );

    // Determine pacing algorithm
    const pacingAlgorithm = this.selectPacingAlgorithm(analysis, agents);

    return {
      dialingRatio: dialingRatio,
      pacingAlgorithm: pacingAlgorithm,
      maxConcurrentCalls: Math.ceil(agents.length * dialingRatio),
      avgConnectionProbability: avgConnectionProb,
      avgExpectedDuration: avgCallDuration,
      recommendedAgentUtilization: 0.85
    };
  }

  calculateOptimalDialingRatio(connectionProb, avgDuration, agentCount) {
    // Advanced algorithm for calculating optimal dialing ratio
    const baseRatio = 1.0 / connectionProb;
    const durationAdjustment = (avgDuration / 180); // 3 minutes baseline
    const agentAdjustment = Math.min(1.2, agentCount / 10); // Scale with agent count
    
    return Math.max(1.1, Math.min(4.0, baseRatio * durationAdjustment * agentAdjustment));
  }
}