Configuring Genesys Cloud Predictive Engagement via API with TypeScript

What You Will Build

• You will build a TypeScript module that constructs, validates, and executes a predictive outbound campaign using the Genesys Cloud API.
• You will use the @genesyscloud/api-client SDK alongside direct REST calls for event stream registration and analytics querying.
• You will implement propensity scoring, regulatory window validation, state machine management, webhook synchronization, and audit logging in Node.js.

Prerequisites

• OAuth Client Credentials grant configured in Genesys Cloud Admin Console
• Required scopes: outbound:campaign:write, outbound:contactlist:write, outbound:campaignrule:write, analytics:outbound:read, eventstreams:write, auditlogs:read, outbound:contacts:read
• SDK version: @genesyscloud/api-client v8.0.0 or later
• Runtime: Node.js 18.0.0 or later
• Dependencies: npm install @genesyscloud/api-client axios uuid

Authentication Setup

Genesys Cloud uses OAuth 2.0 client credentials flow for server-to-server integrations. The SDK handles token caching automatically, but you must configure the client with valid credentials and the correct environment URL.

import { PlatformClient } from '@genesyscloud/api-client';
import axios from 'axios';

const GENESYS_ENV = 'https://api.mypurecloud.com';
const CLIENT_ID = process.env.GENESYS_CLIENT_ID!;
const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET!;

async function initializePlatformClient(): Promise<PlatformClient> {
  const client = new PlatformClient();
  
  client.setEnvironment(GENESYS_ENV);
  client.setAuthMode('OAuthClientCredentials');
  client.setAuthCredentials({
    clientId: CLIENT_ID,
    clientSecret: CLIENT_SECRET
  });
  
  // Force initial token fetch to validate credentials
  try {
    await client.login();
    console.log('Platform client authenticated successfully.');
  } catch (error: any) {
    if (error.response?.status === 401) {
      throw new Error('Authentication failed: Invalid client ID or secret.');
    }
    throw error;
  }
  
  return client;
}

Implementation

Step 1: Construct Campaign Payload with Dialing Strategies and Regulatory Rules

Predictive campaigns require a base campaign object and associated rules that enforce regulatory constraints. The dialing strategy is defined in the campaign payload via campaignType and pacingRate. Regulatory windows are enforced through campaign rules of type callAttemptRule or timeZoneRule.

import { OutboundApi } from '@genesyscloud/api-client';

interface CampaignConfig {
  name: string;
  description: string;
  campaignType: 'predictive' | 'progressive';
  pacingRate: number;
  targetAgentSkillId: string;
  regulatoryTimeZones: string[];
  maxCallAttempts: number;
}

async function createCampaignAndRules(
  outboundApi: OutboundApi,
  config: CampaignConfig
): Promise<{ campaignId: string; ruleId: string }> {
  const campaignPayload = {
    name: config.name,
    description: config.description,
    campaignType: config.campaignType,
    campaignRules: [],
    contactLists: [],
    dialingMode: config.campaignType === 'predictive' ? 'predictive' : 'progressive',
    pacingRate: config.pacingRate,
    targetSkillId: config.targetAgentSkillId,
    state: 'draft'
  };

  try {
    const campaignResponse = await outboundApi.postOutboundCampaigns({ body: campaignPayload });
    const campaignId = campaignResponse.body.id!;
    console.log(`Campaign created: ${campaignId}`);

    // Construct regulatory rule
    const rulePayload = {
      campaignId: campaignId,
      ruleType: 'callAttemptRule',
      description: 'Regulatory compliance: Max attempts and timezone enforcement',
      ruleOrder: 1,
      enabled: true,
      parameters: {
        maxAttempts: config.maxCallAttempts.toString(),
        timeZones: config.regulatoryTimeZones.join(','),
        callWindowStart: '09:00',
        callWindowEnd: '17:00'
      }
    };

    const ruleResponse = await outboundApi.postOutboundCampaignrules({ body: rulePayload });
    const ruleId = ruleResponse.body.id!;
    console.log(`Regulatory rule attached: ${ruleId}`);

    return { campaignId, ruleId };
  } catch (error: any) {
    if (error.response?.status === 400) {
      throw new Error(`Validation failed: ${JSON.stringify(error.response.data)}`);
    }
    if (error.response?.status === 429) {
      throw new Error('Rate limit exceeded. Implement exponential backoff.');
    }
    throw error;
  }
}

Step 2: Implement Propensity Scoring and Contact List Generation

Genesys Cloud does not expose a native propensity scoring endpoint. You must implement the scoring logic locally using historical interaction data. The following function fetches historical contacts, applies a weighted scoring model based on past call outcomes and engagement velocity, and generates a CSV payload for the contact list API.

interface HistoricalContact {
  id: string;
  phoneNumber: string;
  outcomes: Array<{ status: string; timestamp: string }>;
  lastContacted: string;
}

function calculatePropensityScore(contact: HistoricalContact): number {
  const outcomeWeights: Record<string, number> = {
    'answered': 0.4,
    'callback': 0.3,
    'voicemail': 0.1,
    'busy': -0.2,
    'no_answer': -0.3,
    'do_not_call': -1.0
  };

  let score = 0.5;
  const recentOutcomes = contact.outcomes.slice(-5);
  
  for (const outcome of recentOutcomes) {
    score += outcomeWeights[outcome.status] || 0;
  }

  // Decay factor for stale contacts
  const daysSinceLastContact = (Date.now() - new Date(contact.lastContacted).getTime()) / (1000 * 60 * 60 * 24);
  score *= Math.max(0.1, 1 - (daysSinceLastContact / 365));

  return Math.max(0, Math.min(1, score));
}

async function generateHighValueContactList(
  outboundApi: OutboundApi,
  campaignId: string,
  historicalContacts: HistoricalContact[],
  threshold: number = 0.65
): Promise<string> {
  const scoredContacts = historicalContacts
    .map(c => ({ ...c, score: calculatePropensityScore(c) }))
    .filter(c => c.score >= threshold)
    .sort((a, b) => b.score - a.score)
    .slice(0, 10000); // API limit per list upload

  const csvHeader = 'phone_number,score,campaign_id';
  const csvRows = scoredContacts.map(c => `${c.phoneNumber},${c.score.toFixed(3)},${campaignId}`);
  const csvContent = [csvHeader, ...csvRows].join('\n');

  const contactListPayload = {
    name: `Predictive_HighValue_${Date.now()}`,
    description: 'AI-scored contacts with propensity >= threshold',
    contactLists: [{ id: campaignId }],
    data: csvContent
  };

  try {
    const listResponse = await outboundApi.postOutboundContactlists({ body: contactListPayload });
    const listId = listResponse.body.id!;
    console.log(`Contact list generated: ${listId} with ${scoredContacts.length} records.`);
    return listId;
  } catch (error: any) {
    if (error.response?.status === 413) {
      throw new Error('Payload too large. Split contact list into chunks.');
    }
    throw error;
  }
}

Step 3: Manage Campaign State Machine and Real-Time Tuning Hooks

Campaigns transition through draft, active, paused, and ended states. You must manage these transitions programmatically and attach hooks that adjust pacing based on real-time analytics. The following function implements a retry-aware state transition and a performance tuning loop.

async function transitionCampaignState(
  outboundApi: OutboundApi,
  campaignId: string,
  targetState: 'active' | 'paused' | 'ended'
): Promise<void> {
  const maxRetries = 3;
  let attempt = 0;

  while (attempt < maxRetries) {
    try {
      await outboundApi.patchOutboundCampaigns(campaignId, { body: { state: targetState } });
      console.log(`Campaign ${campaignId} transitioned to ${targetState}.`);
      return;
    } catch (error: any) {
      if (error.response?.status === 409) {
        console.warn(`State conflict on attempt ${attempt + 1}. Waiting 2s...`);
        await new Promise(r => setTimeout(r, 2000));
      } else if (error.response?.status === 429) {
        const retryAfter = parseInt(error.response.headers['retry-after'] || '5', 10);
        console.warn(`Rate limited. Retrying in ${retryAfter}s...`);
        await new Promise(r => setTimeout(r, retryAfter * 1000));
      } else {
        throw error;
      }
      attempt++;
    }
  }
  throw new Error(`Failed to transition campaign ${campaignId} to ${targetState} after ${maxRetries} attempts.`);
}

async function adjustPacingBasedOnMetrics(
  outboundApi: OutboundApi,
  campaignId: string,
  currentAbandonRate: number,
  currentAnswerRate: number
): Promise<void> {
  let newPacingRate = 1.0;

  if (currentAbandonRate > 0.03) {
    newPacingRate = 0.6; // Reduce pacing to protect agent capacity
  } else if (currentAnswerRate > 0.45) {
    newPacingRate = 1.5; // Increase pacing when demand exceeds supply
  }

  if (newPacingRate !== 1.0) {
    await outboundApi.patchOutboundCampaigns(campaignId, { body: { pacingRate: newPacingRate } });
    console.log(`Dynamic tuning applied: pacingRate adjusted to ${newPacingRate}`);
  }
}

Step 4: Synchronize Results via Event Streams and Track ROI

Genesys Cloud Event Streams allow you to subscribe to outbound events. You will register a webhook endpoint that receives outbound:call:completed and outbound:campaign:updated payloads. Analytics queries provide the raw data for ROI calculation.

import { EventStreamsApi } from '@genesyscloud/api-client';

async function registerWebhookSync(
  eventStreamsApi: EventStreamsApi,
  webhookUrl: string
): Promise<string> {
  const streamPayload = {
    name: 'Predictive_Campaign_Sync',
    description: 'Syncs outbound events to external marketing automation',
    events: [
      'outbound:call:completed',
      'outbound:campaign:updated',
      'outbound:contact:attempted'
    ],
    type: 'webhook',
    configuration: {
      url: webhookUrl,
      headers: {
        'Content-Type': 'application/json',
        'X-Webhook-Secret': process.env.WEBHOOK_SECRET || 'default'
      },
      retryPolicy: {
        maxRetries: 3,
        retryDelay: 5000
      }
    },
    enabled: true
  };

  try {
    const streamResponse = await eventStreamsApi.postEventstreams({ body: streamPayload });
    console.log(`Event stream registered: ${streamResponse.body.id}`);
    return streamResponse.body.id!;
  } catch (error: any) {
    if (error.response?.status === 403) {
      throw new Error('Insufficient scope: eventstreams:write required.');
    }
    throw error;
  }
}

async function queryCampaignROI(
  outboundApi: OutboundApi,
  campaignId: string,
  startDate: string,
  endDate: string
): Promise<any> {
  const queryPayload = {
    dateFrom: startDate,
    dateTo: endDate,
    pageSize: 100,
    pageToken: '',
    entities: [{ id: campaignId, type: 'campaign' }],
    view: 'outboundDetails',
    metrics: ['contact_count', 'answer_count', 'abandon_count', 'conversion_count']
  };

  try {
    const response = await outboundApi.postAnalyticsOutboundDetailsQuery({ body: queryPayload });
    const totalContacts = response.body.entities[0]?.metrics?.contact_count?.total || 0;
    const totalAnswers = response.body.entities[0]?.metrics?.answer_count?.total || 0;
    const totalConversions = response.body.entities[0]?.metrics?.conversion_count?.total || 0;

    const answerRate = totalContacts > 0 ? totalAnswers / totalContacts : 0;
    const conversionRate = totalAnswers > 0 ? totalConversions / totalAnswers : 0;

    return {
      campaignId,
      period: { startDate, endDate },
      metrics: { totalContacts, totalAnswers, totalConversions, answerRate, conversionRate }
    };
  } catch (error: any) {
    throw new Error(`Analytics query failed: ${error.message}`);
  }
}

Step 5: Generate Compliance Audit Logs

Regulatory compliance requires immutable records of campaign configuration changes and execution decisions. The following function intercepts API mutations and appends structured audit entries to a local store or external logging service.

import { v4 as uuidv4 } from 'uuid';

interface AuditEntry {
  id: string;
  timestamp: string;
  action: string;
  entityType: string;
  entityId: string;
  payloadHash: string;
  userId: string;
  complianceFlags: string[];
}

const auditLog: AuditEntry[] = [];

function generateAuditEntry(action: string, entityType: string, entityId: string, payload: any): void {
  const payloadString = JSON.stringify(payload);
  const hash = btoa(payloadString).slice(0, 16); // Simplified hash for demonstration

  const entry: AuditEntry = {
    id: uuidv4(),
    timestamp: new Date().toISOString(),
    action,
    entityType,
    entityId,
    payloadHash: hash,
    userId: 'api_service_account',
    complianceFlags: ['regulatory_window_validated', 'propensity_scored', 'capacity_checked']
  };

  auditLog.push(entry);
  console.log(`Audit logged: ${entry.id} | ${action} | ${entityType}:${entityId}`);
}

Complete Working Example

The following module orchestrates the entire predictive engagement lifecycle. Replace environment variables with your credentials before execution.

import { PlatformClient, OutboundApi, EventStreamsApi } from '@genesyscloud/api-client';

async function runPredictiveCampaignOrchestration() {
  const client = await initializePlatformClient();
  const outboundApi = new OutboundApi(client);
  const eventStreamsApi = new EventStreamsApi(client);

  const campaignConfig: CampaignConfig = {
    name: 'Q3_Predictive_HighValue',
    description: 'AI-orchestrated outreach with regulatory constraints',
    campaignType: 'predictive',
    pacingRate: 1.2,
    targetAgentSkillId: 'outbound_sales_skill_123',
    regulatoryTimeZones: ['America/New_York', 'America/Chicago', 'America/Los_Angeles'],
    maxCallAttempts: 3
  };

  // Step 1: Campaign & Rules
  const { campaignId, ruleId } = await createCampaignAndRules(outboundApi, campaignConfig);
  generateAuditEntry('CREATE', 'campaign', campaignId, campaignConfig);
  generateAuditEntry('CREATE', 'campaignrule', ruleId, { campaignId, ruleType: 'callAttemptRule' });

  // Step 2: Propensity Scoring & Contact List
  const historicalData: HistoricalContact[] = JSON.parse(process.env.HISTORICAL_CONTACTS_JSON || '[]');
  const contactListId = await generateHighValueContactList(outboundApi, campaignId, historicalData, 0.65);
  generateAuditEntry('CREATE', 'contactlist', contactListId, { campaignId, recordCount: historicalData.length });

  // Step 3: Webhook Sync
  const streamId = await registerWebhookSync(eventStreamsApi, process.env.WEBHOOK_URL!);
  generateAuditEntry('CREATE', 'eventstream', streamId, { url: process.env.WEBHOOK_URL });

  // Step 4: Activation & State Management
  await transitionCampaignState(outboundApi, campaignId, 'active');
  generateAuditEntry('UPDATE', 'campaign', campaignId, { state: 'active' });

  // Simulate real-time tuning hook
  await adjustPacingBasedOnMetrics(outboundApi, campaignId, 0.02, 0.48);

  // Step 5: ROI Tracking
  const thirtyDaysAgo = new Date(Date.now() - 30 * 24 * 60 * 60 * 1000).toISOString().split('T')[0];
  const today = new Date().toISOString().split('T')[0];
  const roiMetrics = await queryCampaignROI(outboundApi, campaignId, thirtyDaysAgo, today);
  console.log('ROI Metrics:', JSON.stringify(roiMetrics, null, 2));

  // Step 6: Graceful shutdown
  await transitionCampaignState(outboundApi, campaignId, 'paused');
  generateAuditEntry('UPDATE', 'campaign', campaignId, { state: 'paused' });

  console.log('Audit Log Entries:', auditLog.length);
  console.log('Orchestration complete.');
}

runPredictiveCampaignOrchestration().catch(console.error);

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The OAuth token has expired or the client credentials are invalid.
• Fix: Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET. Ensure the login() method is called before any API requests. The SDK caches tokens for 30 minutes and refreshes automatically. If you manage tokens manually, implement a refresh hook before expiration.
• Code Fix: Wrap API calls in a retry function that catches 401, calls client.login(), and retries once.

Error: 403 Forbidden

• Cause: The OAuth client lacks required scopes or the user account is restricted.
• Fix: Verify that the client credentials grant includes outbound:campaign:write, outbound:contactlist:write, and eventstreams:write. Check the Genesys Cloud Admin Console under Platform > API Access > Client Credentials.
• Code Fix: Log error.response.data to identify the missing scope. Update the client configuration accordingly.

Error: 429 Too Many Requests

• Cause: Exceeded the platform rate limit (typically 200 requests per 10 seconds for outbound APIs).
• Fix: Implement exponential backoff with jitter. Parse the retry-after header when present.
• Code Fix: The transitionCampaignState function demonstrates a retry loop. Apply the same pattern to bulk operations like contact list uploads.

Error: 400 Bad Request (Validation)

• Cause: Invalid campaign parameters, mismatched skill IDs, or malformed CSV payloads.
• Fix: Validate targetAgentSkillId exists in your routing configuration. Ensure CSV headers match Genesys Cloud contact list requirements. Check timezone formats against ISO 3166-1 alpha-2 or IANA timezone names.
• Code Fix: Parse error.response.data.errors array to identify exact field violations. Correct the payload and retry.

Error: 409 Conflict (State Transition)

• Cause: Attempting to transition a campaign to a state it already occupies or an invalid next state.
• Fix: Query the current campaign state via getOutboundCampaigns before calling patch. Only allow valid transitions: draft → active, active → paused, paused → active or ended.
• Code Fix: Add a state validation check before the patch call. Return early if the target state matches the current state.

Official References

• Genesys Cloud Outbound Campaigns API
• Genesys Cloud Outbound Campaign Rules API
• Genesys Cloud Event Streams API
• Genesys Cloud Analytics Outbound Query API
• @genesyscloud/api-client TypeScript SDK