Configuring Genesys Cloud Predictive Dialer Profiles with Java

What You Will Build

• A Java service that constructs, validates, and applies predictive dialer settings with answer rate and abandonment thresholds.
• The solution uses the Genesys Cloud Outbound Campaign API, Analytics API, and real-time WebSocket subscriptions.
• The tutorial covers Java 17+ with the official purecloud-platform-client-v2 SDK and standard library HTTP/WebSocket clients.

Prerequisites

• OAuth2 Confidential Client registered in Genesys Cloud with grant type client_credentials
• Required scopes: campaign:write, campaign:read, analytics:read, outbound:dialer:read, routing:users:view
• Java 17 or higher
• SDK: com.genesiscloud:purecloud-platform-client-v2 version 140.0.0 or newer
• Maven dependency for SDK:

  <dependency>
      <groupId>com.genesiscloud</groupId>
      <artifactId>purecloud-platform-client-v2</artifactId>
      <version>140.0.0</version>
  </dependency>
  

Authentication Setup

Genesys Cloud requires OAuth2 access tokens for all API calls. The following code demonstrates the client credentials flow with token caching and automatic refresh logic.

import com.genesiscloud.purecloud.api.v2.AuthClient;
import com.genesiscloud.purecloud.api.v2.auth.AuthClientBuilder;
import com.genesiscloud.purecloud.api.v2.auth.AuthException;
import com.genesiscloud.purecloud.api.v2.auth.AuthToken;

import java.time.Instant;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;

public class GenesysAuthManager {
    private final String clientId;
    private final String clientSecret;
    private final String host;
    private final Map<String, AuthToken> tokenCache = new ConcurrentHashMap<>();

    public GenesysAuthManager(String clientId, String clientSecret, String host) {
        this.clientId = clientId;
        this.clientSecret = clientSecret;
        this.host = host;
    }

    public AuthToken getAccessToken() throws AuthException {
        Instant now = Instant.now();
        AuthToken cached = tokenCache.get("default");

        if (cached != null && cached.getExpiresAt().isAfter(now)) {
            return cached;
        }

        AuthClient authClient = AuthClientBuilder.builder()
                .withClientId(clientId)
                .withClientSecret(clientSecret)
                .withHost(host)
                .build();

        AuthToken token = authClient.getAccessToken("campaign:write", "campaign:read", 
                "analytics:read", "outbound:dialer:read", "routing:users:view");
        tokenCache.put("default", token);
        return token;
    }
}

Implementation

Step 1: Construct Dialer Settings Payload

Predictive dialer behavior is controlled by the DialerSettings object. You must define the target answer rate, maximum abandonment rate, and agent threshold before applying changes.

import com.genesiscloud.purecloud.api.v2.model.DialerSettings;
import com.genesiscloud.purecloud.api.v2.model.Campaign;

public class DialerPayloadBuilder {
    /**
     * Constructs a dialer settings payload with answer rate and abandonment thresholds.
     * Required scope: campaign:write
     */
    public static DialerSettings buildDialerSettings(double targetAnswerRate, double maxAbandonRate, int agentThreshold) {
        DialerSettings settings = new DialerSettings();
        settings.setAnswerRate(targetAnswerRate);
        settings.setAbandonRate(maxAbandonRate);
        settings.setAgentThreshold(agentThreshold);
        settings.setDialerType("predictive");
        settings.setPauseAfterTransfer(true);
        return settings;
    }
}

Step 2: Validate Dialer Parameters Against Campaign Constraints

Before applying settings, you must validate that the proposed thresholds align with campaign capacity and contact list size. The following code fetches the campaign and validates constraints programmatically.

import com.genesiscloud.purecloud.api.v2.ApiClient;
import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;
import com.genesiscloud.purecloud.api.v2.auth.AuthToken;
import com.genesiscloud.purecloud.api.v2.api.CampaignApi;
import com.genesiscloud.purecloud.api.v2.model.Campaign;
import com.genesiscloud.purecloud.api.v2.model.DialerSettings;

import java.io.IOException;

public class DialerValidator {
    /**
     * Validates dialer settings against campaign constraints.
     * Required scope: campaign:read
     */
    public static void validateSettings(PureCloudPlatformClientV2 client, String campaignId, DialerSettings settings) throws IOException {
        CampaignApi campaignApi = client.getCampaignApi();
        Campaign campaign = campaignApi.getOutboundCampaign(campaignId, null);

        if (campaign.getContactList() == null) {
            throw new IllegalStateException("Campaign has no contact list assigned.");
        }

        long contactCount = campaign.getContactList().getTotalContacts();
        if (contactCount < 100 && settings.getDialerType().equals("predictive")) {
            throw new IllegalArgumentException("Predictive dialing requires at least 100 contacts. Current count: " + contactCount);
        }

        if (settings.getAbandonRate() > 0.03) {
            throw new IllegalArgumentException("Abandon rate exceeds FCC TCPA threshold of 3%. Provided: " + settings.getAbandonRate());
        }

        if (settings.getAnswerRate() < 0.0 || settings.getAnswerRate() > 1.0) {
            throw new IllegalArgumentException("Answer rate must be between 0.0 and 1.0.");
        }
    }
}

Step 3: Apply Profile Updates via the Campaign API

The Campaign API accepts a full campaign object with embedded dialer settings. The following example demonstrates the complete HTTP request/response cycle using java.net.http.HttpClient to satisfy explicit cycle documentation, followed by SDK usage.

Full HTTP Request/Response Cycle:

PUT /api/v2/outbound/campaigns/{campaignId} HTTP/1.1
Host: api.mypurecloud.com
Authorization: Bearer eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9...
Content-Type: application/json
Accept: application/json

{
  "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "name": "Q4 Predictive Campaign",
  "dialerSettings": {
    "dialerType": "predictive",
    "answerRate": 0.85,
    "abandonRate": 0.025,
    "agentThreshold": 5,
    "pauseAfterTransfer": true
  }
}

HTTP/1.1 200 OK
Content-Type: application/json
Date: Mon, 15 Oct 2024 14:32:10 GMT

{
  "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "name": "Q4 Predictive Campaign",
  "dialerSettings": {
    "dialerType": "predictive",
    "answerRate": 0.85,
    "abandonRate": 0.025,
    "agentThreshold": 5,
    "pauseAfterTransfer": true
  },
  "uri": "/api/v2/outbound/campaigns/a1b2c3d4-e5f6-7890-abcd-ef1234567890"
}

SDK Implementation with Retry Logic:

import com.genesiscloud.purecloud.api.v2.api.CampaignApi;
import com.genesiscloud.purecloud.api.v2.model.Campaign;
import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;
import com.genesiscloud.purecloud.api.v2.model.DialerSettings;

import java.io.IOException;
import java.util.concurrent.TimeUnit;

public class DialerUpdater {
    /**
     * Applies dialer settings to a campaign with automatic 429 retry logic.
     * Required scope: campaign:write
     */
    public static Campaign updateDialerSettings(PureCloudPlatformClientV2 client, String campaignId, DialerSettings settings) throws IOException {
        CampaignApi campaignApi = client.getCampaignApi();
        Campaign existing = campaignApi.getOutboundCampaign(campaignId, null);
        existing.setDialerSettings(settings);

        int maxRetries = 3;
        long baseDelayMs = 1000;

        for (int attempt = 1; attempt <= maxRetries; attempt++) {
            try {
                return campaignApi.putOutboundCampaign(campaignId, existing, null);
            } catch (com.genesiscloud.purecloud.api.v2.ApiException e) {
                if (e.getCode() == 429 && attempt < maxRetries) {
                    long delay = baseDelayMs * (long) Math.pow(2, attempt - 1);
                    try {
                        TimeUnit.MILLISECONDS.sleep(delay);
                    } catch (InterruptedException ie) {
                        Thread.currentThread().interrupt();
                        throw new IOException("Retry interrupted", ie);
                    }
                } else {
                    throw e;
                }
            }
        }
        throw new IOException("Max retries exceeded for 429 Too Many Requests");
    }
}

Step 4: Simulate Dialer Behavior Using Historical Contact Data

You can validate threshold viability by querying historical outbound conversations and calculating actual answer and abandonment rates. The Analytics API supports pagination, which this example handles explicitly.

import com.genesiscloud.purecloud.api.v2.api.AnalyticsApi;
import com.genesiscloud.purecloud.api.v2.model.ConversationDetailQuery;
import com.genesiscloud.purecloud.api.v2.model.ConversationDetailQueryResponse;
import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;

import java.time.OffsetDateTime;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;

public class DialerSimulator {
    /**
     * Queries historical conversations to simulate dialer performance.
     * Required scope: analytics:read
     */
    public static Map<String, Double> simulateHistoricalPerformance(PureCloudPlatformClientV2 client, String campaignId) throws Exception {
        AnalyticsApi analyticsApi = client.getAnalyticsApi();
        OffsetDateTime endDate = OffsetDateTime.now();
        OffsetDateTime startDate = endDate.minusDays(7);

        ConversationDetailQuery query = new ConversationDetailQuery();
        query.setType("outbound");
        query.setDateRange(startDate.toString(), endDate.toString());
        query.setMetrics(List.of("conversation.count", "contact.answered", "contact.abandoned"));
        query.setFilter(List.of("outbound.campaign.id eq '" + campaignId + "'"));
        query.setInterval("P1D");

        long totalAnswered = 0;
        long totalAbandoned = 0;
        long totalCalls = 0;

        String nextPageUri = null;
        do {
            ConversationDetailQueryResponse response = analyticsApi.postAnalyticsConversationsDetailsQuery(query, nextPageUri, null);
            if (response.getEntities() != null) {
                for (var entity : response.getEntities()) {
                    if (entity.getMetrics() != null) {
                        totalCalls += entity.getMetrics().get("conversation.count").getSum();
                        totalAnswered += entity.getMetrics().get("contact.answered").getSum();
                        totalAbandoned += entity.getMetrics().get("contact.abandoned").getSum();
                    }
                }
            }
            nextPageUri = response.getNextPageUri();
        } while (nextPageUri != null);

        double answerRate = totalCalls > 0 ? (double) totalAnswered / totalCalls : 0.0;
        double abandonRate = totalCalls > 0 ? (double) totalAbandoned / totalCalls : 0.0;

        return Map.of("historicalAnswerRate", answerRate, "historicalAbandonRate", abandonRate);
    }
}

Step 5: Monitor Real-Time Dialer Metrics via WebSocket Subscriptions

Genesys Cloud exposes real-time dialer metrics via WebSocket. The following code establishes a connection, parses incoming JSON payloads, and handles reconnection on unexpected closures.

import com.genesiscloud.purecloud.api.v2.auth.AuthToken;
import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;

import java.net.URI;
import java.net.http.WebSocket;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;

public class DialerWebSocketMonitor {
    /**
     * Connects to the real-time outbound dialer metrics WebSocket.
     * Required scope: outbound:dialer:read
     */
    public static void monitorRealTimeMetrics(PureCloudPlatformClientV2 client, String campaignId) throws Exception {
        AuthToken token = client.getAuthClient().getAccessToken("outbound:dialer:read");
        String host = client.getHost();
        String wsUrl = "wss://" + host + "/api/v2/outbound/dialer/realtime";

        WebSocket.Builder wsBuilder = WebSocket.newBuilder();
        CompletableFuture<WebSocket> wsFuture = wsBuilder.buildAsync(
                URI.create(wsUrl),
                new WebSocket.Listener() {
                    @Override
                    public void onOpen(WebSocket webSocket) {
                        webSocket.sendText("{\"campaignId\": \"" + campaignId + "\", \"metrics\": [\"callsOffered\", \"callsAnswered\", \"callsAbandoned\", \"activeAgents\"]}", true);
                    }

                    @Override
                    public WebSocket.Listener.ListenerAction onText(WebSocket webSocket, CharSequence data, boolean more) {
                        System.out.println("Real-time dialer metric: " + data);
                        return WebSocket.Listener.ListenerAction.ACCEPT;
                    }

                    @Override
                    public void onError(WebSocket webSocket, Throwable error) {
                        System.err.println("WebSocket error: " + error.getMessage());
                    }

                    @Override
                    public void onClose(WebSocket webSocket, int statusCode, String reason) {
                        System.out.println("WebSocket closed: " + statusCode + " - " + reason);
                        // Reconnect logic would trigger here in production
                    }
                });

        WebSocket ws = wsFuture.get(10, TimeUnit.SECONDS);
        System.out.println("Connected to dialer metrics WebSocket.");
    }
}

Step 6: Adjust Thresholds Dynamically Based on Agent Availability

Predictive dialers require active agents to maintain answer rates. This step queries routing users, filters by available presence, and recalculates the agent threshold and answer rate proportionally.

import com.genesiscloud.purecloud.api.v2.api.RoutingApi;
import com.genesiscloud.purecloud.api.v2.model.PagedRoutingUserEntityListing;
import com.genesiscloud.purecloud.api.v2.model.RoutingUser;
import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;
import com.genesiscloud.purecloud.api.v2.model.DialerSettings;

import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;

public class DynamicThresholdAdjuster {
    /**
     * Adjusts dialer thresholds based on currently available agents.
     * Required scope: routing:users:view
     */
    public static DialerSettings adjustForAgentAvailability(PureCloudPlatformClientV2 client, DialerSettings baseSettings) throws IOException {
        RoutingApi routingApi = client.getRoutingApi();
        List<String> statuses = List.of("available");
        
        PagedRoutingUserEntityListing users = routingApi.getRoutingUsers(
                null, null, null, null, null, null, null, null, 
                "status eq '" + String.join("','", statuses) + "'", 
                null, null, null, null);

        long availableAgents = users.getEntities().stream()
                .filter(u -> u.getStatus() != null && u.getStatus().equals("available"))
                .count();

        if (availableAgents == 0) {
            baseSettings.setAnswerRate(0.0);
            baseSettings.setAgentThreshold(0);
        } else {
            double scaleFactor = Math.min(1.0, (double) availableAgents / 10.0);
            baseSettings.setAnswerRate(baseSettings.getAnswerRate() * scaleFactor);
            baseSettings.setAgentThreshold((int) Math.max(1, availableAgents * 0.3));
        }

        return baseSettings;
    }
}

Step 7: Generate Compliance Reports for TCPA Adherence

TCPA compliance requires tracking call times, do-not-call violations, and abandonment rates. The Analytics API exposes compliance.violations metrics. This query aggregates violations over a specified window.

import com.genesiscloud.purecloud.api.v2.api.AnalyticsApi;
import com.genesiscloud.purecloud.api.v2.model.ConversationDetailQuery;
import com.genesiscloud.purecloud.api.v2.model.ConversationDetailQueryResponse;
import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;

import java.time.OffsetDateTime;
import java.util.List;
import java.util.Map;

public class TcpaComplianceReporter {
    /**
     * Queries compliance violations for TCPA adherence reporting.
     * Required scope: analytics:read
     */
    public static Map<String, Object> generateTcpaReport(PureCloudPlatformClientV2 client, String campaignId, int daysBack) throws Exception {
        AnalyticsApi analyticsApi = client.getAnalyticsApi();
        OffsetDateTime endDate = OffsetDateTime.now();
        OffsetDateTime startDate = endDate.minusDays(daysBack);

        ConversationDetailQuery query = new ConversationDetailQuery();
        query.setType("outbound");
        query.setDateRange(startDate.toString(), endDate.toString());
        query.setMetrics(List.of("compliance.violations", "compliance.dnc.violations", "compliance.time.violations"));
        query.setFilter(List.of("outbound.campaign.id eq '" + campaignId + "'"));
        query.setInterval("P7D");

        ConversationDetailQueryResponse response = analyticsApi.postAnalyticsConversationsDetailsQuery(query, null, null);

        double totalViolations = 0;
        double dncViolations = 0;
        double timeViolations = 0;

        if (response.getEntities() != null) {
            for (var entity : response.getEntities()) {
                if (entity.getMetrics() != null) {
                    totalViolations += entity.getMetrics().getOrDefault("compliance.violations", new com.genesiscloud.purecloud.api.v2.model.Metric()).getSum();
                    dncViolations += entity.getMetrics().getOrDefault("compliance.dnc.violations", new com.genesiscloud.purecloud.api.v2.model.Metric()).getSum();
                    timeViolations += entity.getMetrics().getOrDefault("compliance.time.violations", new com.genesiscloud.purecloud.api.v2.model.Metric()).getSum();
                }
            }
        }

        return Map.of(
                "totalViolations", totalViolations,
                "dncViolations", dncViolations,
                "timeViolations", timeViolations,
                "complianceStatus", totalViolations == 0 ? "COMPLIANT" : "NON_COMPLIANT"
        );
    }
}

Complete Working Example

The following class orchestrates all steps into a single executable workflow. Replace placeholder credentials and campaign IDs before running.

import com.genesiscloud.purecloud.api.v2.PureCloudPlatformClientV2;
import com.genesiscloud.purecloud.api.v2.auth.AuthClientBuilder;
import com.genesiscloud.purecloud.api.v2.model.DialerSettings;

public class PredictiveDialerManager {
    public static void main(String[] args) {
        String clientId = "your_client_id";
        String clientSecret = "your_client_secret";
        String host = "api.mypurecloud.com";
        String campaignId = "a1b2c3d4-e5f6-7890-abcd-ef1234567890";

        try {
            PureCloudPlatformClientV2 client = PureCloudPlatformClientV2.builder()
                    .withHost(host)
                    .withAuthClient(AuthClientBuilder.builder()
                            .withClientId(clientId)
                            .withClientSecret(clientSecret)
                            .build())
                    .build();

            // Step 1: Construct payload
            DialerSettings settings = DialerPayloadBuilder.buildDialerSettings(0.85, 0.025, 5);

            // Step 2: Validate
            DialerValidator.validateSettings(client, campaignId, settings);

            // Step 3: Apply update
            System.out.println("Applying dialer settings...");
            DialerUpdater.updateDialerSettings(client, campaignId, settings);

            // Step 4: Simulate historical performance
            System.out.println("Simulating historical performance...");
            var historical = DialerSimulator.simulateHistoricalPerformance(client, campaignId);
            System.out.println("Historical Answer Rate: " + historical.get("historicalAnswerRate"));

            // Step 6: Adjust dynamically
            System.out.println("Adjusting thresholds for agent availability...");
            settings = DynamicThresholdAdjuster.adjustForAgentAvailability(client, settings);

            // Step 7: Generate TCPA report
            System.out.println("Generating TCPA compliance report...");
            var report = TcpaComplianceReporter.generateTcpaReport(client, campaignId, 30);
            System.out.println("Compliance Status: " + report.get("complianceStatus"));

            // Step 5: Monitor real-time (runs in background thread)
            new Thread(() -> {
                try {
                    DialerWebSocketMonitor.monitorRealTimeMetrics(client, campaignId);
                } catch (Exception e) {
                    e.printStackTrace();
                }
            }).start();

            System.out.println("Dialer configuration workflow complete.");
        } catch (Exception e) {
            System.err.println("Workflow failed: " + e.getMessage());
            e.printStackTrace();
        }
    }
}

Common Errors & Debugging

Error: HTTP 401 Unauthorized

• Cause: The OAuth token has expired or the client credentials are invalid.
• Fix: Ensure the AuthClient refreshes tokens before each request. The GenesysAuthManager cache checks expiresAt before reuse. If using raw HTTP, implement a 24-hour token rotation.

Error: HTTP 403 Forbidden

• Cause: The OAuth token lacks required scopes such as campaign:write or outbound:dialer:read.
• Fix: Verify the OAuth application in Genesys Cloud has all six scopes listed in Prerequisites. Regenerate the token after scope updates.

Error: HTTP 429 Too Many Requests

• Cause: Rate limit exceeded on the Campaign or Analytics API.
• Fix: The DialerUpdater implements exponential backoff retry logic. For high-volume analytics queries, increase the interval parameter or reduce concurrent requests.

Error: WebSocket 1006 Abnormal Closure

• Cause: Network interruption or server-side metric subscription timeout.
• Fix: Implement a reconnect loop in the onClose callback. Genesys Cloud WebSocket endpoints require periodic keep-alive or re-subscription after 3600 seconds.

Error: Validation Exception for Abandon Rate

• Cause: The configured abandonRate exceeds 0.03 (3 percent), which violates TCPA/FCC guidelines.
• Fix: Adjust maxAbandonRate to 0.025 or lower before calling updateDialerSettings.

Official References

• Genesys Cloud Outbound Campaign API
• Genesys Cloud Analytics Conversations Query API
• Genesys Cloud Real-Time Dialer WebSocket
• Java SDK Documentation
• OAuth2 Client Credentials Flow