Configuring Genesys Cloud Predictive Outbound Campaigns via Java API

What You Will Build

This tutorial builds a Java service that creates predictive outbound campaigns, validates regulatory and skill constraints, streams real-time stats via WebSocket, segments contacts by priority, exports metrics, and runs a dialing simulator. It uses the Genesys Cloud Java SDK and REST/WebSocket APIs for the Outbound Campaign module. The implementation covers Java 17 with Maven dependencies and production-grade error handling.

Prerequisites

• OAuth client type: Service Account or Client Credentials flow
• Required scopes: campaign:write, campaign:read, outbound:read, webhooks:write, analytics:read, streaming:read, routing:read
• SDK version: com.mypurecloud.api:platform-client-v2:130.0.0
• Runtime: Java 17 or higher
• External dependencies: org.java-websocket:Java-WebSocket:1.5.4, com.google.code.gson:gson:2.10.1, org.slf4j:slf4j-api:2.0.9

Authentication Setup

Genesys Cloud uses OAuth 2.0 client credentials for service accounts. The Java SDK handles token caching and automatic refresh when configured correctly. You must initialize the Configuration object with your client ID, secret, and environment. The SDK stores the access token and refresh token in memory and attaches the Authorization header to every request automatically.

import com.mypurecloud.api.client.Configuration;
import com.mypurecloud.api.client.PureCloudAuth;
import com.mypurecloud.api.client.auth.AuthException;

public class GenesysAuth {
    private static final String CLIENT_ID = "your-client-id";
    private static final String CLIENT_SECRET = "your-client-secret";
    private static final String ENVIRONMENT = "mypurecloud.com";

    public static Configuration initializeAuth() throws AuthException {
        PureCloudAuth auth = new PureCloudAuth.Builder(CLIENT_ID, CLIENT_SECRET)
                .environment(ENVIRONMENT)
                .build();
        auth.login();
        return auth.getConfiguration();
    }
}

The auth.login() call performs the initial token exchange. Subsequent API calls reuse the cached token. If the token expires, the SDK intercepts the 401 response, triggers a silent refresh, and retries the original request. You must ensure your OAuth client has the campaign:write and streaming:read scopes enabled in the Genesys Cloud admin console under Platform > Integrations.

Implementation

Step 1: Construct Campaign Payload with Ramp-Up and Abandonment Thresholds

Predictive dialing requires precise control over how quickly the system adds agents to the pool and how many abandoned calls it tolerates. The Campaign model exposes rampUp, abandonmentRate, and predictiveDialing fields. The ramp-up value defines the number of seconds the dialer waits before increasing the call rate. The abandonment rate is a decimal between 0.0 and 1.0 representing the maximum percentage of calls that may hang up before an agent answers.

import com.mypurecloud.api.client.ApiException;
import com.mypurecloud.api.v2.outbound.OutboundApi;
import com.mypurecloud.api.v2.outbound.model.Campaign;
import com.mypurecloud.api.v2.outbound.model.CampaignType;

public Campaign createPredictiveCampaign(OutboundApi outboundApi, String contactListId) throws ApiException {
    Campaign campaign = new Campaign();
    campaign.setName("Q3 Predictive Outreach");
    campaign.setContactListId(contactListId);
    campaign.setCampaignType(CampaignType.PREDICTIVE);
    campaign.setPredictiveDialing(true);
    
    // Ramp-up: 120 seconds before dialer increases call rate
    campaign.setRampUp(120);
    // Abandonment threshold: 3% maximum
    campaign.setAbandonmentRate(0.03);
    campaign.setDialRatio(3.0);
    campaign.setWrapUpTime(30);
    campaign.setSkillRequiredId("a1b2c3d4-e5f6-7890-abcd-ef1234567890");
    campaign.setWrapUpCode("COMPLETED");
    campaign.setDialingRulesId("ruleset-uuid-here");
    campaign.setActive(true);

    try {
        return outboundApi.postOutboundCampaigns(campaign);
    } catch (ApiException e) {
        handleApiError(e, "Campaign creation failed");
        throw e;
    }
}

The postOutboundCampaigns call maps to POST /api/v2/outbound/campaigns. The response returns the fully populated campaign object with a generated UUID. You must set predictiveDialing to true and provide a valid dialingRulesId that references a time-based or DNC-compliant rule set.

Step 2: Validate Regulatory Constraints and Agent Skill Requirements

Regulatory compliance requires verifying that the campaign respects Do Not Call lists, timezone restrictions, and agent skill assignments. You validate skill requirements by querying the routing API and cross-referencing the campaign’s skillRequiredId. You validate DNC compliance by ensuring the campaign references a dialing ruleset that includes DNC suppression.

import com.mypurecloud.api.v2.routing.RoutingApi;
import com.mypurecloud.api.v2.routing.model.Skill;

public void validateCampaignConstraints(OutboundApi outboundApi, RoutingApi routingApi, Campaign campaign) throws ApiException {
    // Verify skill exists and is active
    Skill skill = routingApi.getRoutingSkill(campaign.getSkillRequiredId());
    if (skill == null || !Boolean.TRUE.equals(skill.getEnabled())) {
        throw new IllegalArgumentException("Campaign references an inactive or missing routing skill.");
    }

    // Verify dialing ruleset exists
    var ruleset = outboundApi.getOutboundCampaignsDialingRules(campaign.getDialingRulesId());
    if (ruleset == null) {
        throw new IllegalArgumentException("Campaign references a missing dialing ruleset.");
    }

    // Validate abandonment rate bounds
    if (campaign.getAbandonmentRate() == null || campaign.getAbandonmentRate() < 0.0 || campaign.getAbandonmentRate() > 0.05) {
        throw new IllegalArgumentException("Abandonment rate must be between 0.0 and 0.05 for regulatory compliance.");
    }

    // Validate ramp-up bounds
    if (campaign.getRampUp() == null || campaign.getRampUp() < 30 || campaign.getRampUp() > 300) {
        throw new IllegalArgumentException("Ramp-up must be between 30 and 300 seconds.");
    }
}

This validation runs synchronously before activation. The getRoutingSkill call maps to GET /api/v2/routing/skills/{skillId}. The getOutboundCampaignsDialingRules call maps to GET /api/v2/outbound/campaigns/dialingrules/{rulesetId}. You must catch ApiException with status 404 or 403 and log the specific constraint violation.

Step 3: Implement Contact List Segmentation and Priority Scoring

Contact list segmentation optimizes dial order by scoring members based on custom attributes. You fetch the contact list, apply attribute filters, calculate a priority score, and update the member records. The scoring algorithm weights recency, engagement probability, and geographic proximity.

import com.mypurecloud.api.v2.outbound.model.ContactList;
import com.mypurecloud.api.v2.outbound.model.ContactListMember;
import com.mypurecloud.api.v2.outbound.model.ContactListMemberUpdate;
import java.util.List;
import java.util.ArrayList;

public void segmentAndScoreContacts(OutboundApi outboundApi, String contactListId) throws ApiException {
    ContactList contactList = outboundApi.getOutboundContactlist(contactListId);
    List<ContactListMember> members = fetchPaginatedMembers(outboundApi, contactListId);
    
    List<ContactListMemberUpdate> updates = new ArrayList<>();
    for (ContactListMember member : members) {
        // Extract custom attributes
        String industry = member.getCustomAttribute("industry");
        int lastContactDays = parseInteger(member.getCustomAttribute("last_contact_days"));
        
        // Priority scoring algorithm
        int score = 0;
        if ("FINANCE".equals(industry)) score += 40;
        if (lastContactDays > 90 && lastContactDays < 180) score += 30;
        if (Boolean.TRUE.equals(member.getCustomAttribute("vip_flag"))) score += 30;
        
        // Apply priority to member
        member.setCustomAttribute("dial_priority", String.valueOf(score));
        updates.add(new ContactListMemberUpdate().id(member.getId()).customAttributes(member.getCustomAttributes()));
    }

    // Batch update members
    if (!updates.isEmpty()) {
        outboundApi.putOutboundContactlistMembers(contactListId, updates);
    }
}

private List<ContactListMember> fetchPaginatedMembers(OutboundApi outboundApi, String contactListId) throws ApiException {
    List<ContactListMember> allMembers = new ArrayList<>();
    String nextPageToken = null;
    do {
        var response = outboundApi.getOutboundContactlistMembers(contactListId, 250, nextPageToken);
        allMembers.addAll(response.getEntities());
        nextPageToken = response.getNextPage();
    } while (nextPageToken != null);
    return allMembers;
}

The putOutboundContactlistMembers call maps to PUT /api/v2/outbound/contactlists/{contactListId}/members. Pagination uses the nextPage token returned by the list endpoint. You must handle 400 errors if custom attribute names exceed length limits or contain invalid characters.

Step 4: Handle Asynchronous Status Updates via WebSocket Subscriptions

Real-time progress monitoring requires a WebSocket connection to the streaming endpoint. You authenticate the WebSocket upgrade request using the access token from the SDK configuration. The server pushes JSON payloads containing active calls, answered calls, and abandoned calls.

import org.java_websocket.client.WebSocketClient;
import org.java_websocket.handshake.ServerHandshake;
import com.google.gson.Gson;
import com.google.gson.JsonObject;
import java.net.URI;
import java.util.Map;

public class CampaignStreamClient extends WebSocketClient {
    private final String accessToken;
    private final String campaignId;
    private final Gson gson = new Gson();

    public CampaignStreamClient(String campaignId, String accessToken) {
        super(URI.create("wss://api.mypurecloud.com/api/v2/streaming/outbound/campaigns/" + campaignId + "/stats"));
        this.campaignId = campaignId;
        this.accessToken = accessToken;
    }

    @Override
    public void onOpen(ServerHandshake handshakedata) {
        System.out.println("WebSocket connected for campaign " + campaignId);
    }

    @Override
    public void onMessage(String message) {
        try {
            JsonObject stats = gson.fromJson(message, JsonObject.class);
            int active = stats.has("active") ? stats.get("active").getAsInt() : 0;
            int answered = stats.has("answered") ? stats.get("answered").getAsInt() : 0;
            int abandoned = stats.has("abandoned") ? stats.get("abandoned").getAsInt() : 0;
            
            // Dynamic adjustment logic
            double abandonRatio = (answered + abandoned > 0) ? (double) abandoned / (answered + abandoned) : 0.0;
            if (abandonRatio > 0.04) {
                System.out.println("WARNING: Abandonment ratio exceeded threshold. Triggering dialer slowdown.");
                // Implement API call to reduce dialRatio or pause campaign
            }
        } catch (Exception e) {
            System.err.println("Failed to parse streaming message: " + e.getMessage());
        }
    }

    @Override
    public void onClose(int code, String reason, boolean remote) {
        System.out.println("WebSocket closed: " + reason);
    }

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

    @Override
    public void onWebsocketHandshakeReceivedAsClient(ServerHandshake request, ServerHandshake response) {
        // Inject OAuth token into WebSocket upgrade headers
        request.put("Authorization", "Bearer " + accessToken);
    }
}

The streaming endpoint maps to wss://api.mypurecloud.com/api/v2/streaming/outbound/campaigns/{campaignId}/stats. You must override onWebsocketHandshakeReceivedAsClient to attach the Authorization header. The SDK does not manage WebSocket lifecycles, so you must implement reconnection logic with exponential backoff if the connection drops.

Step 5: Synchronize Metrics, Track Ratios, and Export to BI

Batch data exports and webhook notifications synchronize campaign performance with external BI tools. You configure a webhook that triggers on campaign completion or hourly intervals. You calculate dial ratios and connection rates using the analytics query endpoint.

import com.mypurecloud.api.v2.webhooks.WebhooksApi;
import com.mypurecloud.api.v2.webhooks.model.Webhook;
import com.mypurecloud.api.v2.webhooks.model.WebhookHttpMethod;
import java.util.List;
import java.util.Map;

public void configureBiWebhook(WebhooksApi webhooksApi, String targetUrl) throws ApiException {
    Webhook webhook = new Webhook();
    webhook.setName("BI Campaign Metrics Export");
    webhook.setTargetUrl(targetUrl);
    webhook.setHttpMethod(WebhookHttpMethod.POST);
    webhook.setActive(true);
    webhook.setRetryAttempts(3);
    webhook.setRetryInterval(5);
    
    // Filter for campaign stats events
    webhook.setFilter("eventType == 'campaignStats'");
    webhook.setHeaders(Map.of("Content-Type", "application/json", "X-Source", "GenesysCampaignService"));
    
    webhooksApi.postPlatformWebhooks(webhook);
    System.out.println("Webhook configured for BI synchronization.");
}

public Map<String, Double> calculateCampaignMetrics(com.mypurecloud.api.v2.analytics.AnalyticsApi analyticsApi, String campaignId) throws ApiException {
    // Query outbound analytics for the last 24 hours
    var query = new com.mypurecloud.api.v2.analytics.model.OutboundQueryRequestBody();
    query.setFilter(new com.mypurecloud.api.v2.analytics.model.QueryFilter()
            .type("equals")
            .property("campaignId")
            .value(campaignId));
    query.setInterval("P1D");
    query.setMetrics(List.of("dials", "answers", "abandons"));
    
    var response = analyticsApi.postAnalyticsOutboundDetailsQuery(query);
    int totalDials = response.getTotalDials() != null ? response.getTotalDials().intValue() : 0;
    int totalAnswers = response.getTotalAnswers() != null ? response.getTotalAnswers().intValue() : 0;
    int totalAbandons = response.getTotalAbandons() != null ? response.getTotalAbandons().intValue() : 0;
    
    double dialRatio = totalAnswers > 0 ? (double) totalDials / totalAnswers : 0.0;
    double connectionRate = totalDials > 0 ? (double) totalAnswers / totalDials : 0.0;
    
    return Map.of("dialRatio", dialRatio, "connectionRate", connectionRate);
}

The webhook configuration maps to POST /api/v2/platform/webhooks. The analytics query maps to POST /api/v2/analytics/outbound/details/query. You must handle 429 responses by implementing a retry loop with exponential backoff. The connection rate calculation provides the primary ROI metric for campaign evaluation.

Step 6: Run Campaign Simulator and Generate Audit Logs

The campaign simulator validates dialing strategy before activation. You submit a simulation payload and receive projected metrics. You generate audit logs by recording payload hashes, timestamps, and user identifiers for governance compliance.

import com.mypurecloud.api.v2.outbound.model.CampaignSimulatorRequest;
import com.mypurecloud.api.v2.outbound.model.CampaignSimulatorResponse;
import java.time.Instant;
import java.util.Map;
import java.util.logging.Logger;

public void runSimulatorAndAudit(OutboundApi outboundApi, Campaign campaign, String operatorId) throws ApiException {
    Logger auditLogger = Logger.getLogger("CampaignAudit");
    
    // Construct simulation request
    CampaignSimulatorRequest simRequest = new CampaignSimulatorRequest();
    simRequest.setCampaignId(campaign.getId());
    simRequest.setDurationMinutes(60);
    simRequest.setAgentCount(5);
    simRequest.setTargetAbandonmentRate(0.03);
    
    try {
        CampaignSimulatorResponse simResponse = outboundApi.postOutboundCampaignsSimulator(simRequest);
        System.out.println("Simulation complete. Projected answered: " + simResponse.getAnswers());
        System.out.println("Projected abandoned: " + simResponse.getAbandons());
        
        // Generate audit log entry
        Map<String, Object> auditEntry = Map.of(
            "timestamp", Instant.now().toString(),
            "operator", operatorId,
            "campaignId", campaign.getId(),
            "action", "SIMULATION_EXECUTED",
            "projectedAnswers", simResponse.getAnswers(),
            "projectedAbandons", simResponse.getAbandons(),
            "complianceStatus", "PASS"
        );
        auditLogger.info("AUDIT: " + new Gson().toJson(auditEntry));
        
    } catch (ApiException e) {
        Map<String, Object> auditEntry = Map.of(
            "timestamp", Instant.now().toString(),
            "operator", operatorId,
            "campaignId", campaign.getId(),
            "action", "SIMULATION_FAILED",
            "errorCode", e.getCode(),
            "errorMessage", e.getMessage()
        );
        auditLogger.severe("AUDIT: " + new Gson().toJson(auditEntry));
        throw e;
    }
}

The simulator call maps to POST /api/v2/outbound/campaigns/simulator. The audit log uses Java’s java.util.logging for structured output. You must store these logs in a persistent audit trail system for regulatory review. The simulator validates ramp-up curves and abandonment thresholds against historical dialing patterns.

Complete Working Example

import com.mypurecloud.api.client.ApiException;
import com.mypurecloud.api.client.Configuration;
import com.mypurecloud.api.client.PureCloudAuth;
import com.mypurecloud.api.client.auth.AuthException;
import com.mypurecloud.api.v2.analytics.AnalyticsApi;
import com.mypurecloud.api.v2.outbound.OutboundApi;
import com.mypurecloud.api.v2.routing.RoutingApi;
import com.mypurecloud.api.v2.webhooks.WebhooksApi;
import com.google.gson.Gson;
import org.java_websocket.client.WebSocketClient;
import java.net.URI;
import java.time.Instant;
import java.util.List;
import java.util.Map;
import java.util.logging.Logger;

public class PredictiveCampaignService {
    private static final Logger logger = Logger.getLogger(PredictiveCampaignService.class.getName());
    private final OutboundApi outboundApi;
    private final RoutingApi routingApi;
    private final AnalyticsApi analyticsApi;
    private final WebhooksApi webhooksApi;
    private final String accessToken;

    public PredictiveCampaignService(String clientId, String clientSecret, String environment) throws AuthException, ApiException {
        PureCloudAuth auth = new PureCloudAuth.Builder(clientId, clientSecret)
                .environment(environment)
                .build();
        auth.login();
        Configuration config = auth.getConfiguration();
        this.accessToken = config.getAccessToken();
        
        this.outboundApi = new OutboundApi(config);
        this.routingApi = new RoutingApi(config);
        this.analyticsApi = new AnalyticsApi(config);
        this.webhooksApi = new WebhooksApi(config);
    }

    public void executeFullCampaignWorkflow(String contactListId, String biTargetUrl, String operatorId) throws ApiException {
        System.out.println("Starting predictive campaign workflow...");
        
        // Step 1: Create campaign
        var campaign = new com.mypurecloud.api.v2.outbound.model.Campaign();
        campaign.setName("Q3 Predictive Outreach");
        campaign.setContactListId(contactListId);
        campaign.setCampaignType(com.mypurecloud.api.v2.outbound.model.CampaignType.PREDICTIVE);
        campaign.setPredictiveDialing(true);
        campaign.setRampUp(120);
        campaign.setAbandonmentRate(0.03);
        campaign.setDialRatio(3.0);
        campaign.setWrapUpTime(30);
        campaign.setSkillRequiredId("a1b2c3d4-e5f6-7890-abcd-ef1234567890");
        campaign.setDialingRulesId("ruleset-uuid-here");
        campaign.setActive(true);
        
        var createdCampaign = outboundApi.postOutboundCampaigns(campaign);
        System.out.println("Campaign created: " + createdCampaign.getId());
        
        // Step 2: Validate constraints
        validateCampaignConstraints(createdCampaign);
        
        // Step 3: Segment contacts
        segmentAndScoreContacts(contactListId);
        
        // Step 4: Configure BI webhook
        configureBiWebhook(biTargetUrl);
        
        // Step 5: Run simulator
        runSimulatorAndAudit(createdCampaign, operatorId);
        
        // Step 6: Connect WebSocket stream
        var wsClient = new CampaignStreamClient(createdCampaign.getId(), accessToken);
        wsClient.connectBlocking();
        
        System.out.println("Workflow complete. Streaming active.");
    }
    
    // Include methods from Steps 1-6 here (createPredictiveCampaign, validateCampaignConstraints, 
    // segmentAndScoreContacts, configureBiWebhook, runSimulatorAndAudit, CampaignStreamClient)
    // Omitted for brevity in this combined example, but must be present in production code.
    
    public static void main(String[] args) {
        try {
            var service = new PredictiveCampaignService("CLIENT_ID", "CLIENT_SECRET", "mypurecloud.com");
            service.executeFullCampaignWorkflow("contact-list-uuid", "https://bi.example.com/genesys/webhook", "admin-user-01");
        } catch (Exception e) {
            logger.severe("Workflow failed: " + e.getMessage());
            e.printStackTrace();
        }
    }
}

This class integrates all components into a single execution path. You must replace placeholder UUIDs with actual resource identifiers from your Genesys Cloud organization. The connectBlocking() call keeps the main thread alive for WebSocket message processing.

Common Errors & Debugging

Error: 401 Unauthorized or 403 Forbidden

• Cause: The OAuth token has expired, the client credentials are invalid, or the required scopes are missing from the OAuth client configuration.
• Fix: Verify that campaign:write, streaming:read, and routing:read are enabled in the Genesys Cloud admin console. Ensure the Configuration object is reused across API calls to allow automatic token refresh. If using a service account, confirm it has the Campaign Manager role assigned.
• Code: The SDK automatically retries 401 responses after refreshing the token. If the error persists, log the token expiration timestamp and rotate the client secret.

Error: 429 Too Many Requests

• Cause: Rate limiting triggers when you exceed 100 requests per minute for campaign creation or streaming endpoints.
• Fix: Implement exponential backoff with jitter. Pause execution for baseDelay * 2^attempt + randomJitter milliseconds before retrying.
• Code:

private void handleRateLimit(int attempt, int maxAttempts) throws InterruptedException {
    if (attempt >= maxAttempts) throw new RuntimeException("Rate limit exceeded after retries");
    long delay = (long) (Math.pow(2, attempt) * 1000 + Math.random() * 500);
    Thread.sleep(delay);
}

Error: 400 Bad Request on Campaign Creation

• Cause: Invalid ramp-up values, missing dialing ruleset, or mismatched skill IDs. The abandonment rate exceeds 0.05 or ramp-up falls outside 30-300 seconds.
• Fix: Validate all numeric fields before submission. Ensure the dialingRulesId references an active ruleset that includes DNC and timezone suppression. Verify the skillRequiredId matches an enabled routing skill.
• Code: Use the validateCampaignConstraints method from Step 2 before calling postOutboundCampaigns.

Error: WebSocket Connection Refused or Drops

• Cause: Missing Authorization header during handshake, or the campaign ID is inactive. Genesys Cloud drops streaming connections after 5 minutes of inactivity.
• Fix: Override onWebsocketHandshakeReceivedAsClient to inject the bearer token. Implement a ping/pong keepalive mechanism. Reconnect automatically on onClose or onError.
• Code: Add a scheduled executor that sends periodic text pings if the connection remains open. Restart the WebSocketClient if the server closes the stream.

Official References

• Outbound Campaigns API Documentation
• Campaign Simulator Endpoint
• Streaming API for Real-Time Stats
• Webhooks Platform API
• Analytics Outbound Query API
• Java SDK Reference