Triggering Proactive Web Messaging Invites using the Genesys Predictive Engagement API
What This Guide Covers
This guide details the architectural implementation of API-driven Predictive Engagement campaigns that programmatically fire proactive Web Chat invites based on real-time behavioral signals. You will configure the campaign schema, inject dynamic session context, assign routing targets, and execute the trigger endpoint with production-grade payloads. The result is a fully automated, externally orchestrated invite flow that bypasses static UI rule limits and integrates directly with your downstream analytics or ML scoring pipelines.
Prerequisites, Roles & Licensing
- Licensing Tier: Genesys Cloud CX 3 or CX One with the Predictive Engagement add-on. Web Chat requires the CX 1 base license minimum, but proactive invite evaluation consumes PE capacity.
- Permission Strings:
Predictive Engagement > Campaign > EditPredictive Engagement > Campaign > ReadWeb Chat > Invite > SendRouting > Queue > ReadRouting > Skill Group > Read
- OAuth Scopes:
predictiveengagement:campaign:read,predictiveengagement:campaign:write,webchat:invite:send,conversation:write,routing:queue:read - External Dependencies:
- Genesys Web Chat embed configured with
proactive: truecapability - Real-time data source (CDP, event stream, or external ML model) capable of pushing JSON payloads to your orchestration layer
- Queue or skill group designated for web messaging routing
- Genesys Web Chat embed configured with
The Implementation Deep-Dive
1. Campaign Schema Definition & Real-Time Filter Configuration
Predictive Engagement campaigns in Genesys Cloud operate as evaluation engines rather than static broadcast tools. When you drive invites via API, you are essentially submitting a contact session into the PE evaluation pipeline and requesting a deterministic decision. The campaign schema must explicitly define which signals qualify for an invite, how those signals are weighted, and what action fires upon a positive evaluation.
The campaign creation payload requires a structured filters array that maps to real-time attributes. These attributes are evaluated at trigger time, not at campaign creation time. You must design the filter schema to accept dynamic values from your orchestration layer.
Production Payload: Campaign Creation
POST /api/v2/analytics/predictiveengagement/campaigns
Authorization: Bearer <access_token>
Content-Type: application/json
{
"name": "API-Driven Proactive Web Invite",
"description": "Programmatically triggered web chat invite based on external ML churn score and page dwell time",
"enabled": true,
"campaignType": "proactive",
"evaluationMode": "realtime",
"filters": [
{
"attributeName": "external.churn_probability",
"operator": "greater_than",
"value": 0.72,
"dataType": "float"
},
{
"attributeName": "session.dwell_time_seconds",
"operator": "greater_than",
"value": 45,
"dataType": "integer"
},
{
"attributeName": "contact.is_authenticated",
"operator": "equals",
"value": true,
"dataType": "boolean"
}
],
"actions": [
{
"type": "webchat_invite",
"priority": 1,
"config": {
"inviteMessage": "We noticed you reviewing pricing. Would you like to speak with a specialist?",
"displayDuration": 300,
"autoDismissOnScroll": false
}
}
],
"throttling": {
"maxInvitesPerContact": 1,
"cooldownSeconds": 86400,
"maxInvitesPerMinute": 500
}
}
Architectural Reasoning:
We structure the filters array to reference external.* and session.* namespaces. This prevents collision with native Genesys contact attributes and allows your middleware to inject arbitrary signals without modifying the campaign schema. The evaluationMode: realtime directive forces the PE engine to evaluate the payload immediately upon trigger receipt rather than batching it for later processing. This is critical for web messaging because user intent decays within seconds.
The Trap:
Configuring evaluationMode as batch while expecting immediate invite delivery. Batch mode queues trigger requests for asynchronous processing, which introduces 30 to 120 second delays depending on system load. For web messaging, this delay guarantees the user has already navigated away or completed the action that triggered the signal. Always use realtime for conversational channels with sub-minute intent windows.
2. Web Chat Invite Action Routing & Queue Assignment
The webchat_invite action does not route the conversation itself. It only pushes the invite UI element to the client embed. When the user accepts the invite, Genesys Cloud instantiates a webchat conversation and routes it according to the routing configuration attached to the campaign or the underlying channel. You must explicitly bind the campaign to a routing target to prevent the conversation from falling into the default overflow queue.
Routing assignment happens at the action level through the routingConfig object. This object dictates how the resulting conversation is distributed across agents or virtual agents.
Production Payload: Routing Configuration Injection
{
"actions": [
{
"type": "webchat_invite",
"priority": 1,
"config": {
"inviteMessage": "Need assistance with your order status?",
"displayDuration": 300,
"autoDismissOnScroll": false
},
"routingConfig": {
"queueId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"skillGroups": ["web_support_tier1"],
"wrapUpCode": "proactive_invite_accepted",
"priorityLevel": 5,
"overflowQueueId": "x9y8z7w6-v5u4-3210-dcba-fe0987654321"
}
}
]
}
Architectural Reasoning:
We assign a specific queueId and skillGroups array to ensure the conversation lands in a dedicated routing pool. Proactive invites generate higher intent conversations than inbound web chat, so isolating them in a tiered queue prevents them from competing with low-priority inbound traffic. The priorityLevel: 5 ensures the conversation moves to the front of the routing queue once an agent becomes available. We also define an overflowQueueId to handle capacity spikes without dropping the conversation into the global default queue.
The Trap:
Omitting skillGroups or queueId in the routingConfig. When these fields are absent, Genesys Cloud falls back to the channel-level default routing, which typically targets a shared general support queue. This creates skill mismatch, increases average handle time, and inflates abandon rates because specialized agents are bypassed. Always explicitly define routing targets at the action level to maintain intent-to-agent alignment.
3. Programmatic Trigger Execution & Session Context Injection
The trigger endpoint is where your orchestration layer hands off the evaluation request to the PE engine. You must inject the contact identifier, channel context, and the real-time signal payload that matches the campaign filter schema. The PE engine compares the injected attributes against the campaign filters and returns a deterministic decision.
Production Payload: Campaign Trigger
POST /api/v2/analytics/predictiveengagement/campaigns/{campaignId}/trigger
Authorization: Bearer <access_token>
Content-Type: application/json
{
"contactId": "ext:customer_8842910",
"channelId": "webchat:primary_embed",
"sessionData": {
"external.churn_probability": 0.87,
"session.dwell_time_seconds": 52,
"contact.is_authenticated": true,
"browser.locale": "en-US",
"referrer.page": "/pricing/enterprise"
},
"evaluationContext": {
"timestamp": "2024-05-21T14:32:11Z",
"requestId": "req_9f8e7d6c5b4a",
"correlationId": "corr_web_invite_4421"
}
}
Architectural Reasoning:
We use the ext: prefix for contactId to indicate an external identifier mapping. This allows your CDP or CRM to own the identity resolution while Genesys Cloud maintains the conversational state. The sessionData object must exactly match the attributeName keys defined in the campaign filters. Mismatched keys cause silent filter failures, which the PE engine interprets as negative evaluations. The evaluationContext block provides traceability for debugging and audit logging. We include correlationId to link the trigger request to downstream conversation events in Genesys Cloud analytics.
The Trap:
Injecting sessionData attributes with mismatched data types. If the campaign filter defines dataType: float but the trigger payload sends a string "0.87", the PE engine performs a strict type comparison and evaluates the condition as false. This results in zero invite deliveries without generating explicit error responses. Always cast numeric values to their native JSON types before serialization. Use schema validation middleware to enforce type consistency before calling the trigger endpoint.
4. Evaluation Mode Selection & Throttle Architecture
Throttling in Predictive Engagement operates at three levels: contact-level frequency capping, campaign-level rate limiting, and system-level backpressure. When triggering via API, you must respect these boundaries to avoid invite fatigue and API throttling penalties.
The throttling object in the campaign schema defines the hard limits. The maxInvitesPerContact and cooldownSeconds fields enforce suppression logic. If a contact receives an invite, the PE engine records a suppression token in the contact profile. Subsequent trigger requests within the cooldown window return a suppressed status without consuming evaluation capacity.
Architectural Reasoning:
We configure cooldownSeconds: 86400 to prevent re-engagement within 24 hours. Web messaging invites have high conversion potential but also high annoyance risk when repeated. The maxInvitesPerMinute: 500 protects the PE evaluation pipeline from burst traffic originating from your event stream. When your middleware detects a traffic spike, it should implement client-side exponential backoff before retrying suppressed or throttled requests.
The Trap:
Disabling throttling to achieve maximum invite volume. Setting maxInvitesPerContact to 0 or omitting the throttling block removes suppression logic entirely. This causes the PE engine to evaluate every trigger request independently, resulting in multiple invites for the same session. Users perceive this as aggressive marketing, which increases opt-out rates and triggers Web Chat embed rate limits. Always enforce contact-level cooldowns and campaign-level rate caps to preserve channel reputation and maintain API stability.
Validation, Edge Cases & Troubleshooting
Edge Case 1: Invite Suppression and Frequency Capping Collisions
The Failure Condition:
Your orchestration layer sends a trigger request, but the Web Chat embed never displays the invite. The API response returns 200 OK with status: "suppressed".
The Root Cause:
The contact already received an invite within the configured cooldown window, or the contact profile contains a legacy suppression token from a previous UI-configured campaign sharing the same routing queue. Genesys Cloud consolidates suppression logic across all campaigns targeting the same contact identifier. If any campaign fired an invite within the cooldown period, the PE engine blocks subsequent requests to prevent overlap.
The Solution:
Query the contact suppression state before triggering. Use the GET /api/v2/analytics/predictiveengagement/contacts/{contactId}/suppression endpoint to verify the current cooldown status. If the response indicates an active suppression window, defer the trigger request until the expiresAt timestamp passes. Alternatively, assign a unique campaignId per signal type and configure distinct cooldown windows to prevent cross-campaign suppression collisions.
Edge Case 2: Session Context Loss on Cross-Domain Redirects
The Failure Condition:
The trigger request succeeds, but the invite fails to render when the user navigates to a subdomain or external partner page. The Web Chat embed remains hidden or shows a loading state indefinitely.
The Root Cause:
The Web Chat embed relies on session cookies and localStorage to maintain state. Cross-domain redirects break the session persistence layer, causing the embed to lose the channelId and contactId mapping. The PE engine delivered the invite payload to the original domain context, but the client-side SDK cannot correlate it to the new navigation state.
The Solution:
Implement domain-agnostic session tracking using the externalId parameter in the Web Chat embed configuration. Pass the contactId and correlationId through URL query parameters or a secure cross-domain messaging protocol. Configure the embed to rehydrate the session on page load using genesys.cloud.webchat.initialize({ sessionContext: { contactId: "...", correlationId: "..." } }). This ensures the invite payload remains bound to the user session regardless of navigation boundaries.
Edge Case 3: API Rate Limiting and Campaign Evaluation Backpressure
The Failure Condition:
Your orchestration layer experiences intermittent 429 Too Many Requests responses from the trigger endpoint. Campaign evaluation latency spikes, and invite delivery drops by 40 percent during peak traffic windows.
The Root Cause:
The PE evaluation pipeline enforces per-tenant rate limits based on your licensing tier and concurrent evaluation capacity. Burst traffic from your event stream exceeds the maxInvitesPerMinute threshold, causing the API gateway to throttle requests. The PE engine queues excess evaluations, which increases processing latency and causes invite timeouts on the client side.
The Solution:
Implement a token bucket rate limiter in your orchestration layer that aligns with the maxInvitesPerMinute campaign setting. Distribute trigger requests across multiple worker threads with jittered retry logic. Monitor the X-RateLimit-Remaining and X-RateLimit-Reset headers in API responses to dynamically adjust throughput. If sustained high volume is required, request a capacity increase from Genesys Cloud support and upgrade to the PE High-Throughput tier, which raises the evaluation concurrency limit and reduces queue depth.