Triggering Architect Flows from Predictive Engagement Action Maps

How-To-Articles
1

Triggering Architect Flows from Predictive Engagement Action Maps

What This Guide Covers

Configure Predictive Engagement Action Maps to route connected outbound calls into Architect Flows instead of static queues or direct routes. The end result is a dynamic routing architecture where campaign metadata, predictive disposition probabilities, and dialer session state pass directly into flow variables for real-time branching, CRM synchronization, and compliance enforcement.

Prerequisites, Roles & Licensing

  • Licensing: Genesys Cloud CX 3 base license with the Predictive Engagement add-on. Architect Flow routing requires CX 3 or higher.
  • Permissions: Predictive Engagement > Campaign > Edit, Predictive Engagement > Action Map > Edit, Architect > Flow > Edit, Routing > Queue > Edit, Telephony > Trunk > Edit, Reporting > Interaction > View.
  • OAuth Scopes: predictive:engagement:read, predictive:engagement:write, flow:read, flow:write, routing:queue:read, interaction:read.
  • External Dependencies: Provisioned SIP trunks with sufficient concurrent session capacity, CRM or middleware endpoint for real-time data updates, and a compliant DNC/DND screening service with sub-500ms response times.

The Implementation Deep-Dive

1. Design the Architect Flow Destination & Parameter Contract

Predictive Engagement does not inject raw campaign records directly into flow execution. It passes a structured context payload containing the contact record ID, campaign ID, action map ID, and dialer session metadata. You must design the Architect Flow to accept these parameters explicitly through the Flow Configuration settings. The dialer grid performs a routing handshake before media pickup, and it validates the flow schema against the Action Map mapping. If the contract fails, the call drops before the flow engine processes the first node.

Navigate to Architect > Flows and create a new flow or clone an existing outbound template. In the Flow Settings panel, enable Accept parameters from external sources. Define input variables that match the Predictive Engagement context schema. The critical variables are contactId, campaignId, actionMapId, dialerSessionId, predictiveScore, and campaignPriority.

The Trap: Defining flow parameters with mismatched data types or relying on implicit string conversion. Predictive Engagement passes predictiveScore as a decimal between 0.0 and 1.0. If you define the flow parameter as an Integer, the flow engine rejects the payload during the routing handshake. The call drops to the fallback destination or terminates immediately. Always declare numeric campaign metrics as Decimal or Number types. Furthermore, marking optional predictive metadata as required causes immediate routing failures when the model pipeline returns incomplete records.

Architect Reasoning: We enforce a strict parameter contract at the flow boundary because Predictive Engagement operates on a high-throughput dialer grid. The dialer grid expects a sub-200ms routing acknowledgment. If the flow engine must perform type coercion or schema validation at call connect time, latency spikes cascade into dropped connections and reduced answer seizure rates. Explicit typing eliminates runtime coercion overhead and guarantees deterministic routing behavior under load.

To validate the parameter contract before deployment, use the Architect Flow API to inspect the flow definition:

GET /api/v2/architect/flows/{flowId}
Authorization: Bearer <token>
Accept: application/json

The response payload contains the inputs array. Verify that each input has a defined type and that required is set to false for optional predictive metadata. Predictive Engagement may omit fields if the campaign does not generate them, so marking everything as required causes immediate routing failures. Additionally, check the version field. Predictive Engagement caches flow references. If you update the flow schema without publishing a new version, the dialer grid continues using the cached schema until the cache expires, which typically takes 15 minutes. Always publish a new version and update the Action Map reference after schema changes.

2. Configure the Action Map with Flow Routing & Context Mapping

Action Maps dictate the routing behavior for each campaign outcome. When a Predictive Engagement call connects, the system evaluates the Action Map rules. You must replace the legacy Queue or Direct Route destination with the Architect Flow destination type. The Action Map acts as the stateless routing contract that injects campaign context into the flow execution context.

Navigate to Predictive Engagement > Action Maps. Select your target action map and edit the Connected rule. Change the Destination Type to Architect Flow. Select the flow you configured in Step 1. The interface exposes a Parameter Mapping grid. Map the Predictive Engagement system fields to your flow inputs. Standard mappings include:

  • contactId → Flow input contactId
  • campaignId → Flow input campaignId
  • predictiveScore → Flow input predictiveScore
  • dialerSessionId → Flow input dialerSessionId

The Trap: Mapping the predictiveScore to a flow variable without implementing a fallback default value. Predictive models occasionally return null scores during model retraining or data pipeline delays. If the score is null and the flow expects a value, the routing engine cannot evaluate downstream conditional nodes, resulting in a silent drop to the flow error handler or an abandoned call. Always configure a default value in the Action Map mapping grid. Additionally, avoid mapping large string payloads (such as full CRM URLs or JSON blobs) into flow parameters. The routing handshake payload has a 4KB limit. Exceeding this limit causes the dialer to reject the routing request and terminate the call.

Architect Reasoning: We use the Action Map as the routing contract layer because it decouples campaign strategy from flow logic. If you hardcode campaign routing inside the flow, you create tight coupling that breaks when marketing changes targeting rules. The Action Map allows flow developers to optimize call handling logic without touching campaign configuration, and vice versa. This separation also enables A/B testing at the routing layer. You can route the same campaign to two different flow versions by splitting traffic in the Action Map rules, which is impossible if routing is embedded in the flow.

For programmatic deployment, use the Action Map Update API. Note that the destination payload requires the exact flow ID and a parameter mapping array:

PUT /api/v2/predictive/engagement/action-maps/{actionMapId}
Authorization: Bearer <token>
Content-Type: application/json

{
  "name": "PE_Campaign_Outbound_Flow_Routing",
  "rules": [
    {
      "name": "Connected_Rule",
      "condition": "true",
      "destinationType": "flow",
      "destinationId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "parameterMappings": [
        {
          "sourceField": "contactId",
          "targetField": "contactId"
        },
        {
          "sourceField": "campaignId",
          "targetField": "campaignId"
        },
        {
          "sourceField": "predictiveScore",
          "targetField": "predictiveScore",
          "defaultValue": "0.5"
        },
        {
          "sourceField": "dialerSessionId",
          "targetField": "dialerSessionId"
        }
      ]
    }
  ]
}

The API enforces schema validation. If destinationId does not reference a published flow, the request returns a 400 Bad Request with invalid_destination_reference. Always publish the flow before linking it in the Action Map. The API also validates that destinationType matches the referenced resource. Routing to a flow ID with destinationType: queue returns a 409 Conflict.

3. Implement Flow-Level Dialer State Handling & Timeout Logic

Once the call connects and routes into the flow, Predictive Engagement maintains a dialer session that expects the flow to handle the media stream. The flow must manage three critical states: media pickup, agent transfer, and call termination. Predictive Engagement does not hold the call while the flow executes logic. If the flow runs data lookups or API calls before answering, the caller hears silence or a disconnect.

Structure the flow with an immediate Play Prompt or Transfer to Queue node at the root. If you require data enrichment, execute asynchronous lookups in parallel using the Make REST Request node with a timeout set to 2000ms. Route the response to a conditional split that branches based on CRM availability. Never block the media path for synchronous database queries. The SIP INVITE from the dialer grid expects a 200 OK response within 3 seconds. If the flow delays media pickup, the SIP stack drops the call.

The Trap: Configuring the flow to transfer to a queue without preserving the Predictive Engagement session metadata. When a flow transfers a call to a routing queue, the original dialer session context is stripped unless you explicitly pass the dialerSessionId and campaignId as queue interaction attributes. Without these attributes, wrap-up codes, disposition tracking, and predictive model feedback loops break. The campaign will register the call as abandoned or unknown, degrading model accuracy.

Architect Reasoning: We preserve session metadata through queue transfers because Predictive Engagement relies on closed-loop feedback to adjust dialing rates and predictive scores. The dialer grid uses disposition data to calculate answer seizure rates and adjust the predictive algorithm in near real-time. If the flow drops the metadata, the campaign loses its feedback signal, causing the dialer to either throttle aggressively or dial too aggressively. Metadata preservation is not optional for predictive campaigns. Furthermore, preserving metadata enables accurate WEM (Workforce Engagement Management) reporting. If you integrate WEM, the recording system requires the dialerSessionId to correlate IVR audio with agent conversation segments.

To pass metadata during a queue transfer, use the Transfer to Queue node configuration. In the Attributes section, add key-value pairs:

  • predictive.campaignId = {campaignId}
  • predictive.dialerSessionId = {dialerSessionId}
  • predictive.score = {predictiveScore}

These attributes become available in the routing interaction object and are exposed to the WFM and Analytics pipelines. If you integrate with a CRM via middleware, include the same attributes in the HTTP payload to ensure downstream systems correlate the call with the correct campaign record. Use the Data Transformation node to format the payload before the REST call. Avoid embedding the entire interaction object in the CRM payload. Extract only the required fields to reduce middleware processing time.

4. Deploy Campaign with Throttling & Compliance Guardrails

Predictive Engagement calculates dialing rates based on historical answer rates, agent availability, and campaign priorities. When routing to Architect Flows, you must account for flow execution latency in the campaign throttling configuration. The dialer grid assumes a standard queue transfer latency of approximately 800ms. Architect Flows with media playback or conditional routing add 1.5 to 3 seconds of latency before the call reaches an agent or disposition node.

Navigate to Predictive Engagement > Campaigns and edit the target campaign. In the Dialing Rules section, adjust the Maximum Expected Answer Rate and Agent Availability Threshold. Reduce the maximum concurrent calls per trunk by 15 percent to accommodate flow processing overhead. Enable Compliance Screening and map the campaign to your DNC/DND list. Predictive Engagement checks compliance at dial time, but if the flow modifies the contact record during execution, the compliance state does not retroactively apply to the current call.

The Trap: Leaving the default Call Setup Timeout at 30 seconds while routing to complex flows. Predictive Engagement terminates the dialer session if the flow does not answer or transfer within the configured timeout. Complex flows with multiple REST calls, data splits, and media nodes frequently exceed 30 seconds under load. The dialer registers these as network failures, which triggers campaign throttling and degrades the predictive model. Set the Call Setup Timeout to 45 seconds for flow-routed campaigns, and implement flow-level error handlers that disposition the call as No_Agent_Available rather than letting it timeout silently.

Architect Reasoning: We adjust the call setup timeout and reduce concurrent call targets because Architect Flows introduce variable latency that the predictive algorithm cannot predict at dial time. The predictive model optimizes for queue-based routing where latency is deterministic. Flow routing introduces branching logic, media playback, and external API calls that create non-deterministic execution paths. Compensating with reduced concurrency and extended timeouts prevents false negative feedback to the predictive engine while maintaining acceptable service levels. Additionally, trunk capacity must account for flow media streams. If a flow plays a 10-second prompt before transferring, the SIP session remains active and consumes trunk capacity. Reducing concurrency prevents trunk overflow during peak flow execution windows.

To validate campaign throttling behavior, monitor the Campaign Performance dashboard. Track the Answer Seizure Rate and Flow Routing Latency metrics. If latency exceeds 4 seconds consistently, the flow contains blocking operations. Refactor the flow to execute non-critical lookups asynchronously or cache data in flow variables during the initial prompt playback. Use the Split Merge node to parallelize independent data paths. Monitor the Trunk Utilization metric in the Telephony dashboard. If utilization exceeds 85 percent during flow execution, reduce the campaign concurrent call limit by 10 percent increments until utilization stabilizes below 75 percent.

Validation, Edge Cases & Troubleshooting

Edge Case 1: Flow Execution Timeout vs. Dialer Hold Timeout

The failure condition: Calls connect successfully but drop to a generic disconnect tone after 30 seconds. Campaign reports show high call setup failures.
The root cause: The Architect Flow executes a sequential chain of REST requests or data processing nodes that exceed the Predictive Engagement Call Setup Timeout. The dialer grid assumes the call is stuck and terminates the session to preserve trunk capacity.
The solution: Increase the campaign Call Setup Timeout to 45 seconds. Refactor the flow to parallelize REST requests using the Split Merge node with a Join condition set to Any. Implement a flow-level Timeout node that routes to a fallback queue or disposition if execution exceeds 20 seconds. Monitor the Flow Execution Time metric in Architect Analytics to identify blocking nodes. Use the Interaction API to trace failed calls:

GET /api/v2/analytics/interactions/query
Authorization: Bearer <token>
Content-Type: application/json

{
  "timeFilter": {
    "type": "relative",
    "value":