Sending Genesys Cloud Web Messaging Proactive Campaigns via Guest API with Python

What You Will Build

• A Python module that constructs proactive web messaging campaign payloads with segment references, template matrices, and delivery schedules, then dispatches them via the Genesys Cloud Web Chat and Guest APIs.
• The script uses the genesys-cloud-purecloud-platform-client SDK and httpx for HTTP operations with full schema validation, opt-out verification, timezone alignment, and rate limiting.
• Language: Python 3.9+

Prerequisites

• OAuth 2.0 client credentials grant configured in Genesys Cloud Admin
• Required scopes: webchat:session:create, webchat:message:send, guest:contact:view, analytics:query, webchat:proactive:send
• Genesys Cloud Python SDK genesys-cloud-purecloud-platform-client>=100.0.0
• Python 3.9+ runtime
• External dependencies: httpx>=0.25.0, pydantic>=2.0.0, pytz>=2023.3, aiofiles>=23.0.0

Authentication Setup

Genesys Cloud uses a standard OAuth 2.0 client credentials flow. The following implementation caches the access token and automatically refreshes it before expiration. The token request targets /oauth/token and returns a JSON payload containing access_token and expires_in.

import httpx
import time
from dataclasses import dataclass
from typing import Optional

@dataclass
class OauthClient:
    client_id: str
    client_secret: str
    base_url: str = "https://api.mypurecloud.com"
    _token: Optional[str] = None
    _expires_at: float = 0.0

    async def get_token(self) -> str:
        if self._token and time.time() < self._expires_at:
            return self._token
        
        async with httpx.AsyncClient(timeout=10.0) as client:
            response = await client.post(
                f"{self.base_url}/oauth/token",
                headers={"Content-Type": "application/x-www-form-urlencoded"},
                data={
                    "grant_type": "client_credentials",
                    "client_id": self.client_id,
                    "client_secret": self.client_secret,
                    "scope": "webchat:session:create webchat:message:send guest:contact:view analytics:query"
                }
            )
            
            if response.status_code in (401, 403):
                raise PermissionError(f"OAuth authentication failed: {response.text}")
            
            response.raise_for_status()
            token_data = response.json()
            self._token = token_data["access_token"]
            self._expires_at = time.time() + token_data["expires_in"] - 60
            return self._token

HTTP Request Cycle

• Method: POST
• Path: /oauth/token
• Headers: Content-Type: application/x-www-form-urlencoded
• Body: grant_type=client_credentials&client_id={id}&client_secret={secret}&scope=webchat:session:create%20webchat:message:send%20guest:contact:view%20analytics:query
• Response: {"access_token": "eyJhbGci...", "token_type": "Bearer", "expires_in": 7200}

Implementation

Step 1: Campaign Payload Construction & Schema Validation

Campaign payloads must reference a segment ID, define a template matrix, and specify delivery schedules. The Genesys Cloud frontend enforces strict push constraints and maximum frequency limits. Pydantic validates the schema before dispatch to prevent 400 Bad Request failures.

from pydantic import BaseModel, Field, field_validator
from datetime import datetime
from typing import List

class DeliverySchedule(BaseModel):
    start_time: datetime
    end_time: datetime
    timezone: str = Field(default="America/New_York")

class TemplateMatrix(BaseModel):
    primary_message: str
    fallback_message: str
    max_frequency_per_day: int = Field(default=3, le=5)
    frontend_push_limit: int = Field(default=10, le=20)

class CampaignPayload(BaseModel):
    segment_id: str
    template: TemplateMatrix
    schedule: DeliverySchedule
    channel: str = "WEBCHAT"
    tags: List[str] = Field(default_factory=list)

    @field_validator("template")
    @classmethod
    def validate_frequency_constraints(cls, v: TemplateMatrix, info) -> TemplateMatrix:
        if v.max_frequency_per_day > v.frontend_push_limit:
            raise ValueError("Frequency limit exceeds frontend push constraint")
        return v

OAuth Scope Required: webchat:proactive:send
Expected Validation Output: Raises pydantic.ValidationError if max_frequency_per_day exceeds frontend_push_limit or if segment_id is missing.

Step 2: Guest Validation Pipeline (Opt-Out & Timezone)

Before dispatch, the system must verify guest opt-out status and align delivery timezones. The Guest API endpoint /api/v2/guest/contacts/{contactId} returns communication preferences. The pipeline filters out suppressed contacts and shifts schedule boundaries to the guest local timezone.

import pytz
from datetime import timedelta

class GuestValidator:
    def __init__(self, oauth: OauthClient):
        self.oauth = oauth
        self.base_url = oauth.base_url

    async def check_opt_out_and_timezone(self, contact_id: str, payload: CampaignPayload) -> bool:
        token = await self.oauth.get_token()
        headers = {"Authorization": f"Bearer {token}", "Accept": "application/json"}
        
        async with httpx.AsyncClient(timeout=10.0) as client:
            response = await client.get(
                f"{self.base_url}/api/v2/guest/contacts/{contact_id}",
                headers=headers
            )
            
            if response.status_code == 404:
                return False
            response.raise_for_status()
            
            guest_data = response.json()
            opt_out_status = guest_data.get("optOut", False)
            if opt_out_status:
                return False
            
            guest_tz_str = guest_data.get("timezone", "UTC")
            try:
                guest_tz = pytz.timezone(guest_tz_str)
                payload_tz = pytz.timezone(payload.schedule.timezone)
                
                local_start = payload.schedule.start_time.astimezone(guest_tz)
                local_end = payload.schedule.end_time.astimezone(guest_tz)
                
                payload.schedule.start_time = local_start
                payload.schedule.end_time = local_end
                return True
            except pytz.exceptions.UnknownTimeZoneError:
                return False

OAuth Scope Required: guest:contact:view
HTTP Request Cycle

• Method: GET
• Path: /api/v2/guest/contacts/{contactId}
• Headers: Authorization: Bearer {token}, Accept: application/json
• Response: {"id": "guest-123", "optOut": false, "timezone": "America/Chicago", "email": "user@example.com", "createdDate": "2023-10-01T12:00:00.000Z"}

Step 3: Atomic Dispatch & Rate Limiting

Dispatch uses an atomic POST to /api/v2/webchat/sessions. The implementation includes exponential backoff for 429 Too Many Requests responses and verifies the response format matches the expected session structure.

import asyncio
import json
import logging

logger = logging.getLogger(__name__)

class CampaignDispatcher:
    def __init__(self, oauth: OauthClient):
        self.oauth = oauth
        self.base_url = oauth.base_url

    async def _safe_post(self, url: str, headers: dict, json_payload: dict) -> dict:
        max_retries = 5
        base_delay = 1.0
        
        async with httpx.AsyncClient(timeout=15.0) as client:
            for attempt in range(max_retries):
                response = await client.post(url, headers=headers, json=json_payload)
                
                if response.status_code == 429:
                    retry_after = float(response.headers.get("Retry-After", base_delay * (2 ** attempt)))
                    logger.warning(f"Rate limited (429). Retrying in {retry_after:.2f}s")
                    await asyncio.sleep(retry_after)
                    continue
                
                response.raise_for_status()
                return response.json()
                
        raise RuntimeError("Max retries exceeded due to rate limiting")

    async def dispatch_session(self, payload: CampaignPayload, contact_id: str) -> dict:
        token = await self.oauth.get_token()
        headers = {
            "Authorization": f"Bearer {token}",
            "Content-Type": "application/json",
            "Accept": "application/json"
        }
        
        session_body = {
            "channel": payload.channel,
            "routingData": {
                "segmentId": payload.segment_id,
                "tags": payload.tags
            },
            "guest": {
                "id": contact_id,
                "name": f"Guest_{contact_id}"
            },
            "proactive": {
                "enabled": True,
                "message": payload.template.primary_message,
                "fallbackMessage": payload.template.fallback_message
            }
        }
        
        result = await self._safe_post(
            f"{self.base_url}/api/v2/webchat/sessions",
            headers,
            session_body
        )
        
        if "id" not in result or "state" not in result:
            raise ValueError(f"Invalid session response format: {result}")
            
        return result

OAuth Scope Required: webchat:session:create
HTTP Request Cycle

• Method: POST
• Path: /api/v2/webchat/sessions
• Headers: Authorization: Bearer {token}, Content-Type: application/json
• Body: {"channel": "WEBCHAT", "routingData": {"segmentId": "seg-987", "tags": ["promo-q4"]}, "guest": {"id": "guest-123", "name": "Guest_guest-123"}, "proactive": {"enabled": true, "message": "Welcome! Check our new offers.", "fallbackMessage": "How can we help?"}}
• Response: {"id": "session-abc-123", "state": "INITIATED", "channel": "WEBCHAT", "createdDate": "2023-10-25T14:30:00.000Z", "guestId": "guest-123"}

Step 4: Webhook Sync, Metrics Tracking, & Audit Logs

After dispatch, the system synchronizes events to an external marketing automation tool via webhook, tracks latency and open rates using the Analytics API, and writes audit logs. The analytics query uses pagination to handle large result sets.

from datetime import datetime, timedelta

class CampaignSync:
    def __init__(self, oauth: OauthClient, webhook_url: str):
        self.oauth = oauth
        self.base_url = oauth.base_url
        self.webhook_url = webhook_url

    async def sync_to_webhook(self, event: dict) -> None:
        async with httpx.AsyncClient(timeout=10.0) as client:
            response = await client.post(
                self.webhook_url,
                json={"eventType": "campaign_dispatch", "timestamp": datetime.utcnow().isoformat(), "data": event}
            )
            if response.status_code >= 400:
                logger.error(f"Webhook sync failed: {response.status_code} {response.text}")

    async def fetch_analytics(self, session_id: str, page: int = 1, size: int = 25) -> dict:
        token = await self.oauth.get_token()
        headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json", "Accept": "application/json"}
        
        query_body = {
            "viewId": "conversationDetail",
            "groupBy": [],
            "where": f"sessionId eq '{session_id}'",
            "timeFrame": {
                "start": (datetime.utcnow() - timedelta(days=7)).isoformat(),
                "end": datetime.utcnow().isoformat()
            },
            "size": size,
            "page": page
        }
        
        async with httpx.AsyncClient(timeout=15.0) as client:
            response = await client.post(
                f"{self.base_url}/api/v2/analytics/conversations/details/query",
                headers=headers,
                json=query_body
            )
            response.raise_for_status()
            return response.json()

    async def calculate_metrics(self, session_id: str) -> dict:
        analytics = await self.fetch_analytics(session_id)
        total_conversations = analytics.get("total", 0)
        open_rate = 0.0
        avg_latency_ms = 0.0
        
        if total_conversations > 0:
            open_rate = (analytics.get("openedCount", 0) / total_conversations) * 100
            latencies = [c.get("duration", 0) for c in analytics.get("entities", [])]
            avg_latency_ms = sum(latencies) / len(latencies) if latencies else 0.0
            
        return {"openRate": round(open_rate, 2), "avgLatencyMs": round(avg_latency_ms, 2)}

    async def write_audit_log(self, log_entry: dict) -> None:
        log_file = "campaign_audit.log"
        async with aiofiles.open(log_file, mode="a") as f:
            await f.write(json.dumps(log_entry) + "\n")

OAuth Scope Required: analytics:query
Pagination Note: The analytics endpoint returns total, count, and entities. The page and size parameters control pagination. The implementation fetches page 1 by default but can be looped to aggregate larger datasets.

Complete Working Example

The following script combines all components into a runnable module. Replace placeholder credentials and IDs before execution.

import asyncio
import logging
import aiofiles
from datetime import datetime, timedelta
import pytz

logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
logger = logging.getLogger(__name__)

async def run_campaign():
    oauth = OauthClient(client_id="your_client_id", client_secret="your_client_secret")
    validator = GuestValidator(oauth)
    dispatcher = CampaignDispatcher(oauth)
    sync = CampaignSync(oauth, webhook_url="https://your-marketing-tool.com/webhook/genesys")
    
    payload = CampaignPayload(
        segment_id="seg-promo-2023-q4",
        template=TemplateMatrix(
            primary_message="Exclusive offer inside!",
            fallback_message="Need assistance?",
            max_frequency_per_day=2,
            frontend_push_limit=5
        ),
        schedule=DeliverySchedule(
            start_time=datetime(2023, 11, 1, 9, 0, 0),
            end_time=datetime(2023, 11, 1, 17, 0, 0),
            timezone="America/New_York"
        ),
        tags=["webchat", "proactive", "q4-campaign"]
    )
    
    contact_ids = ["guest-123", "guest-456", "guest-789"]
    
    for cid in contact_ids:
        try:
            is_valid = await validator.check_opt_out_and_timezone(cid, payload)
            if not is_valid:
                logger.info(f"Contact {cid} skipped due to opt-out or timezone mismatch")
                continue
                
            session_result = await dispatcher.dispatch_session(payload, cid)
            logger.info(f"Dispatched session {session_result['id']} for {cid}")
            
            await sync.sync_to_webhook({"contactId": cid, "sessionId": session_result["id"], "status": "dispatched"})
            
            metrics = await sync.calculate_metrics(session_result["id"])
            audit_entry = {
                "timestamp": datetime.utcnow().isoformat(),
                "contactId": cid,
                "sessionId": session_result["id"],
                "metrics": metrics,
                "campaignId": payload.segment_id
            }
            await sync.write_audit_log(audit_entry)
            
        except Exception as e:
            logger.error(f"Failed processing contact {cid}: {str(e)}")
            
if __name__ == "__main__":
    asyncio.run(run_campaign())

Common Errors & Debugging

Error: 401 Unauthorized

• What causes it: Expired OAuth token, invalid client credentials, or missing Authorization header.
• How to fix it: Verify the client ID and secret match the OAuth client in Genesys Cloud Admin. Ensure the OauthClient class refreshes the token before expiration. The implementation caches the token and subtracts 60 seconds from the TTL to prevent boundary failures.
• Code showing the fix: The get_token method checks time.time() < self._expires_at and re-fetches the token automatically.

Error: 403 Forbidden

• What causes it: The OAuth client lacks the required scopes for the requested endpoint.
• How to fix it: Add the missing scope to the scope parameter during token generation and regenerate the token. For web messaging, webchat:session:create and webchat:message:send are mandatory.
• Code showing the fix: Update the scope string in OauthClient.get_token() to include all required permissions.

Error: 429 Too Many Requests

• What causes it: Exceeding Genesys Cloud API rate limits, typically 20-30 requests per second per client.
• How to fix it: Implement exponential backoff. The _safe_post method reads the Retry-After header or calculates delay using base_delay * (2 ** attempt). It retries up to 5 times before raising a runtime error.
• Code showing the fix: See CampaignDispatcher._safe_post implementation with the 429 status check and asyncio.sleep delay.

Error: 400 Bad Request (Schema Validation)

• What causes it: Payload violates frontend push constraints or frequency limits.
• How to fix it: Adjust max_frequency_per_day to be less than or equal to frontend_push_limit. The Pydantic validator validate_frequency_constraints catches this before the HTTP request is sent.
• Code showing the fix: Modify TemplateMatrix values to respect le=5 and le=20 constraints, or update the field_validator logic to match business rules.

Error: 409 Conflict (Opt-Out Status)

• What causes it: Attempting to message a contact flagged as optOut: true in the Guest API.
• How to fix it: The GuestValidator.check_opt_out_and_timezone method returns False when optOut is true. The main loop skips dispatch and logs the suppression.
• Code showing the fix: The run_campaign loop checks is_valid and continues without calling dispatcher.dispatch_session.

Official References

• Genesys Cloud OAuth 2.0 Documentation
• Web Chat Sessions API
• Guest Contacts API
• Analytics Conversations Query API
• Python SDK Reference