Agentic Workflow for Automated Upsell and Cross-Sell Opportunity Triggers

This foundational agent ingests and fuses data from the PMS, CRM, loyalty platform, and booking engine to build a real-time guest profile. It identifies key signals: special occasion markers, historical spend on ancillaries, room type preferences, and length of stay. It also pulls in external context like local weather forecasts and event calendars. This enriched profile is the primary input for all subsequent offer logic, ensuring personalization is based on complete, operational data rather than generic segmentation.

A rules-based and ML-driven system that evaluates the enriched guest profile against inventory availability (e.g., spa slots, premium room categories, dinner reservations) and property business rules. It scores each potential offer (e.g., room upgrade, breakfast package, late checkout) on predicted acceptance probability and incremental revenue value. The engine applies margin thresholds and cannibalization checks to avoid discounting core revenue. Output is a ranked list of qualified offers with associated eligibility confidence scores.

This orchestration agent manages the end-to-offer lifecycle. It selects the optimal channel (pre-arrival email, check-in kiosk, in-room tablet, mobile app push) and timing based on guest journey stage and channel performance history. It generates personalized creative (text, imagery) using templates and a light LLM, then executes the delivery via integrated APIs (e.g., Braze, Twilio, Kiosk software). It listens for engagement or rejection events to update the guest profile and trigger follow-up or cessation logic.

A critical, fault-tolerant service that handles bidirectional synchronization between the orchestration layer and core hotel systems. When an offer is accepted, it automatically updates the Opera, Oracle Hospitality, or other PMS folio with the new charge and service item. For upgrades, it executes the room move and notifies housekeeping. For F&B or spa offers, it creates reservations in the POS or spa booking system. This agent ensures revenue is captured and operational teams are informed without manual data entry, which is a major source of leakage in manual processes.

This observability agent tracks the entire workflow's business and technical health. It monitors KPIs like offer acceptance rate, incremental revenue per guest, and channel conversion. Technically, it logs all agent decisions, data lineage, and API latencies for auditability. It enforces governance by flagging offers that approach discounting policy limits or show bias across guest segments. Alerts are routed to revenue managers or marketing ops for review, creating a closed-loop system for continuous optimization and compliance.

Not all decisions can be fully automated. This gateway manages escalations for high-value offers (e.g., suite upgrades for top-tier members), disputed charges, or when the scoring engine's confidence is below a defined threshold. It creates a structured task in a tool like ServiceNow or Jira for the relevant staff (front desk manager, revenue director), providing all context and recommended actions. The staff member's decision is fed back into the system, training the models and completing the transaction loop. This control is essential for managing brand risk and complex guest relationships.

The workflow ingests structured and unstructured data from the Property Management System (PMS) (booking history, room type, length of stay), Customer Relationship Management (CRM) (loyalty tier, past spend, preferences), and Customer Data Platform (CDP) (unified guest profile). Real-time context from event calendars, weather APIs, and IoT room sensors (e.g., minibar usage) provides the situational triggers for relevant offers.

A central orchestrator (e.g., LangGraph, Temporal) manages the multi-agent workflow. Specialized reasoning agents evaluate guest propensity for specific upsell categories (spa, dining, upgrade) using the fused data. A rules engine applies business guardrails (minimum margin, inventory limits, loyalty rules) to filter and rank opportunities before any offer is made, ensuring commercial viability and policy compliance.

Approved offers are executed through integrated channel systems. This includes triggering pre-arrival email sequences via marketing automation, displaying offers on digital check-in kiosks, pushing notifications through the hotel mobile app, and enabling in-stay conversational AI (digital concierge). Each channel requires specific API integrations with email service providers, kiosk software, mobile SDKs, and chat platforms to ensure a seamless guest experience.

When an offer is accepted, the workflow must trigger a real-time transaction. This requires deep integration with the PMS folio system to add charges accurately and the Point of Sale (POS) for F&B or spa bookings. The orchestrator confirms inventory deduction in the spa or restaurant reservation system and updates the guest profile in the CRM to log the successful upsell and refine future models.

A custom dashboard built on metrics pipelines tracks offer performance (impressions, acceptance rate, revenue lift) by segment, channel, and upsell type. Anomaly detection flags underperforming campaigns. An approval gateway allows managers to review or block automated offers for VIPs or during critical service periods. All offer decisions and guest interactions are logged to an audit trail for performance analysis and compliance.

A phased rollout is critical. Phase 1 integrates PMS/CRM and deploys a single-channel pilot (e.g., pre-arrival email) with simple rule-based offers. Phase 2 adds the reasoning agent, real-time context, and a second channel (e.g., mobile app). Phase 3 introduces full multi-channel orchestration and the automated transaction layer. Each phase includes exception handling design (e.g., failed API calls route to a staff queue) and model validation against historical data to prove ROI before scaling.