AI Workflow for Intelligent Booking Splitting (for large groups across properties)

Manual group RFP analysis and property allocation is a sequential, multi-departmental process prone to delays. A custom AI agent workflow ingests the RFP, evaluates real-time availability and rate constraints across the property cluster, and generates a pre-negotiated split proposal in minutes. This compresses the sales cycle, improves win rates against competitors, and allows sales managers to focus on high-touch relationship building instead of administrative coordination.

Splitting groups manually often leads to suboptimal allocations based on gut feel or individual property pressure. An AI-driven workflow uses displacement cost modeling, forecasted demand, and ancillary revenue potential to allocate room blocks in a way that maximizes total portfolio RevPAR. It prevents cannibalization of high-value transient business at one property by strategically utilizing capacity at another, protecting overall yield.

Coordinating a split booking requires copying data between Sales & Catering (S&C) systems, Property Management Systems (PMS), and CRS entries for each property—a major source of errors. The automated workflow acts as an orchestration layer, creating synchronized bookings and rooming lists directly in each target system via APIs. This eliminates duplicate entry, ensures rate integrity, and provides a single source of truth for the group coordinator.

The complexity of multi-property coordination inherently limits the volume of group business a cluster can handle. Automating the splitting and proposal generation process acts as a force multiplier for the sales team. A single manager can oversee and refine the output of AI agents handling multiple RFPs simultaneously, effectively increasing the sales team's throughput and allowing the business to pursue more group opportunities without proportional headcount growth.

A fragmented, last-minute group allocation disrupts housekeeping, F&B, and staffing forecasts at individual properties. By automating and finalizing splits earlier in the cycle, the workflow provides each property with accurate, advanced notice of incoming group blocks. This allows for precise labor scheduling, inventory ordering, and service preparation, reducing operational waste and improving guest experience consistency across the cluster.

Manual splitting decisions lack transparency, making it difficult to audit why a group was allocated a certain way. A custom workflow logs every decision factor—from displacement cost calculations and property capacity to the final revenue optimization logic. This creates a defensible audit trail for commercial reviews, simplifies training for new sales staff, and ensures brand standards and rate parity rules are consistently applied.

The workflow begins with an orchestration agent ingesting the RFP from a CRM (e.g., Salesforce) or sales platform. It immediately queries the Central Reservation System (CRS) and individual Property Management Systems (PMS) for real-time availability across the defined cluster. This agent uses constraint programming to model room types, dates, and operational capacities, creating a unified, real-time inventory view that is impossible to maintain manually.

A dedicated allocation agent evaluates multiple split scenarios. It runs displacement analysis to weigh the group's value against potential lost transient revenue at each property. The logic incorporates revenue management system (RMS) forecasts, minimum rate thresholds, and strategic goals (e.g., filling a shoulder-night pattern). This is where the core optimization happens, turning a manual spreadsheet exercise into a simulated, data-driven decision.

Once the optimal split is determined, a document agent assembles the proposal. It pulls approved rate templates, property-specific amenity details, and maps the room block allocation. Using a framework like LangChain, it generates a cohesive, branded document that clearly delineates the split across properties, including summarized terms and a master cover letter. The output is formatted for the Sales & Catering system and CRM.

Before release, proposals are routed based on predefined rules. Splits exceeding a revenue threshold or involving a sold-out property may require Director of Sales or Cluster GM approval. An approval agent manages this workflow via email or Slack integration, escalating if no response is received. All exceptions (e.g., a property rejecting its allocation) are logged and fed back to the allocation agent for re-calculation, creating a closed-loop system.

Upon client acceptance, the fulfillment agent executes the split. It connects via API to each relevant PMS (e.g., Opera, Protel) and the CRS to create the group blocks, load negotiated rates, and attach the master booking ID for tracking. This eliminates the error-prone, multi-system data entry performed by sales coordinators, ensuring the digital inventory is accurately reserved immediately.

A monitoring agent tracks the entire workflow's performance—from RFP receipt to booking creation—providing dashboards for sales leadership. Key metrics include response time, win rate by split type, and revenue per available room (RevPAR) impact. Crucially, the outcomes (won/lost) and final negotiated terms are fed back into the system, allowing the allocation logic to continuously learn and improve future split recommendations.