We are deploying the first iteration of AI Insights to approximately 20 hotels.
This soft launch delivers the initial layer of AI Insights to Property Champions.

Included Functionality

The soft launch encompasses three core insight categories:

Strategic Training Recommendations

• Pairing mechanics: Top performers in specific product categories are identified and recommended as training partners for developing agents
• Focus areas: Service-based sales methodology and mastery of the wheel mechanics

Agent-Level Performance Analysis

• Identification of top performers by specific performance vectors
• Flagging of agents requiring support with granular focus on performance gaps and opportunity areas
• Diagnostic output based on current data patterns within the ING ecosystem

Executive Revenue Opportunity Mapping

• Quantification of potential revenue impact if identified training improvements are implemented
• Based on performance delta analysis between current state and observed top-performer benchmarks within the dataset

Delivery Cadence and Data Processing

• Insights delivery: Once per week
• Data scope: AI Insights processes exclusively against data ingested and available within the IN-Gauge framework

Model Development and Accuracy

This soft launch establishes the foundation for AI Insights. Model precision will strengthen as we:

• Ingest additional data across more properties and time periods
• Refine feature engineering based on observed performance correlations
• Tune model parameters against validated outcomes

The recommendations generated are actionable and data driven. As we expand the training dataset and feedback, the model's pattern recognition and recommendation specificity will become increasingly refined.

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Collaborative Approach - Augmenting Expertise, Not Replacing It

AI Insights is designed to augment existing expertise and institutional knowledge,
The system:

• Surfaces data patterns at scale that would be time-prohibitive to identify manually
• Provides a data-backed foundation for strategic conversations between Champions, and CSCs.
• Enables faster identification of training opportunities and revenue optimization paths

The AI identifies the what—Champions and CSCs expertise determines the how and when.

Testing Timeline and Expansion

• Weeks 1-2: Active testing across the 20-property cohort to refine model veracity and output fidelity
• Objective: Ingest and process performance datato optimize recommendation algorithms before broader deployment
• Expansion criteria: Demonstrated consistency in recommendation accuracy and actionable insight generation

Upon successful completion, we will expand to the full customer base.