Turning guest feedback into predictable revenue and operational perfection.
Today, a single negative review about a poor experience can impact bookings for months. But with countless variables at play, identifying the true root operational cause is like finding a needle in a haystack.
The AI learns that business travelers who check in late are highly sensitive to Wi-Fi speed, while families are sensitive to pool cleanliness. It creates proactive task lists for staff based on the guest profile of incoming reservations to prevent negative reviews before they happen.
During a major conference, the model suggests a 15% ADR increase but also recommends offering a "business traveler" package with complimentary breakfast and pressing service. During a holiday weekend, it simulates the impact of a "third night free" offer to maximize occupancy.
When a VIP guest complains about noise, the model simulates two responses. Option A: A room change (high cost, high satisfaction). Option B: Offering a complimentary dinner and loyalty points (medium cost, medium satisfaction). This allows managers to make data-driven recovery decisions.