Guest Behavior Prediction System for Personalized Hotel Services
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Solution Overview
Problem
Current hotel management systems lack the ability to provide personalized services to guests, as they primarily focus on data collection and manual staff allocation, failing to meet evolving guest expectations and resulting in a gap between guest needs and staff capabilities.
Innovation Solution
A system and method utilizing location devices and detection technology to predict guest behavior based on real-time location data and attribute information, generating personalized service suggestions for hotel staff to enhance guest experiences without manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If hotel management systems manually collect and manage guest data, then guest information is stored and processed, but the system lacks the ability to automatically predict guest behavior and provide personalized service suggestions
Solution Approach 1:
The system performs preliminary actions by collecting and storing guest attribute data during check-in and reservations before the guest actually needs services. This advance data preparation enables the analytic module to quickly predict guest behavior and generate service suggestions without manual intervention when the guest is in the facility.
Solution Approach 2:
The analytic module acts as an intermediary between the collected guest data and the service delivery system. It processes location data and attribute information to predict guest behavior, then communicates these predictions to staff devices, bridging the gap between raw data and actionable service suggestions.
2Ease of operation
If hotel staff manually review guest details and derive service recommendations, then personalized services can be provided, but this increases staff workload and time requirements
Solution Approach 1:
The system enables self-service by automatically generating service recommendations without requiring staff to manually review guest details. The analytic module autonomously processes location data and guest attributes to produce personalized service suggestions, which are then presented to staff for quick review and execution.
Solution Approach 2:
The patent replaces the mechanical process of manual data review and recommendation generation with an automated electronic system. The analytic module uses computer algorithms to process guest data and location information, substituting staff cognitive effort with automated computational analysis.
3Adaptability or versatility
If hotel staff allocate time to understand guest needs beyond basic duties, then personalized guest experiences improve, but staff turnover remains high due to increased workload
Solution Approach 1:
The system segments the complex task of understanding guest needs into automated components. The analytic module handles data analysis and behavior prediction, while staff devices receive organized service suggestions. This segmentation reduces the cognitive burden on staff while maintaining personalized service capability.
4Measurement precision
If traditional hotel management systems are used, then basic guest data is collected, but the system lacks real-time location tracking and automatic service suggestion generation
Solution Approach 1:
The system achieves multi-functionality by integrating location tracking, behavior prediction, and service suggestion generation into a unified platform. The same infrastructure that collects guest data during check-in also supports real-time location monitoring and automated recommendation generation, reducing overall system complexity despite enhanced capabilities.
Data Source
AI summary
The invention provides a system for generating guest-specific service suggestions for a guest within a facility such as a hospitality facility. The system comprises a location device carried or worn by the guest within the facility; one or more location detecting devices arranged at the facility, the location detecting devices being arranged to detect the location device carried or worn by the guest, and to communicate one or more location detection signals to a computer implemented analytic module; wherein the analytic module is configured to determine location data for the location device carried or worn by the guest and, based on said location data and/or data from a person attribute database, predict a behavior of the guest from at least said location data and communicate behavior information to one or more service devices.