Patron Flow Visualization Aggregating Wagering Game Data
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Solution Overview
Problem
Current methods fail to effectively aggregate and visualize patron flow data across wagering game establishments, limiting the ability to optimize floor layouts, enhance player experience, and increase revenue by understanding patron movements and social interactions.
Innovation Solution
A method that aggregates data from various sources, including wagering game machines and non-gaming activities, to generate patron flow data, which is then used to visualize and analyze patron movements, infer social groups, and tailor marketing offers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is aggregated from multiple wagering game machines and sources, then the completeness and accuracy of patron flow data is improved, but the complexity of data processing and system integration increases
Solution Approach 1:
The system divides data collection into separate modules: wagering game machine data collection, non-wagering game data collection, and patron flow data generation. Each module handles specific data sources independently, reducing overall system complexity while maintaining data completeness.
Solution Approach 2:
The system introduces an intermediary processing layer that aggregates data from multiple sources (wagering game machines, non-wagering games, RFID, wireless access points) and transforms it into standardized patron flow data. This intermediary layer manages the complexity of integrating diverse data sources.
2Loss of information
If multiple data sources including non-wagering game data are integrated, then the insight into patron behavior is improved, but the difficulty of data chaining and synchronization increases
Solution Approach 1:
The system performs preliminary data preparation by collecting and storing data from all sources (wagering game machines, non-wagering games, RFID tags, wireless access points) before patron flow analysis. This preliminary collection ensures all relevant information is available and properly formatted for subsequent analysis.
Solution Approach 2:
The system uses feedback mechanisms to synchronize data from multiple sources by comparing timestamps and patron identifiers across different data streams. This feedback loop ensures data consistency and proper temporal alignment between wagering game data, non-wagering game data, and patron flow data.
3Productivity
If patron flow data is visualized and analyzed in real-time, then the ability to optimize floor layouts and marketing strategies is improved, but the processing power and computational resources required increase
Solution Approach 1:
The system applies partial processing by focusing computational resources on generating patron flow data and key visualizations rather than processing every possible metric in real-time. This selective approach provides sufficient operational insights while managing computational resource consumption.
Data Source
AI summary
A patron flow system aggregates wagering game data from a plurality of wagering game machines in a wagering game establishment. The wagering game data indicates a plurality of patrons and times. Patron flow data is generated from the aggregated wagering game data. The patron flow data indicate flows of the plurality of patrons among the plurality of wagering game machines in the wagering game establishment with respect to the times.