Gaming System Wagering Threshold Personalization
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Solution Overview
Problem
Current gaming systems lack effective methods to provide personalized benefits to players based on their wagering history, leading to a need for dynamic and player-specific bonus triggers.
Innovation Solution
A method and system that determine a wagering threshold based on past gaming sessions, triggering events such as bonuses or awards when this threshold is reached, using data from individual or group player sessions and accounting for return to player (RTP) rates, to offer tailored benefits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed wagering thresholds are used for all players, then system simplicity is maintained, but player engagement and personalization are reduced
Solution Approach 1:
The system pre-calculates wagering thresholds based on historical player data before gaming sessions begin. Player profiles are pre-populated with personalized thresholds that are automatically applied during gameplay, eliminating the need for real-time complex calculations while maintaining high personalization levels
Solution Approach 2:
The system creates simplified copies of player profiles containing only the essential personalized parameters (wagering thresholds, bonus preferences) that are distributed to gaming terminals. This allows complex personalization logic to be stored centrally while simple copies are used at each terminal, reducing overall system complexity
2Measurement precision
If wagering thresholds are based on extensive historical data, then accuracy of player segmentation improves, but data processing time increases
Solution Approach 1:
Player segmentation and threshold calculation are performed in advance using extensive historical wagering data. The system analyzes past gaming patterns, bonus responses, and wagering behavior to create accurate player profiles before sessions begin, avoiding time-consuming processing during active gameplay
Solution Approach 2:
The system uses dynamic threshold adjustment where wagering thresholds are continuously refined based on recent player behavior while maintaining the structure of historical analysis. This allows the system to adapt to changing player preferences without re-processing entire historical datasets in real-time
3Productivity
If bonus events are triggered frequently, then player engagement increases, but gaming venue operating costs increase
Solution Approach 1:
The system applies different bonus trigger frequencies and types to different player segments based on their individual profiles. High-value players receive more frequent and generous bonuses, while casual players receive less frequent, smaller incentives. This localized approach optimizes engagement ROI by matching bonus expenditure to player value and behavior patterns
Solution Approach 2:
The system dynamically adjusts bonus parameters (threshold amounts, bonus sizes, trigger frequencies) based on player response data and venue budget constraints. When player engagement metrics indicate diminishing returns, the system automatically modifies bonus parameters to maintain engagement at lower cost levels
Data Source
AI summary
A method of gaming comprising: determining a wagering threshold to apply to play of at least one gaming device during a current gaming session based on an amount wagered in at least one prior gaming session; and triggering an event upon reaching the wagering threshold in the current gaming session.