Dynamic Reward Calculation for Online Game Sponsorship
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Solution Overview
Problem
Existing online games lack effective methods to dynamically tailor rewards for player interaction with sponsored content, leading to suboptimal engagement and conversion rates, as current systems offer static rewards regardless of player attributes and behavior.
Innovation Solution
A system that identifies player attributes and calculates custom, dynamically variable rewards based on interaction probabilities, offering tailored incentives for sponsored content engagement, such as energy boosts or virtual currency, to enhance player interaction and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static rewards are offered to all players for sponsored content interaction, then the system is simple to implement, but player engagement and conversion rates are suboptimal
Solution Approach 1:
The reward system transitions from static to dynamic by adjusting reward values based on player attributes and interaction probabilities. The system calculates customized reward amounts for different player segments, making the reward structure adaptive rather than fixed, thereby improving conversion rates while maintaining manageable complexity through automated calculations.
Solution Approach 2:
The patent applies different reward values to different player segments based on their specific attributes and behaviors. Instead of a uniform reward structure, each player receives a customized reward amount tailored to their profile, creating local optimization for each player segment while maintaining overall system coherence.
2Adaptability or versatility
If customized rewards are calculated based on player attributes and interaction probabilities, then player engagement increases, but system complexity increases
Solution Approach 1:
The system changes the parameters of rewards based on player attributes and interaction probabilities. By dynamically adjusting reward values according to calculated probabilities and player characteristics, the system achieves high adaptability and personalization. The complexity is managed by automating the calculation process rather than requiring manual customization.
Solution Approach 2:
The system performs self-service by automatically calculating interaction probabilities and determining customized reward values without manual intervention. The automated calculation engine handles the complexity internally, allowing the system to provide personalized rewards while minimizing the operational burden on users.
3Measurement precision
If interaction probability calculations are performed for each player, then reward targeting precision improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating or quickly determining interaction probabilities using efficient algorithms. By streamlining the calculation process and potentially using pre-computed player profiles or segmented approaches, the system achieves accurate probability measurements without excessive processing delays, balancing precision with speed.
Data Source
AI summary
A system and method for managing a computer-implemented online game provides dynamically variable rewards to incentivize player interaction with sponsored content presented within the game. The particular reward offered to incentivize player interaction with particular sponsored content (e.g., a particular advertisement) can be dynamically variable based on the attributes of the player, thus providing user-specific custom rewards for interaction with sponsored content. Properties of incentive rewards that may be dynamically variable can include a custom type of in-game asset or resource, and/or a custom amount of a particular in-game asset or resource.