Dynamic Ad Selection in Game Environments
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for targeting advertisements in computer game environments lack effectiveness in selecting and displaying ads based on user behavior, affinity, and characteristics, leading to limited personalization and flexibility.
Innovation Solution
An apparatus and method that monitor user activity in computer game environments to select advertisements based on personality traits, user interactions, and affinity for specific products or genres, utilizing a user monitoring component, analysis engine, and advertisement selection engine to dynamically choose ads tailored to individual users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If advertisements are hard coded into the game, then advertisement placement is simple and stable, but advertisements cannot be changed or targeted to specific users once the game is released
Solution Approach 1:
The advertisement system transitions from static hard-coded placement to dynamic selection based on user behavior. The system continuously monitors user actions and dynamically selects advertisements from a pool, allowing ads to change based on user profile and context without requiring game code modifications.
Solution Approach 2:
User profiles and behavior patterns are established in advance through continuous monitoring and analysis. This preliminary characterization of users enables the system to make informed advertisement selections before actual ad delivery, resolving the contradiction by preparing targeting data beforehand rather than requiring complex real-time decision-making.
2Adaptability or versatility
If dynamic advertisement placement is implemented, then advertisement flexibility and targeting capability are improved, but system complexity increases
Solution Approach 1:
The system divides advertisement delivery into distinct functional components: user behavior monitoring, profile analysis, and advertisement selection. This segmentation allows each component to be optimized independently, managing complexity by breaking down the overall system into manageable modules with specific responsibilities.
Solution Approach 2:
A user profile acts as an intermediary between raw behavior data and advertisement selection. The profile synthesizes monitored user actions into meaningful characteristics, simplifying the selection process by providing a pre-processed representation of user preferences rather than requiring direct analysis of raw behavior data for each ad decision.
3Measurement precision
If user behavior is monitored to determine personality traits, then advertisement targeting precision is improved, but user privacy concerns and system complexity increase
Solution Approach 1:
Instead of directly analyzing raw user behavior data for each advertisement decision, the system creates simplified copies in the form of user profiles containing personality traits and preferences. These profiles serve as representative models that capture essential user characteristics without requiring continuous access to detailed behavior data, reducing monitoring complexity while maintaining targeting precision.
Data Source
AI summary
Advertisements may be selected for display to a user in a computer game environment based at least in part on one or more of a personality trait of the user as determined from monitoring a behavior of the user as the user is participating in the computer game environment, a user affinity for a subject of another advertisement as determined from monitoring activity of the user after the user views the other advertisement while the other advertisement is displayed in the computer game environment, and a characteristic of the user as determined from a username selected by the user.