Virtual Shop Interface Offer Placement Optimization
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Solution Overview
Problem
Players in online games often find it difficult to locate specific virtual items in shop menus, leading to frustration and potential abandonment of the search, as existing systems lack effective methods to optimize item placement based on user behavior and context.
Innovation Solution
A system that determines optimal locations for offers in a shop interface by analyzing user purchases in a test bed environment, using a combination of processors and modules to adjust display priority based on user context and purchase history, ensuring relevant items are prominently displayed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If players manually browse through all items in the shop menu, then they can find the exact item they are looking for, but it becomes difficult and time-consuming especially when there are many items
Solution Approach 1:
The system performs preliminary actions by analyzing user behavior data, purchase history, and contextual information before the user even searches for an item. It pre-calculates and prepares personalized item placements and search optimizations based on predicted user needs, so when the user opens the shop menu, the most relevant items are already positioned for quick access
Solution Approach 2:
The patent replaces the manual mechanical browsing process with an automated intelligent system. Instead of users physically scrolling through lists and manually searching for items, the system uses algorithms to automatically analyze user context, predict item locations, and dynamically optimize the shop menu structure, substituting human effort with automated computational processes
2Adaptability or versatility
If the shop menu displays all available virtual items, then users can find any item they want, but it becomes overwhelming and difficult to locate specific items among many
Solution Approach 1:
The system applies local quality by making different parts of the shop menu have different properties based on user context. Instead of a uniform display structure, the menu dynamically adjusts which items are highlighted, grouped, or positioned in prominent locations based on the user's current game state, purchase history, and behavioral patterns, so each section of the menu is optimized for its specific purpose
Solution Approach 2:
The shop menu transitions from a static display structure to a dynamic one that automatically reconfigures based on real-time user context. The system continuously monitors user behavior and adjusts item placement, grouping, and visibility in response to changing user needs, making the menu adaptive rather than fixed
3Ease of manufacture
If the shop interface uses a fixed display structure, then it is simple to implement, but it cannot adapt to different user contexts and behaviors
Solution Approach 1:
The system performs preliminary analysis of user behavior data, purchase history, and contextual information to pre-determine optimal display configurations. By analyzing patterns in advance and preparing personalized menu structures before users interact with the shop, the system can implement complex adaptive behavior without requiring real-time computational complexity during user interaction
Data Source
AI summary
One aspect of the disclosure relates to determining locations for offers in a shop interface for an online game. The locations may be determined based on observance of purchases made by users in a test bed environment. The test bed environment may grant free virtual currencies to players that can be spent in the isolated and controlled test environment. The spending of these virtual currencies by users on offers of virtual items for use in the test bed environment may then be used to automatically adjust the shop menu/interface in a live environment for the online game, where the virtual currency spent has been purchased for real money consideration.