Wish List Gamification for Consumer Preference Measurement
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Solution Overview
Problem
Conventional methods fail to accurately determine consumer interest in products added to wish lists or collections, as these lists often contain items of varying interest levels, making it difficult for merchants to assess genuine consumer preferences.
Innovation Solution
A system and method that engages consumers in games, such as sweepstakes or 'Instant Win' promotions, where they can win products chosen from their own wish lists or catalogs, allowing merchants to assess preferences by analyzing selection criteria and user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If consumers add products to wish lists or collections, then the quantity of products of interest is increased, but the precision of measuring consumer interest is reduced
Solution Approach 1:
The patent segments the consumer's product collection into multiple categories or groups, allowing consumers to organize products by interest level or intent. This segmentation enables more precise measurement of consumer interest by analyzing which segments contain which products, rather than treating the entire collection as a single undifferentiated group.
Solution Approach 2:
The system provides feedback to consumers about their wish list items through gamified interactions, such as showing them which items other consumers are interested in or what items might be available for purchase. This feedback loop helps refine the consumer's understanding of their own preferences and improves the accuracy of interest measurement over time.
2Adaptability or versatility
If consumers use collections as a parking place for various interest levels, then the versatility of the collection is improved, but the difficulty of detecting genuine preferences increases
Solution Approach 1:
The patent applies local quality by allowing different portions or aspects of the collection to have different meanings or weightings. For example, items at the top of a list or in specific categories can be weighted more heavily as indicators of genuine interest, while items in other areas may represent lesser interests. This enables the system to detect preferences by focusing on specific high-quality indicators within the versatile collection structure.
Solution Approach 2:
The system dynamically adjusts the interpretation and weighting of collection items based on consumer behavior patterns, interaction history, and temporal changes. Items that are frequently viewed, recently added, or consistently retained in the collection are dynamically weighted as stronger indicators of genuine preference, allowing the system to adapt to changing consumer interests while maintaining measurement accuracy.
Data Source
AI summary
A system and method for assessing personal preferences and interests of end-users by engaging one or more end-users in a game in which the end-user may be given a chance to win a product item from a collection of product items selected by the end-user.