Anonymous Auction System for Recipe Ranking and Consumer Targeting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Producers face challenges in influencing the consumption of consumables after sale, as existing marketing methods lack effectiveness in encouraging consumer behavior and promoting the use of purchased products.
Innovation Solution
A computerized auction system that allows multiple producers to bid on individual components of a multi-component ensemble, with bids being combined anonymously to affect the ranking of ensembles in consumer search results, promoting the consumption of specific products by prioritizing recipes that include those components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If producers use traditional advertisement methods to promote products, then they can reach consumers, but they cannot effectively influence the subsequent use or consumption of the sold products
Solution Approach 1:
The system implements feedback by allowing consumers to indicate whether they made or consumed the product after receiving targeted recipe recommendations. This feedback mechanism enables producers to measure the actual impact of their marketing campaigns on consumer behavior, resolving the contradiction between reaching consumers and influencing their subsequent usage.
Solution Approach 2:
The patent replaces traditional mechanical advertisement systems with a computerized auction-based recommendation system. Instead of direct advertising, the system uses an automated auction mechanism to allocate marketing budgets efficiently, substituting the mechanical ad placement process with a more sophisticated algorithmic approach that optimizes based on consumer data and product performance.
2Reliability
If the auction system combines bids from multiple marketers anonymously, then it promotes fair competition and prevents bid rigging, but it reduces transparency about individual marketer performance
Solution Approach 1:
The system introduces an intermediary mechanism - the auction facilitator - that manages the bidding process anonymously. This intermediary combines bids from multiple marketers while maintaining fairness and preventing rigging, yet preserves the ability to attribute results to individual marketers through the underlying data structures, thus balancing integrity with necessary transparency.
3Measurement precision
If the system targets consumers based on their existing product inventory, then marketing precision increases, but the complexity of tracking and managing consumer data increases
Solution Approach 1:
The system segments consumer data into distinct categories - identifying which products consumers already possess versus which they do not. This segmentation enables precise targeting of consumers likely to benefit from specific product recommendations, while managing data complexity through structured classification rather than attempting to track every consumer interaction in detail.
Data Source
AI summary
A computerized auction system is used for collecting bids from a plurality of producers. The bids are placed on individual components of a multi-component ensemble. Bids from separate marketers are added and affect the rank of a single ensemble within a potential consumer's ensemble search result. The bids are cooperative as the separate bids on the components are added to form the single bid on the ensemble. The bids are anonymous such that each bidding marketer is kept unaware of whether another marketer's bid was combined with the bidding marketer's bid.