Shared Content Distribution Adjusting Bids by Visitor Engagement Probability
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Solution Overview
Problem
Current shared content distribution systems based on auctions only consider revenue from a single viewing and do not account for the ability of content to maintain visitor interest, leading to suboptimal long-term revenue generation.
Innovation Solution
A system that adjusts bids based on the probability of a visitor remaining engaged with the content source, using a shared content request unit, bid retrieval unit, probability retrieval unit, bid adjustment unit, and shared content selection unit to select content that maximizes long-term revenue by incorporating click-through rates and visitor attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the content source selects shared content based on the highest bid during the auction process, then immediate revenue from a single viewing is maximized, but long-term revenue generation is reduced due to visitor abandonment
Solution Approach 1:
The system performs preliminary actions by adjusting bids based on predicted visitor engagement and abandonment probabilities before content selection. This allows the content source to proactively account for long-term visitor retention rather than simply reacting to immediate bid amounts, thereby preventing visitor abandonment before it occurs.
Solution Approach 2:
The system introduces feedback mechanisms by incorporating visitor engagement metrics and abandonment probabilities into the bid adjustment process. This feedback loop allows the auction system to continuously learn from visitor behavior patterns and optimize content selection to maximize both immediate and long-term revenue.
2Ease of operation
If the auction process only considers bid amount for shared content selection, then the bidding process remains simple and transparent, but the system fails to account for visitor engagement quality and long-term value
Solution Approach 1:
The system introduces an intermediary mechanism (bid adjustment unit) that translates complex visitor engagement metrics into adjusted bid values. This intermediary layer handles the complexity of engagement quality assessment while maintaining the simplicity of the core auction process, as bidders still submit straightforward bids but the system automatically adjusts them based on engagement quality.
Solution Approach 2:
The system changes the parameter used for content selection from raw bid amount to adjusted bid amount that incorporates engagement quality metrics. This parameter transformation allows the system to consider visitor engagement quality without fundamentally changing the auction mechanism, as the adjustment is performed automatically based on calculated engagement probabilities.
Data Source
AI summary
A system and method for distributing shared content based on a probability is provided. The system includes a shared content request unit to receive a shared content request; a bid retrieval unit to retrieve a plurality of shared content items based on the share content request, and to retrieve a plurality of bids corresponding to the plurality of shared content items, respectively; a probability retrieval unit to retrieve a plurality of likelihood values for each of the plurality of bids, respectively; a bid adjustment unit to adjust the plurality of bids based on the corresponding plurality of likelihood values; and a shared content selection unit to select shared content based on the adjusted plurality of bids.