Content Feed Insertion System for Fair Revenue Distribution
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Solution Overview
Problem
Existing methods for monetizing internet content through advertising in feeds or streams often unfairly distribute revenue among content creators, particularly favoring popular content, and can annoy users with frequent or intrusive ads, leading to reduced viewer engagement.
Innovation Solution
A system that monitors user interaction with content and inserts additional content, such as advertising, at specific positions based on user engagement, associating it with the original content for revenue sharing, and adjusting insertion frequency and timing to minimize user annoyance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If advertising is displayed via pre-roll or post-roll videos before or after content, then advertising revenue can be generated, but automatic playback of advertising may annoy users and cause them to lose interest quickly
Solution Approach 1:
The system performs preliminary actions by selecting and preparing relevant additional content based on user interaction with the first content item before the user actually encounters it. This allows the content to be customized and relevant, reducing user annoyance while maintaining revenue generation opportunities.
Solution Approach 2:
The system uses feedback from user interactions (selections, views, scrolling behavior) with the first content item to dynamically determine what additional content to insert and where to place it. This feedback mechanism ensures that inserted content is relevant to user interests, reducing annoyance while maintaining engagement.
2Quantity of substance
If advertising is inserted into the content via interstitial advertising played while pausing the content, then advertising revenue can be generated, but interrupting content may annoy viewers particularly for short content
Solution Approach 1:
The system prepares and selects additional content in advance based on user interaction with the first content item, so that when the user encounters it, the content is already relevant and tailored to their interests. This reduces the disruptive effect of interruptions.
Solution Approach 2:
The system uses feedback from user interactions to dynamically select additional content that is relevant to the user's interests. This ensures that even when content is interrupted, the inserted material is valuable to the user, reducing annoyance and maintaining engagement.
3Quantity of substance
If advertising is displayed as banners adjacent to content or in pop-up windows, then advertising revenue can be generated, but for long feeds this reduces any individual's share significantly and may drive popular content creators away
Solution Approach 1:
The system segments the feed into discrete content items and inserts additional content at specific positions relative to each item based on user interactions. This allows revenue to be associated with specific content items and their creators, enabling fairer revenue distribution while maintaining overall ad revenue generation.
Solution Approach 2:
The system uses feedback from user interactions with specific content items to determine where to insert additional content and how to associate revenue with creators. This ensures that popular content creators receive appropriate revenue shares based on actual user engagement, making the system fairer and more adaptable.
4Quantity of substance
If additional content is inserted frequently into the stream to maximize revenue, then advertising revenue increases, but user engagement decreases due to excessive interruptions
Solution Approach 1:
The system applies partial action by selectively inserting additional content only at positions where user interactions indicate interest. Rather than inserting content uniformly throughout the feed, it uses feedback to determine optimal insertion points, balancing revenue generation with user engagement.
Solution Approach 2:
The system uses feedback from user interactions (selections, views, scrolling) to dynamically adjust the frequency and placement of additional content. This feedback mechanism ensures that content is inserted at rates that maintain user engagement while still generating revenue, preventing excessive interruptions.
Data Source
AI summary
A user's interaction with a list of content may be monitored and a second item of content may be inserted into the list at a position based on the user's interaction. The additional content may be associated with a first item of content in the list based on the interaction. A direction of scrolling of the list may be monitored, and the second item of content may be inserted into the list in a position subsequent to the first item of content in the direction of scrolling, such that the viewer encounters the second item of content after the associated first item of content. Because the second item of content may be selected to be desirable to viewers of the first item of content, presenting the second item of content subsequent to the first item of content may increase the likelihood of ingestion of the second item of content.