Dynamic Ad Substitution for Contextual Media Recommendations
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Solution Overview
Problem
Users face difficulty in finding media programs of interest among a broad array of options, and existing recommendation services are underutilized, as they often require user initiative and lack contextually relevant suggestions.
Innovation Solution
A system and method that dynamically assesses ad impression contractual obligations in real-time to substitute media program recommendations for reduced or zero-revenue advertisements, using short video trailers to generate interest, typically presented during the last advertising pod of media programs, thereby maximizing advertising revenue and increasing viewership.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a broad array of media programs is made available to users, then the variety and selection of media programs increase, but it becomes difficult for users to find programs of interest
Solution Approach 1:
The system automatically generates and presents media program recommendations to users without requiring them to actively search or categorize programs. The recommendation engine self-services by analyzing viewing history and automatically selecting relevant programs to present to the user during ad breaks.
2Ease of operation
If recommendation services are provided that require user initiative, then users can search for programs of interest, but such services are underutilized
Solution Approach 1:
The system performs preliminary actions by pre-analyzing user viewing history and pre-generating personalized recommendations before users need them. Recommendations are prepared in advance and automatically presented at optimal moments (during ad breaks), eliminating the need for users to initiate searches.
Solution Approach 2:
The system incorporates feedback loops where user responses to recommendations (clicks, views, skips) are continuously analyzed to refine and personalize future recommendations. This feedback mechanism increases utilization by making recommendations progressively more relevant to individual user preferences.
3Productivity
If media program recommendations are substituted for paid advertisements, then viewership increases, but advertising revenue decreases
Solution Approach 1:
The system dynamically balances recommendation delivery with revenue optimization by adjusting the mix of paid ads and recommendation substitutions in real-time. During high-value ad breaks, paid advertisements are prioritized, while during lower-value breaks, recommendations are substituted to drive viewership without significant revenue loss.
Solution Approach 2:
The system changes parameters such as the timing, frequency, and targeting of recommendation substitutions based on user profile, time of day, and program context. This allows optimization of both viewership impact and revenue preservation by adapting the substitution strategy to specific conditions.
Data Source
AI summary
A processing workflow method, system, and computer program product provide the ability; to recommend alternative programming during playback of a source media program. A media program player plays the source media program to a first viewer and provides information regarding the first viewer to a recommendation engine. The recommendation engine calculates and sends the media player a list of recommended media program candidates (including identifications of the candidates) based on the information. Prior to reaching an advertising break in the source media program, the media player transmits a request (including the identifications) for an advertisement to an advertising server and in response, receives an advertisement that is played to the first viewer during the advertising break.