Audience Identification Profiles for Content Delivery
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Solution Overview
Problem
Current content selection processes lack the ability to identify and target individual members of a viewing audience, leading to ineffective or wasted advertising and content placements, as they rely on circumstantial data and do not account for the actual type or size of the audience.
Innovation Solution
A computer-implemented system and method for identifying individuals in a group and determining a group response metric for content, such as video media files, by generating identification profiles for each member, calculating individual and group scores based on these profiles, and ranking media files for optimal content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional content selection processes are used based on circumstantial data, then device complexity is reduced, but measurement precision of audience characteristics deteriorates
Solution Approach 1:
The system segments the audience into distinct groups based on multiple characteristics (demographics, viewing habits, device information) and creates separate identification profiles for each segment, enabling precise measurement of audience characteristics while managing complexity through modular profile structures
Solution Approach 2:
The system introduces an intermediary identification profile that bridges raw circumstantial data and meaningful audience characteristics. This profile acts as a mediator that structures and interprets data from multiple sources (device info, viewing behavior, demographics) to achieve accurate audience measurement without directly complex processing
2Reliability
If content targeting is performed without individual member identification, then processing time is reduced, but advertising effectiveness deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-generating identification profiles for audience members and pre-scoring multiple media files against these profiles before actual content delivery. This advance preparation ensures advertising effectiveness is maintained while reducing real-time processing time when content needs to be delivered
Solution Approach 2:
The system implements dynamic content scoring that adapts to different audience segments and individual members. By dynamically calculating scores based on identified characteristics and allowing for real-time updates as new data becomes available, the system maintains high advertising effectiveness while optimizing processing efficiency through adaptive rather than static evaluation
3Adaptability or versatility
If all audience members are individually identified and scored, then content relevance is improved, but computational load increases
Solution Approach 1:
The system applies partial action by identifying and scoring only the most relevant characteristics and media files for each audience segment rather than exhaustively analyzing all possible attributes and content. This selective approach maintains content personalization and adaptability while significantly reducing the computational energy required for processing
Solution Approach 2:
The system applies different levels of identification and scoring depth to different audience segments based on their specific characteristics and the context of content delivery. Rather than uniformly processing all members with the same intensity, it tailors the level of analysis to local needs, achieving personalized content delivery while optimizing computational resource allocation
Data Source
AI summary
Systems, methods, and computer-readable media are provided for group identification and content delivery. In accordance with one implementation, a computer-implemented method is provided that includes operations performed by at least one processor. The operations of the method include generating, based on identification data, an identification profile for each member of a set of members, the set of members being associated with a viewing group. The set of members may comprise all of the members of the viewing group or any subset of the members of the viewing group. The operations also include determining an individual score for each member of the set of members for each media file of a plurality of available media files based on the corresponding identification profile. Additionally, the operations include determining a group score for each of the plurality of available media files based on the corresponding individual score of each member.