Personalized Advertisement Selection for Co-Viewers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing media streaming systems fail to provide personalized advertisement content to both primary and secondary users consuming media item content, often targeting only the primary user and neglecting the demographics and preferences of secondary users.
Innovation Solution
The system identifies primary and secondary users through methods like user login, facial recognition, biometric algorithms, and RFID, generating presence metadata to select appropriate advertisements based on demographic data, interaction history, and items observed, ensuring targeted advertising for all users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advertisement content is selected based only on primary user data, then the advertising system is simple and fast, but the advertisement relevance to secondary users deteriorates
Solution Approach 1:
The system segments users into primary users (account holders) and secondary users (co-viewers detected via facial recognition). Different identification and data collection methods are applied to each segment, allowing personalized advertising for both groups without compromising system efficiency.
Solution Approach 2:
The advertising system is enhanced to serve multiple functions: it continues to target primary users based on account data while simultaneously identifying and targeting secondary users through facial recognition and demographic analysis, making the system adaptable to all users present.
2Adaptability or versatility
If facial recognition and biometric algorithms are implemented to identify all users, then advertisement personalization for secondary users improves, but system complexity increases
Solution Approach 1:
The system performs preliminary user identification by detecting facial features and generating demographic data before advertisement selection occurs. This preliminary action enables personalized advertising for secondary users without adding complexity during the actual ad delivery phase.
Solution Approach 2:
The system introduces an intermediary processing layer that handles facial recognition and biometric analysis separately from the core advertising delivery mechanism. This intermediary component manages the complexity of user identification while keeping the advertising system itself relatively simple.
3Measurement precision
If the system collects and processes demographic data from all users, then advertisement targeting accuracy improves, but data processing time increases
Solution Approach 1:
The system applies partial action by collecting comprehensive demographic data for primary users (from account profiles) and sufficient demographic data for secondary users (from facial recognition), rather than exhaustive data collection for all users. This balances accuracy with processing efficiency.
Data Source
AI summary
Disclosed are various embodiments for selecting personalized advertisements to be transmitted to a user device during the streaming of advertisement-supported media item content. A primary user and a secondary user may be associated with the consumption of media item content being streaming to a user device. Based on the identification of both the primary user and secondary user, presence metadata may be generated. Using at least the presence metadata, advertisements that are appropriate for and target both the primary and any secondary users may be selected and transmitted to the client device.