Cross-Platform Ad Selection via TV Interaction Data
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Solution Overview
Problem
Traditional advertising models for television and online content do not effectively leverage knowledge gained from one medium to enhance the experience or revenue opportunities in another, leading to separate and less effective advertising strategies across different platforms.
Innovation Solution
By monitoring interaction data from television content, such as viewing habits and advertisement engagement, to select and display relevant online advertisements that match the content and advertisers, providing a consistent experience across platforms and increasing revenue opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional separate advertising models are used for television and online content, then each model can operate independently with its own strategies, but knowledge gained from one medium cannot be leveraged to enhance the other, resulting in less effective advertising strategies
Solution Approach 1:
The patent combines television advertising data and online advertising data into a unified advertising selection system. Interaction data from both television content and online content is merged and stored together, allowing the system to leverage knowledge from one medium to enhance advertising effectiveness in another medium, thereby resolving the contradiction between separate model independence and cross-medium knowledge utilization
2Productivity
If advertising models are provided separately for television and online content, then implementation and management are simpler for each individual model, but revenue opportunities are limited due to inability to leverage cross-platform interaction data
Solution Approach 1:
The patent creates a universal advertising selection system that handles both television and online advertising through a single platform. The system stores interaction data from multiple sources (television and online) and uses unified selection logic to generate advertisements for different content types, thereby increasing revenue opportunities while managing complexity through consolidation rather than proliferation of separate systems
3Measurement precision
If interaction data from television content is monitored and stored, then more information is available for selecting relevant online advertisements, but the complexity of data collection and storage increases
Solution Approach 1:
The patent introduces an intermediary component (the advertising selection system with integrated data storage) that receives and processes interaction data from television content. This intermediary consolidates data from multiple sources into a unified storage structure, making precise advertisement selection possible while managing the complexity of data collection and storage through a centralized intermediary layer rather than distributed complex systems
Data Source
AI summary
Online advertisement selection techniques are described. In an implementation, data is obtained which describes interaction of one or more clients with advertisements embedded in television content. An advertisement is selected to be displayed in conjunction with web content accessed by the one or more clients based on the interaction with the advertisements described in the data.