Ad Playback Interest Detection From Rewind and Pause Signals
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Solution Overview
Problem
Existing systems struggle to accurately assess viewer interest in advertisements during media content playback, making it difficult to deliver targeted or customized content based on user interactions.
Innovation Solution
The system correlates playback mode changes, such as rewinding or pausing during advertisements, with user interest levels, allowing for the selection and delivery of relevant content or items based on these interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional advertisement delivery systems are used, then advertisements can be broadcast to viewers, but the system cannot accurately assess viewer interest or deliver targeted content
Solution Approach 1:
The system performs preliminary actions by tracking and recording user interactions (rewind, pause, fast-forward) during advertisement playback before making any assessment decisions. This preliminary data collection enables subsequent accurate measurement of viewer interest levels based on specific interaction patterns with advertisements.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring user interactions with advertisements and using this information to adjust and improve viewer interest assessment. The feedback loop allows the system to learn from interaction patterns and refine its measurement accuracy over time.
2Productivity
If generic advertisements are delivered to all users, then advertisement delivery is simple, but user engagement and response probability are low
Solution Approach 1:
The system applies local quality by delivering customized advertisements and content based on individual user interaction patterns rather than uniform generic content. Each user receives content tailored to their specific interests and behaviors, with advertisement selection and follow-up content customized according to their demonstrated engagement levels with particular ad types.
Solution Approach 2:
The system utilizes parameter changes by varying content delivery parameters based on detected interaction patterns. When users exhibit high interest (rewind, pause), the system changes parameters to deliver more targeted follow-up content and advertisements, whereas low interest triggers different content selection parameters, thereby dynamically adapting to user preferences.
3Reliability
If user interaction tracking is implemented, then viewer interest can be assessed, but system complexity increases
Solution Approach 1:
The system extracts only the most relevant interaction data needed for reliable advertisement effectiveness measurement, such as rewind, pause, and fast-forward actions during ad playback. By extracting and focusing on specific key interactions rather than tracking all possible user behaviors, the system achieves reliable measurement while minimizing unnecessary complexity.
Data Source
AI summary
A method for assessing viewer interest in content and advertisements may include receiving an indication regarding a content playback mode change (e.g., a change from a skip or fast-forward mode to a pause or rewind mode) occurring during playing of a media content segment such as a television program or movie. The method then proceeds to associate the playback mode change with a sub-segment of the television program, such as an advertisement or commercial, and a level of interest of a user in the advertisement or commercial is determined based on the associated content playback mode change. An item, such as an advertisement or promotional offer can be selected to be presented to the user based on the determined level of interest of the user in the advertisement or commercial. Systems for assessing viewer interest in content and advertisements include devices and components configured to perform or enable such methods.