Ad Schedule Generation via Automatic Content Recognition
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Solution Overview
Problem
Current ad schedule generation techniques are inefficient and prone to errors, requiring weeks to process data and struggling with accuracy due to changes in television schedules, human errors, and difficulties in capturing targeted and hyper-local advertisements.
Innovation Solution
A system utilizing automatic content recognition (ACR) and a large, behaviorally tracked television panel to determine when advertisements were output across multiple client devices, identifying peak viewing times to generate an ad schedule quickly and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional ad schedule generation techniques are used, then data processing can be performed, but the process takes weeks and is prone to errors
Solution Approach 1:
The patent replaces traditional mechanical data processing methods with automatic content recognition (ACR) technology. ACR uses automated systems to detect and identify advertisement content in video streams, eliminating manual processing and significantly reducing the time required to generate ad schedules from weeks to much shorter periods while improving accuracy.
2Measurement precision
If traditional methods are used to capture advertisements, then data can be collected, but accuracy is reduced due to schedule changes and human errors
Solution Approach 1:
The patent replaces human-operated data collection methods with automatic content recognition systems. ACR continuously monitors video streams and automatically identifies advertisement content, eliminating human errors and the inability to keep up with schedule changes. This automated approach provides more reliable and precise data on when advertisements are actually aired.
Solution Approach 2:
The system uses ACR to provide real-time feedback on advertisement playback across multiple client devices. By continuously monitoring and comparing actual ad output times against scheduled times, the system can identify discrepancies caused by schedule changes and adjust accordingly, improving measurement precision and reliability.
3Adaptability or versatility
If traditional data processing is used, then ad schedule can be generated, but it struggles with targeted and hyper-local advertisements
Solution Approach 1:
The patent implements a universal ACR system that can detect and identify all types of advertisements regardless of their targeting or localization. The system processes video streams from multiple sources and client devices, making it adaptable to various ad formats including targeted and hyper-local advertisements, which traditional single-purpose systems cannot handle effectively.
Data Source
AI summary
Data indicative of times at which at least one item of supplemental video content was output via a plurality of client devices may be received. A first time at which the at least one item of supplemental video content was output via a greatest quantity of client devices of the plurality of client devices may be determined. A second time at which the at least one item of supplemental video content was output via a second greatest quantity of client devices of the plurality of client devices may also be determined. A schedule associated with output of the at least one item of supplemental video content may be generated based at least on the first time and the second time.