Video Ad Viewability Measurement via Device Self-Sensing
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Solution Overview
Problem
Conventional digital video advertising systems rely on reported end user device properties, which can be erroneous, fraudulent, or limited, leading to inaccurate targeting and viewability measurements, and fail to account for actual device conditions that affect ad effectiveness.
Innovation Solution
A video advertising system that measures end user device properties directly, such as video player size, bandwidth, and geographic location, to select and display ads more accurately, and measures viewability even in challenging environments using statistical inferences, allowing for real-time adjustments to ad playback based on visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses reported end user device properties from conventional advertising systems, then the system operation is simple, but the measurement precision is low and properties may be erroneous or fraudulent
Solution Approach 1:
The end user device performs self-measurement of its own properties (video player size, bandwidth, geographic location) through software running directly on the device. This eliminates reliance on external reporting mechanisms and ensures accurate, fraud-resistant data collection for advertising targeting.
Solution Approach 2:
The patent replaces the mechanical/reporting-based property acquisition system with a software-based direct measurement system. Instead of devices reporting properties through communication protocols that can be manipulated, software directly measures properties using device sensors and system APIs, substituting indirect reporting with direct digital measurement.
2Reliability
If the system measures actual device properties directly, then the targeting accuracy is improved, but the device complexity increases
Solution Approach 1:
The end user device's software performs self-measurement of device properties including video player dimensions, bandwidth capabilities, and geographic location through GPS. This self-service approach ensures reliable data for ad selection without requiring complex external verification systems.
Solution Approach 2:
The software running on the end user device serves multiple functions: it acts as both the advertisement player and the property measurement tool. This multi-functionality reduces overall system complexity by consolidating measurement and playback capabilities within a single software component on the device.
3Measurement precision
If the system uses conventional viewability reporting methods, then the implementation is simple, but the measurement precision is low and cannot detect scrolling away from video
Solution Approach 1:
The software continuously monitors the position of the video player within the device display and provides real-time feedback about viewability status. By detecting when the video moves out of the visible screen area due to scrolling, the system generates accurate viewability metrics that reflect actual user exposure to advertisements.
Solution Approach 2:
The system performs preliminary measurements of device properties and viewability conditions before ad delivery decisions are made. By pre-measuring video player size, bandwidth, and initial viewability status, the system can make informed targeting decisions and adjust ad delivery based on predicted viewability outcomes.
4Adaptability or versatility
If the system targets ads based on reported properties, then the targeting process is fast, but the adaptability to actual device conditions is poor
Solution Approach 1:
The software performs preliminary measurement of device properties (video player size, bandwidth, location) before the ad selection process. This advance measurement ensures that when ad targeting decisions are made, the system already has accurate device condition data, enabling both fast selection and high adaptability to actual device capabilities.
Solution Approach 2:
The system dynamically adapts ad selection based on real-time device conditions measured by the software. Instead of static targeting based on reported properties, the system adjusts ad delivery decisions according to actual measured properties such as video player dimensions and bandwidth availability, ensuring optimal ad performance for each device.
Data Source
AI summary
A video advertising system, methods, and apparatus are disclosed, which may include an advertising system, including an advertising server and advertising console, and a user device, which may cooperate to select video advertising campaigns and display video advertisements. In an example embodiment, a method includes playing a video on a display, overlaying markings on the video while the video plays, at a first time while the video plays, measuring a first refresh rate of the video, at a second time while the video plays, performing a first operation on the markings, measuring a second refresh rate of the video at the second time, and determining an estimated area of the video displayed on the display based on the first refresh rate and the second refresh rate. In an example embodiment, a prediction model is trained to output a viewability inference for a video.