Bandwidth-Aware Video Ad Formats for Lower Buffer Wait Time
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Solution Overview
Problem
Consumers often terminate video playback due to excessive wait times caused by advertisements, diminishing the opportunity to monetize video content with ads.
Innovation Solution
A system determines client device buffer wait time or ratio using bandwidth factors to select appropriate advertisement formats and ads, optimizing playback experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advertisements are played during video playback, then monetization opportunity is improved, but video playback wait time increases
Solution Approach 1:
The system dynamically adjusts advertisement format selection based on real-time buffer status and bandwidth conditions. Different advertisement formats (e.g., video, image, text) are selected adaptively to match the client's buffering capacity, ensuring that ads are delivered in a format that minimizes additional wait time while maintaining monetization opportunities.
Solution Approach 2:
The system changes parameters such as advertisement format type, size, and complexity based on buffer ratio and bandwidth factors. When buffer ratio is low, simpler formats with smaller data requirements are selected; when buffer ratio is high, more complex formats can be used, thereby optimizing the balance between monetization and playback wait time.
2Productivity
If larger advertisement formats are selected, then monetization revenue is improved, but buffer wait time increases
Solution Approach 1:
The system applies different advertisement formats to different local conditions (buffer status, device type, network bandwidth). Instead of using a uniform advertisement format for all users, the system tailors the advertisement quality and complexity to match each user's specific buffering capacity and device capabilities, optimizing both revenue and user experience locally.
Solution Approach 2:
The system selects advertisement formats that are partially optimized for revenue based on buffer conditions. When buffer ratio is low, it uses smaller, faster-loading formats; when buffer ratio is high, it can use larger, more revenue-generating formats. This partial optimization approach ensures that monetization is maximized within the constraints of available buffer space.
3Productivity
If advertisement delivery is increased, then monetization opportunity is improved, but video streaming performance deteriorates
Solution Approach 1:
The system performs preliminary assessment of buffer ratio and bandwidth factors before delivering advertisements. By evaluating the client's buffering status in advance, the system can pre-select appropriate advertisement formats that will not compromise video streaming performance, ensuring that ad delivery enhances monetization without degrading video quality or causing playback interruptions.
Solution Approach 2:
The system uses feedback from buffer ratio measurements and bandwidth factor reports to continuously adjust advertisement delivery strategies. Based on real-time feedback about buffering conditions, the system modifies advertisement format selection and delivery timing to maintain video streaming performance while maximizing monetization opportunities.
Data Source
AI summary
This disclosure generally relates to systems and methods that facilitate employing bandwidth factors to determine, infer, or predict a client device buffer wait time or a client device buffer ratio associated with a video playback on a client device to select an advertisement format for the video and select an advertisement to accompany the video based upon the format.