Video Ad Forecasting via Syndication Constraints
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Solution Overview
Problem
Existing forecasting methods for digital content consumption, particularly video content, are inaccurate as they fail to incorporate key drivers of consumption and do not adequately translate forecasted content consumption into available advertising inventory, especially when content items have individual identities and are syndicated across various platforms, leading to inaccurate projections and missed opportunities in advertising sales.
Innovation Solution
A computer-driven apparatus that collects metadata from consumers' devices and adjusts forecasting inputs based on actual delivery history, incorporating factors like legal display rights, consumption patterns, age of content, distribution points, and technical constraints to provide a net available supply forecast for advertising opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If historical trend projection is used to forecast future content consumption, then the forecasting method is simple and easy to implement, but the forecast accuracy deteriorates because it does not incorporate key drivers of consumption specific to individual content items
Solution Approach 1:
The patent segments the forecasting approach by creating distinct methodologies for traditional web content versus video content. For video content, it segments the analysis into multiple key drivers (content attributes, distribution points, technical constraints, legal rights) rather than using a single historical trend projection, thereby improving accuracy while maintaining implementation feasibility through structured data collection.
Solution Approach 2:
The patent changes the parameters used for forecasting from simple historical consumption patterns to multiple specific parameters including content attributes (genre, duration, rating), distribution point characteristics, technical constraints (screen size, bandwidth), and legal display rights. This parameter expansion significantly improves forecast accuracy for video content while the structured approach keeps implementation manageable.
2Device complexity
If existing forecasting methods are used that do not account for syndication variability, then the forecasting system is simple, but the translation of forecasted consumption into available advertising inventory is inaccurate
Solution Approach 1:
The patent segments the advertising inventory forecasting by distribution point, accounting for variability in what advertisements can be displayed at each location. It separately evaluates technical constraints (screen size, bandwidth), legal rights (territorial restrictions, time windows), and content attributes for each distribution point, thereby accurately translating consumption forecasts into usable advertising inventory while maintaining systematic organization.
Solution Approach 2:
The patent introduces an intermediary forecasting system that acts as a bridge between raw consumption data and actionable advertising inventory. This intermediary layer processes consumption forecasts through multiple filtering stages (technical constraints, legal rights, content attributes) to produce accurate advertising opportunity data, without requiring direct complex integration between all system components.
3Measurement precision
If forecasting incorporates multiple key drivers and syndication variability, then forecast accuracy improves, but the complexity of the forecasting system increases
Solution Approach 1:
The patent manages complexity by segmenting the forecasting system into distinct functional modules: data collection module (gathering content attributes, distribution information, technical constraints), processing module (applying legal rights filters, evaluating content-distribution compatibility), and output module (generating advertising inventory forecasts). This modular segmentation maintains high forecast accuracy while keeping system complexity manageable through organized structure.
Solution Approach 2:
The patent creates a universal forecasting framework that handles multiple content types and distribution scenarios through a single integrated system. The system universally applies the same key driver analysis (content attributes, distribution points, technical constraints, legal rights) across all video content, eliminating the need for separate forecasting systems for different content categories and reducing overall system complexity.
Data Source
AI summary
A forecast for compatible advertisement opportunities, compatible with a class of advertisements, that will be available over a future time period is generated. For a content item associated with one or more advertisement opportunities, one or more compatible advertisement opportunities of the one or more advertisement opportunities are determined based on characteristics of the class of advertisements. Expected output of the content item over the future time period may be determined from historical data of output of other content items similar to the content item, and may be adjusted based on additional information, such as actual output of the content item. The forecast may be generated from the compatible advertisement opportunities associated with the content item and the expected output of the content item.