Break-Based Video Inventory Forecasting Equation
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Solution Overview
Problem
Traditional inventory forecasting models fail to accurately predict video content inventory due to constraints on breaks, such as impression and time limits, leading to discrepancies between prior actual impressions and capacity, resulting in underestimated inventory and lost revenue.
Innovation Solution
An improved forecasting technique that identifies breaks within an impression log, determines their configuration, and uses a specific equation to calculate future inventory based on the maximum permitted impressions and time, accounting for targeting attributes and duration attributes, thereby providing a more accurate forecast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional impressions-based forecast model is used, then forecasting simplicity is maintained, but forecasting accuracy deteriorates for video content inventory
Solution Approach 1:
The patent segments video inventory forecasting into distinct components: break identification, configuration determination, and equation-based calculation. This segmentation allows the system to handle the complexity of video inventory (with its multiple constraints) by breaking it down into manageable analytical steps, thereby improving forecasting accuracy without overwhelming system complexity
Solution Approach 2:
The patent introduces new parameters specific to video inventory (break configurations, maximum permitted impressions, maximum permitted time) and applies a specific equation to calculate forecasted inventory. This parameter-based approach transforms the forecasting process from simple impression counting to a multi-parameter calculation that accurately reflects video content constraints
2Measurement precision
If break constraints (impression and time limits) are not accounted for, then forecasting process is simplified, but inventory accuracy deteriorates
Solution Approach 1:
The patent performs preliminary identification and configuration determination of breaks before conducting the inventory calculation. By pre-identifying break structures and their constraints (maximum permitted impressions, maximum permitted time), the system prepares all necessary data beforehand, ensuring accurate forecasting while organizing the complexity into a systematic preliminary analysis phase
Solution Approach 2:
The patent replaces traditional mechanical impression-counting methods with an equation-based calculation system. Instead of simply counting impressions, the system uses a mathematical equation that incorporates break configurations and constraints, substituting the mechanical counting process with a more sophisticated but systematic calculation approach that improves accuracy
3Adaptability or versatility
If static impressions-based model is used, then model simplicity is maintained, but adaptability to video content deteriorates
Solution Approach 1:
The patent transitions from static impression counting to a dynamic model that accounts for video-specific characteristics such as break configurations, duration attributes, and time-based constraints. The forecasting model adapts to video content by incorporating these dynamic elements, allowing it to versatilely handle different video inventory scenarios while maintaining a structured approach through the defined equation
Data Source
AI summary
Techniques are disclosed for advantageously forecasting an inventory of a product having a particular duration (e.g., video content). The technique can include determining the particular configuration (e.g., maximum number of impressions, maximum amount of time permitted) of breaks identified within an impression log. Based on the number of breaks and the configurations of the breaks, the technique can forecast a future inventory of the product. In some implementations, the disclosed technique can identify an amount of a previous break that was not filled with video content. These forecasts can enable product sellers to better communicate with their customers, negotiate supply contracts, price their products, plan for business operations, etc.