Ad Exposure Threshold Adjustment for Personalized Frequency Caps
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Solution Overview
Problem
Existing advertisement delivery systems fail to accurately predict individual user exposure thresholds for repeat advertisements, leading to potential user frustration and loss of viewership due to repeated presentations, as current methods rely on demographics and stagnant frequency caps.
Innovation Solution
Systems and methods to determine adjusted advertisement exposure thresholds by tracking user interactions and environmental factors, allowing for personalized and dynamic frequency cap adjustments based on viewing statistics, environment, and advertisement characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single exposure threshold is used for all users, then the system is simple to implement, but advertisement effectiveness decreases due to inability to account for individual user differences
Solution Approach 1:
The patent segments the exposure threshold determination by dividing users into different groups based on demographics, viewing statistics, environment, and advertisement characteristics. Instead of using a single threshold for all users, the system creates multiple exposure threshold values tailored to different user segments, thereby improving advertisement effectiveness while managing complexity through structured classification.
Solution Approach 2:
The patent implements dynamic exposure thresholds that adapt based on real-time factors including viewing statistics, environmental conditions, and advertisement characteristics. The exposure threshold is not fixed but dynamically adjusted for each user based on their specific context, allowing the system to optimize advertisement delivery effectiveness while responding to individual user behaviors.
2Reliability
If exposure threshold is increased to reduce viewer fatigue, then viewer retention improves, but advertisement effectiveness decreases due to reduced exposure opportunities
Solution Approach 1:
The patent applies local quality by tailoring exposure thresholds to specific user contexts, demographics, and viewing situations. Instead of applying a uniform high threshold to all users, the system determines appropriate exposure levels for each user segment based on their specific characteristics, thereby maintaining viewer retention while preserving advertisement effectiveness through localized optimization.
Solution Approach 2:
The patent changes the exposure threshold parameter dynamically based on multiple factors including viewing statistics, environment, and advertisement characteristics. By adjusting this parameter on a per-user, per-context basis, the system optimizes the balance between viewer retention and advertisement effectiveness, preventing both over-exposure fatigue and under-exposure inefficiency.
3Measurement precision
If individual exposure thresholds are determined for each user, then advertisement delivery accuracy improves, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments users into distinct groups based on demographics, viewing behavior patterns, environmental factors, and advertisement characteristics. This segmentation enables the system to determine exposure thresholds with higher precision for each segment while managing complexity through structured classification rather than treating every user as entirely unique.
Solution Approach 2:
The patent incorporates feedback mechanisms where viewing statistics and user interactions are continuously monitored and fed back into the exposure threshold determination process. This feedback loop allows the system to refine and adjust exposure thresholds based on actual user responses, improving measurement precision while using the feedback to optimize future threshold determinations.
Data Source
AI summary
Systems, apparatuses, and methods are described for adjusted exposure threshold values. Each user may be associated with one or more of a plurality of exposure threshold values, for example, a frequency cap value, that may be a cap (e.g., threshold) on the number of times a repeat advertisement content may be output to a user. Exposure threshold values may be modified based on one or more viewing statistics, for example, information about one or more interactions of the user associated with one or more outputs of repeat advertisement content, environment information, and/or one or more advertisement characteristics.