Biometric Advertising System Receptivity Analysis
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Solution Overview
Problem
Traditional target advertising methods are inefficient as they do not account for audience receptivity, leading to ads being drowned out by 'noise' and failing to effectively capture attention, with current systems relying on verbal or social media conversations rather than physiological or emotional states.
Innovation Solution
A system that utilizes biometric information such as heart rate, sleep patterns, location, and food intake, paired with facial recognition technology, to determine emotional and physiological receptivity, allowing for personalized and effective targeted advertising by selecting ads based on calculated receptivity probabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional target advertising methods are used based on verbal or social media conversations, then the advertising system is simple to operate, but the advertising effectiveness is low due to audience receptivity not being accounted for and ads being drowned out by noise
Solution Approach 1:
The patent segments the advertising system into multiple independent components: biometric data collection module, emotional state analysis module, receptivity probability calculation module, and ad selection module. This segmentation allows the system to process complex biometric information while maintaining operational simplicity through modular architecture.
Solution Approach 2:
The patent introduces an intermediary processing layer that translates raw biometric data into meaningful emotional state indicators and receptivity probabilities. This intermediary layer (facial recognition technology and analysis algorithms) bridges the gap between simple data collection and complex advertising decision-making, enhancing effectiveness without proportionally increasing operational complexity.
2Productivity
If ads are delivered frequently to ensure message retention, then advertising coverage is improved, but audience receptivity decreases due to promotional clutter and noise
Solution Approach 1:
The patent performs preliminary analysis of audience emotional states and receptivity probabilities before ad delivery. By pre-assessing when audiences are most receptive based on biometric indicators, the system delivers ads at optimal moments rather than using frequent blanket delivery, thereby maintaining productivity while minimizing promotional clutter.
Solution Approach 2:
The patent dynamically changes the delivery parameter from fixed-frequency scheduling to variable-frequency delivery based on real-time receptivity probability calculations. When receptivity is high, ads are delivered; when receptivity is low, delivery is postponed. This parameter change optimizes advertising efficiency while reducing harmful promotional clutter.
3Measurement precision
If biometric information and facial recognition technology are used to determine emotional and physiological receptivity, then advertising precision is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent segments biometric data processing into distinct functional modules: data collection from biometric devices, facial recognition analysis, emotional state determination, and receptivity probability calculation. This segmentation enables high measurement precision while managing complexity through modular, specialized processing units.
Solution Approach 2:
The patent replaces manual or simple survey-based receptivity measurement with automated biometric sensing and facial recognition technology. This substitution provides objective, real-time measurement of emotional states with high precision, eliminating the need for complex manual assessment systems while achieving superior measurement accuracy.
4Ease of operation
If ads are targeted based on verbal conversations or social media posts, then implementation is straightforward, but the ability to capture genuine emotional receptivity is limited
Solution Approach 1:
The patent replaces text-based or voice-based inference of emotional states with direct biometric measurement through facial recognition technology. This substitution provides more reliable and accurate detection of genuine emotional receptivity while maintaining ease of operation through automated processing, eliminating the need for complex text analysis or interpretation.
Data Source
AI summary
An apparatus for providing customized advertisements includes a database that stores a plurality of electronic advertisements, receives biometric information of a client from at least one biometric device of the client, and receives receptivity information of the client responding to the plurality of electronic advertisements, as well as a processor that accesses the database, and maps the biometric information and the receptivity information and analyzes the mapped information to generate customized marketing data. The processor also calculates a receptivity probability for each of the plurality of electronic advertisements based on the customized marketing data by using current biometric state of the client, selects an electronic advertisement from the plurality of electronic advertisements based on the calculated receptivity probabilities, and outputs to the client the selected electronic advertisement.