Viewer Emotion Detection for Ad Effectiveness Measurement
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Solution Overview
Problem
Advertisers face challenges in determining the effectiveness of advertisements due to the unreliability of traditional survey methods and coupon redemption programs, which often result in incomplete or inaccurate data regarding viewer responses.
Innovation Solution
A system that captures and analyzes images of viewers to detect their emotions and environment in real-time, selecting supplemental content based on these analyses to induce a desired emotional response, and uses feedback loops to refine content effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional survey methods or coupon redemption programs are used to determine advertisement effectiveness, then advertisers can gather some viewer response data, but the data is unreliable and incomplete due to viewer non-participation, forgetfulness, or failure to use coupons
Solution Approach 1:
The patent replaces mechanical survey methods and coupon redemption tracking with an automated image recognition system using cameras and computer vision algorithms. The system automatically captures viewer images, detects emotions through facial analysis, and tracks viewer actions without requiring manual participant engagement, thereby eliminating the reliability issues of traditional methods
Solution Approach 2:
The system enables self-service measurement by automatically capturing and analyzing viewer responses without requiring viewer participation in surveys or coupon redemption. The automated image analysis system independently processes viewer emotions and actions, generating reliable effectiveness data without human intervention from the viewer side
2Loss of time
If there is a time delay between the viewer seeing an advertisement and the viewer acting on it or completing a survey, then advertisers lose accurate timing information about viewer response, but traditional methods still attempt to capture this delayed response
Solution Approach 1:
The system performs preliminary action by continuously capturing viewer images and detecting emotions in real-time before and during the advertisement presentation. This allows the system to establish a baseline of viewer emotional state prior to ad exposure and immediately detect changes, eliminating time delay issues inherent in post-viewing surveys
Solution Approach 2:
The patent implements continuous image capture and emotion detection throughout the advertisement viewing process, maintaining uninterrupted monitoring of viewer responses. This continuous measurement approach ensures no timing information is lost, as the system constantly tracks emotional changes from pre-ad baseline through ad exposure and immediate post-ad response
3Reliability
If advertisers use cumbersome surveys or coupon redemption programs to measure advertisement effectiveness, then some viewer response data can be collected, but the process becomes complex and unreliable
Solution Approach 1:
The patent replaces complex mechanical systems of survey administration and coupon tracking with a streamlined optical system using cameras and image recognition software. This substitution simplifies the measurement process by automatically capturing viewer responses through facial expression analysis, eliminating the need for complex survey protocols and coupon redemption infrastructure
Data Source
AI summary
Embodiments are directed towards providing supplemental content to a viewer based on the viewer's environment while the viewer is viewing content. Content is provided to a content receiver for presentation to the viewer. While the viewer is viewing the content, an image of the viewer's environment is captured and analyzed to detect the context of the environment. Supplemental content is selected based on this detected context and presented to the viewer, which allows the supplemental content to be tailored to the viewer. One or more additional images of the viewer's environment are captured while the viewer is viewing the supplemental content and the context of the viewer's environment emotion while the viewer is viewing the supplemental content is detected. This subsequent context is analyzed to determine if the viewer had an expected response to the supplemental content, which can be used to determine the efficiency of the supplemental content.


