Emotional Mapping for Online Advertising Precision
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Solution Overview
Problem
Emotional targeting in online advertising remains underutilized despite its potential, as existing methods lack the precision to effectively capture and leverage users' emotional states for targeted advertising.
Innovation Solution
The development of techniques for emotional targeting, including emotional mapping and the use of emoticlips, which involve classifying users into emotional states based on their online behavior and interactions, and utilizing rich media segments to facilitate communication of emotional states for targeted advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If emotional targeting techniques are implemented, then advertising performance and relevance are improved, but system complexity and difficulty of measuring emotional states increase
Solution Approach 1:
The patent uses online behavior data, content interactions, and device sensors as intermediary indicators to infer emotional states indirectly. Rather than directly measuring emotions, the system analyzes behavioral proxies such as browsing patterns, social media interactions, and physiological signals from mobile devices to determine emotional states, thereby avoiding the complexity of direct emotional measurement while maintaining measurement precision
Solution Approach 2:
The patent replaces complex psychological and neurological measurement systems with computational analysis of digital footprints and behavioral data. Instead of using intricate devices to directly measure emotions, the system uses algorithms to analyze online behavior patterns, content consumption, and device usage metrics, substituting mechanical/physiological measurement with information processing
2Measurement precision
If granular user tracking is implemented, then targeting precision is improved, but user privacy concerns and data collection complexity increase
Solution Approach 1:
The patent applies different levels of data collection and processing to different users and contexts. Rather than uniformly tracking all user activities with the same intensity, the system adapts the granularity of tracking based on user preferences, device settings, and contextual relevance, allowing precise targeting where appropriate while preserving privacy where not needed
Solution Approach 2:
The system dynamically adjusts tracking parameters such as data collection frequency, detail level, and retention period based on user behavior patterns and engagement levels. High-value users or those showing strong purchase intent receive more intensive tracking, while casual users receive minimal tracking, thereby optimizing targeting precision while minimizing privacy intrusion for the overall user base
Data Source
AI summary
Methods and systems are provided for emotional mapping, such as of online users, based at least in part on online activities of users. Techniques are provided in which information including a set of emotional states is generated or obtained, such as a hierarchical network of emotional states representing a spectrum of human emotions. Information regarding user online activities and content choices of a user is obtained. Based at least in part on this information, the user is classified into an emotional state of the set of emotional states, and advertisements or content may be targeted to the user accordingly.