Personality-Based Message Delivery System for Auction Targeting

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Solution Overview

Problem

Current message-delivery systems, such as targeted advertising, often neglect personality characteristics, which are crucial for maximizing the effectiveness of advertisements, as they rely on keyword-matching and demographic-targeting techniques that do not account for psychological factors.

Innovation Solution

A system that infers user personality traits using machine-learning techniques based on activity data, maps these traits into pre-defined groups, and auctions message-delivery opportunities to advertisers, allowing for targeted messaging that maximizes expected benefits by selecting messages based on user preferences and bidding prices.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If keyword-matching and demographic-targeting techniques are used for message delivery, then the system complexity is reduced and ease of operation is improved, but the accuracy of audience selection and effectiveness of targeted advertising deteriorates

Engineering Contradiction:

Improveease of operationVSAvoidaccuracy of audience selection

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent changes the parameters used for targeting from simple keywords and demographics to multi-dimensional personality characteristics (Big Five traits). This allows for more precise audience selection by capturing psychological factors that influence advertising effectiveness, thereby improving measurement precision while maintaining system operability through automated inference.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces manual keyword-matching and demographic analysis with automated machine-learning-based inference of personality characteristics. This substitution improves both ease of operation (automation) and accuracy (personality-based targeting) by using computational models to analyze user behavior patterns and infer psychological traits.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If personality characteristics are incorporated into message delivery targeting, then the accuracy of audience selection is improved, but the device complexity and difficulty of detecting and measuring increase

Engineering Contradiction:

Improveaccuracy of audience selectionVSAvoiddevice complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary machine-learning model that acts as a mediator between observable user behaviors and unobservable personality characteristics. This intermediary automatically infers personality traits from behavioral data, thereby improving measurement precision without requiring direct measurement of psychological constructs or increasing system complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs self-service by automatically collecting user activity data, inferring personality characteristics, and using these inferences for targeted message delivery without requiring manual intervention. This automation reduces the practical complexity despite the sophistication of the underlying algorithms.

Inventive Principle:

Principle #25Self-service

3Reliability

If personality characteristics are used for targeted advertising, then the effectiveness of advertising is improved, but the difficulty of detecting and measuring characteristics increases

Engineering Contradiction:

Improveeffectiveness of advertisingVSAvoiddifficulty of detecting and measuring

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent replaces direct measurement of personality characteristics (which is difficult) with automated machine-learning-based inference from observable behavioral data. This substitution maintains high reliability of advertising effectiveness by accurately capturing psychological factors while eliminating the difficulty of direct measurement through computational modeling.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system uses feedback from user activity data to continuously refine personality characteristic inferences. By monitoring user behaviors and updating personality profiles based on observed patterns, the system improves measurement accuracy over time, thereby enhancing advertising effectiveness while managing the complexity of psychological measurement.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS10354284B2System and method for estimating and clustering multiple-dimension characteristics for auction-based message delivery

Publication Date: 2019.07.16 GENESEE VALLEY INNOVATIONS LLC

AI summary

One embodiment of the present invention provides a system for characteristics-based message delivery. During operation, the system receives activity data associated with a user, and infers a characteristic profile associated with the user based on the received activity data. The system further receives a plurality of messages, estimates the user's preference for the messages based on the inferred characteristic profile and content of the messages, selects a message from the plurality of messages based on the user's preference and a pre-determined bidding price associated with the message and the characteristic profile, and delivers the selected message to the user.