AI Advertisement Generation Using Social Data for Targeted Delivery

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Solution Overview

Problem

Existing advertisement production methods require significant financial investment by brands and advertisers, and there is a need for more efficient and cost-effective ways to generate and deliver targeted advertisements.

Innovation Solution

A server-based system that utilizes user social datasets and machine learning models to automatically generate and distribute advertisements to selected recipients, incorporating user input, social media data, and platform-specific recommendations to optimize advertisement content and delivery.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional advertisement production methods are used by brands and advertisers, then advertisement quality and effectiveness can be maintained, but production costs increase significantly

Engineering Contradiction:

Improveadvertisement effectivenessVSAvoidproduction cost

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The system enables users to automatically generate and send advertisements themselves using AI models, eliminating the need for professional advertisement production services. Users input basic information and the system automatically generates optimized advertisement content, reducing production costs while maintaining effectiveness through automated intelligent generation.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces traditional manual advertisement creation processes with AI-based automatic generation models. Instead of human advertisers manually creating advertisement content, the system uses machine learning models to automatically generate optimized advertisement text, images, and distribution strategies, significantly reducing production costs.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If manual advertisement creation processes are used, then advertisement content can be customized, but time consumption and production efficiency decrease

Engineering Contradiction:

Improveadvertisement customizationVSAvoidadvertisement production efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system replaces manual advertisement creation with automated AI generation models that can produce customized advertisement content rapidly. The models process user inputs and generate tailored advertisements automatically, maintaining customization capabilities while dramatically improving production efficiency and reducing time consumption.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system allows users to input various parameters such as target audience characteristics, product information, and platform preferences, which the AI models then use to dynamically adjust and optimize advertisement content. This parameter-based approach enables flexible customization while maintaining high production efficiency through automated processing.

Inventive Principle:

Principle #35Parameter changes

3Quantity of substance

If broad audience targeting is used for advertisements, then advertisement reach increases, but advertisement effectiveness and user acceptance decrease

Engineering Contradiction:

Improveadvertisement reachVSAvoiduser acceptance

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system generates different optimized advertisement versions tailored to specific target user groups rather than using a single broad-targeting approach. By analyzing user characteristics and generating customized content for different segments, the system maintains high user acceptance while achieving effective reach through precisely targeted distribution.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system uses user social dataset information and platform feedback to continuously optimize advertisement content and targeting. By incorporating feedback from user interactions and social data analysis, the system adjusts advertisement strategies to improve both reach and acceptance, ensuring advertisements are delivered to the most appropriate audiences.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250371582A1Method and server for generating and sending advertisement

Publication Date: 2025.12.04 LIN CHIH CHANG

AI summary

A method for generating and sending an advertisement is implemented by a server that communicates with an initiating device operated by an initiating user and with at least one online platform, each online platform communicating with multiple promotion-end devices. The method includes: obtaining multiple sets of promotional information related to an object, and transmitting the same to the initiating device for the initiating device to obtain and transmit to the server a set of basic promotional information; obtaining a target user account, and a target platform based on the target user account; generating a set of target promotional information; making the target user account serve as a promotion user account, and transmitting the set of target promotional information and the promotion user account to the target platform for the target platform to transmit the set of target promotional information to a target promotion-end device corresponding to the promotion user account.