Native Community Advertising Placement for Topic-Targeted Engagement
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Solution Overview
Problem
Existing advertising platforms fail to effectively integrate advertisements into community spaces as native content, lacking the ability to target specific topics and user interactions, leading to a sense of heterogeneity and reduced marketing effectiveness.
Innovation Solution
A computer system and method that registers advertising materials as native content within community platforms, utilizing AI-based machine learning to identify relevant topics and spaces, allowing advertisements to be posted as comments or posts, and enabling user interactions, with control over exposure based on targeting information and bid rankings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If advertisements are displayed in separate advertising areas, then advertising placement is simple, but user engagement is reduced and marketing effectiveness decreases
Solution Approach 1:
The patent merges advertisements with native community content by displaying ads as posts or comments within the community feed rather than in separate advertising sections. This integration allows advertisements to be seamlessly embedded in the natural flow of community interactions, improving user engagement while maintaining placement feasibility through automated selection of appropriate community spaces.
2Productivity
If advertisements are integrated as native content, then user engagement increases, but system complexity increases due to topic targeting and AI processing requirements
Solution Approach 1:
The patent introduces an intermediary advertising platform that acts as a mediator between advertisers and community spaces. This platform handles the complex tasks of topic analysis, AI-based content generation, and bid ranking management, allowing community platforms to benefit from native advertising integration without directly implementing the complex targeting and processing systems themselves.
Solution Approach 2:
The system dynamically adjusts advertising parameters including bid rankings, topic relevance thresholds, and content generation parameters based on real-time community data and user behavior patterns. This allows the system to optimize engagement while managing complexity through automated parameter adaptation rather than rigid fixed rules.
3Manufacturing precision
If topic-based targeting is implemented, then advertising relevance improves, but measurement and detection difficulty increases due to AI-based topic identification requirements
Solution Approach 1:
The patent uses AI-based topic modeling to create simplified representations of community topics and content themes. Instead of requiring complex real-time analysis of every post, the system copies and matches against pre-established topic profiles and keyword associations, reducing the computational complexity of topic detection while maintaining relevant advertising targeting.
Data Source
AI summary
An advertising method may include registering an advertising material and targeting information; determining at least one community corresponding to the targeting information; and controlling the advertising material to be exposed in the form of native content on the community.