Social Network Feed Aggregation System for Contextual Ad Targeting
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Solution Overview
Problem
Businesses struggle to efficiently collect, analyze, and utilize social network data across multiple platforms to create effective advertising campaigns, as existing methods lack the ability to tailor advertisements based on users' social context and relevance in real-time.
Innovation Solution
A system and method for aggregating social network feed information from multiple sources, parsing user activity data to extract targeting parameters, matching them with advertising conditions, and deploying contextually relevant campaigns across various social media platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If social network data is collected from multiple platforms to improve advertising effectiveness, then the relevance and targeting precision improve, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent introduces an intermediary system comprising data aggregation modules, parsing modules, and matching modules that serve as mediators between multiple social network platforms and the advertising campaign system. These intermediary components consolidate and standardize data from diverse sources, enabling precise targeting without requiring direct complex integrations with each platform, thus resolving the contradiction between targeting precision and system complexity
Solution Approach 2:
The system employs universal data structures and standardized interfaces that can handle multiple types of social network data (user profiles, activity logs, contextual information) through a unified framework. This multi-functional approach allows the same system architecture to process data from different platforms consistently, achieving high targeting precision while controlling system complexity through reusability
2Productivity
If real-time analysis of user activity data is performed to improve campaign relevance, then the advertising effectiveness improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and structuring social network data in advance, creating standardized data formats and pre-computing relevant user attributes before campaigns are launched. This preliminary preparation reduces the computational burden during real-time campaign execution, enabling fast deployment while maintaining analytical depth
Solution Approach 2:
The data processing workflow is segmented into distinct modular stages: data collection, parsing, analysis, and campaign deployment. Each segment handles specific tasks independently, allowing parallel processing and optimizing the timing of computationally intensive operations. This segmentation reduces overall processing time while maintaining comprehensive analysis capabilities
3Measurement precision
If comprehensive user data is aggregated from multiple social networks to improve targeting accuracy, then the advertising relevance improves, but the data volume and analysis complexity increase
Solution Approach 1:
The system extracts only the most relevant and valuable data elements from comprehensive user profiles and activity logs, such as key demographic attributes, primary interests, and contextual signals. By selectively extracting essential information rather than processing entire data sets, the system achieves high targeting accuracy while reducing data volume and analysis complexity
Data Source
AI summary
In accordance with disclosed embodiments, there are provided methods, systems, and apparatuses for aggregating social network feed information including, for example, means for receiving user activity data from one or more social networks; parsing the user activity data to render a plurality of targeting parameters culled from the user activity data; matching one or more of the plurality of targeting parameters with advertising conditions for a social media campaign, wherein the advertising conditions of the social media campaign are contextually relevant to the one or more targeting parameters matched; recommending the social media campaign via a user interface; receiving authorization to launch the social media campaign via input received at the user interface or automatically launching the social media campaign based on pre-defined parameters; and deploying the social media campaign to one or many social media networks. Other related embodiments are disclosed.