Joining Multiple User Lists via Data Exchange Engine
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in providing cost-effective, relevant advertising content to users due to limited access to user data and inefficient targeting methods across different entities.
Innovation Solution
A computer-implemented method that joins multiple user lists based on Boolean functions, allowing advertisers to create customized lists by merging user lists associated with different ownership entities, enabling targeted advertising by providing definitions and member information to consumers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple user lists from different ownership entities are merged to improve targeting precision, then the precision of user targeting is improved, but the complexity of data integration and system operation increases
Solution Approach 1:
The patent introduces a data exchange engine as an intermediary component that mediates between multiple data owners and consumers. This engine receives user lists from different ownership entities, processes them through standardized interfaces, and provides integrated results to consumers. The intermediary handles the complexity of data integration, merging, and coordination internally, while presenting a simplified interface to external users, thus resolving the contradiction between improved targeting precision and increased system complexity.
2Loss of information
If user lists from multiple entities are integrated to provide more comprehensive user data, then the relevance of advertising content is improved, but the cost of implementing and maintaining the system increases
Solution Approach 1:
The data exchange engine is designed as a universal platform that serves multiple functions: it handles data collection from various owners, performs merging and integration, manages consumer requests, and provides targeted content delivery. By creating a multi-functional system that consolidates these operations into a single engine, the patent reduces the need for separate systems for each function, thereby lowering overall implementation and maintenance costs while achieving comprehensive user data integration.
3Measurement precision
If real-time joining of user lists is performed to improve targeting accuracy, then the accuracy of content delivery is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and organizing user list data as it is received from data owners. The data exchange engine maintains ready-to-use integrated user lists that have been pre-merged and validated. When a consumer requests targeted content, the system can quickly query these pre-prepared lists without performing complex real-time joins, thus maintaining high accuracy while significantly reducing processing time and computational resource requirements.
Data Source
AI summary
A computer-implemented method comprises receiving a request for content from a user, determining two user lists that are associated with the user, each user list including a definition that characterizes members of a respective user list, determining a consumer is a subscriber to the two user lists, determining the consumer has indicated a preference to target members that are included in both user lists, and providing an indication to the consumer for all users that are included in both user lists including providing the definitions associated with both user lists along with the request to the consumer.